full text - Caspar Bgsu - Bowling Green State University

Aggression 

Volume 75

Advances 

in 

Genetics, Volume 75 

Serial Editors 

Theodore Friedmann 

University of California at San Diego, School of Medicine, USA 

Jay C. Dunlap 

Dartmouth Medical School, Hanover, NH, USA 

Stephen F. Goodwin 

University of Oxford, Oxford, UK

Volume 75 

Aggression 

Edited by 

Robert Huber 

JP Scott Center for Neuroscience 

Mind & Behavior, Biological Sciences 

Bowling Green State University, Bowling Green, OH, USA 

Danika L. Bannasch 

Department of Population Health and Reproduction 

School of Veterinary Medicine, University of California 

Davis, CA, USA 

Patricia Brennan 

Department of Psychology 

Emory University, Atlanta, GA, USA 

Editorial Assistant 

Kate Frishman 

Bowling Green, OH, USA 

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11 12 13 10 9 8 7 6 5 4 3 2 1

Contents 

Contributors 

ix 

1 Aggression 1 

Robert Huber and Patricia A. Brennan 

2 Evolutionary Aspects of Aggression: The Importance 

of Sexual Selection 7 

Patrik Lindenfors and Birgitta S. Tullberg 

I. Introduction 8 

II. Sexual Selection 9 

III. Mating Systems 12 

IV. When to Fight and When to Flee 13 

V. Case Studies: Sexual Dimorphism 16 

VI. Humans and the Mammalian Pattern 20 

Acknowledgment 20 

References 21 

3 Signaling Aggression 23 

Moira J. van Staaden, William A. Searcy, and 

Roger T. Hanlon 


II. Bird Song Signals Aggressive Intentions: Speak Softly 

and Carry a Big Stick 31 

III. Visual Displays Signal Aggressive Intent in Cephalopods: 

The Sweet Smell of Success 37 

Acknowledgments 44 

References 44 

v

vi 

Contents 

4 Self-Structuring Properties of Dominance Hierarchies: 

A New Perspective 51 

Ivan D. Chase and Kristine Seitz 


II. Definitions 53 

III. Animal Models 55 

IV. Factors Affecting Dominance Relationships in Pairs 

of Animals 58 

V. Formation of Dominance Relationships and Dominance 

Hierarchies in Groups 63 

VI. A New Approach to Explaining the Formation of Linear 

Hierarchies: Behavioral Processes 70 

VII. Conclusion 74 


References 75 

5 Neurogenomic Mechanisms of Aggression in 

Songbirds 83 

Donna L. Maney and James L. Goodson 

I. Aggression in Context 84 

II. Hormonal Mechanisms of Aggression 87 

III. Transcriptional Activity and Neural Mechanisms 

of Aggression in Birds 95 

IV. A Natural Model Uniting Social Behavior, Hormones, and 

Genetics 103 

V. Future Directions 109 


References 110 

6 Genetics of Aggression in Voles 121 

Kyle L. Gobrogge and Zuoxin W. Wang 


II. The Prairie Vole Model 122 

III. Neural Correlates 125 

IV. Neural Circuitry 127 

V. Neurochemical Regulation of Selective Aggression 128 

VI. Molecular Genetics of Selective Aggression 136 

VII. Drug-induced Aggression 136 

VIII. Conclusions and Future Directions 138

Contents 

vii 



7 The Neurochemistry of Human Aggression 151 

Rachel Yanowitch and Emil F. Coccaro 


II. Serotonin 152 

III. Dopamine 157 

IV. Norepinephrine (Noradrenaline) 159 

V. GABA 160 

VI. Peptides 162 

VII. Conclusion 162 


8 Human Aggression Across the Lifespan: Genetic 

Propensities and Environmental Moderators 171 

Catherine Tuvblad and Laura A. Baker 

I. Heritability of Aggression: Twin and 

Adoption Studies 174 

II. G E Interaction in Aggressive Behavior 197 

III. Specific Genes for Aggressive Behavior: Findings 

from Molecular Genetic Studies 203 

IV. Conclusions 205 


9 Perinatal Risk Factors in the Development of 

Aggression and Violence 215 

Jamie L. LaPrairie, Julia C. Schechter, 

Brittany A. Robinson, and Patricia A. Brennan 


II. The Neurobiological and Psychophysiological Systems 

Involved in the Regulation of Aggression 

and Violence 217 

III. Perinatal Factors Related to the Development 

of Aggression 227 

IV. Genetic Contributions 238 

V. Conclusions 242 

References 243

viii 

Contents 

10 Neurocriminology 255 

Benjamin R. Nordstrom, Yu Gao, Andrea L. Glenn, 

Melissa Peskin, Anna S. Rudo-Hutt, Robert A. Schug, 

Yaling Yang, and Adrian Raine 


II. Psychodynamic Theories 257 

III. Neuroimaging 258 

IV. Neuropsychological Testing 262 

V. Psychophysiological Evidence 263 

VI. Genetics 266 

VII. Nongenetic Risk Factors 269 

VIII. The Limitations and Potential of Neurocriminology 272 

IX. Modifiable Risk Factor Interventions 273 

X. Conclusion 274 


Index 285

Contributors 

Numbers in parentheses indicate the pages on which the authors’ contributions begin. 

Laura A. Baker (171) University of Southern California, Los Angeles, 

California, USA 

Patricia A. Brennan (1, 215) Department of Psychology, Emory University, 

Atlanta, Georgia, USA 

Ivan D. Chase (51) Department of Sociology, Stony Brook University, Stony 

Brook, New York, USA 

Emil F. Coccaro (151) Clinical Neuroscience Research Unit, Department of 

Psychiatry, The University of Chicago Pritzker School of Medicine, 

Chicago, Illinois, USA 

Yu Gao (255) Department of Psychology, Brooklyn College, New York, USA 

Andrea L. Glenn (255) Department of Child and Adolescent Psychiatry, 

Institute of Mental Health, Singapore, Singapore 

Kyle L. Gobrogge (121) Department of Psychology and Program in 

Neuroscience, Florida State University, Tallahassee, Florida, USA 

James L. Goodson (83) Department of Biology, Indiana University, 

Bloomington, Indiana, USA 

Roger T. Hanlon (23) Marine Resources Center, Marine Biological Laboratory, 

Woods Hole, Massachusetts, USA 

Robert Huber (1) JP Scott Center for Neuroscience, Mind & Behavior, 

Biological Sciences, Bowling Green State University, Bowling Green, 

Ohio, USA 

Jamie L. LaPrairie (215) Department of Psychology, Emory University, 


Patrik Lindenfors (7) Department of Zoology, and Centre for the Study of 

Cultural Evolution, Stockholm University, Stockholm, Sweden 

Donna L. Maney (83) Department of Psychology, Emory University, Atlanta, 

Georgia, USA 

Benjamin R. Nordstrom (255) Department of Psychiatry, University of 

Pennsylvania, Philadelphia, USA 

Melissa Peskin (255) Department of Psychology, University of Pennsylvania, 

Philadelphia, USA 

Adrian Raine (255) Departments of Psychiatry, Psychology and Criminology, 

University of Pennsylvania, Philadelphia, USA 

ix

x 

Contributors 

Brittany A. Robinson (215) Department of Psychology, Emory University, 


Anna S. Rudo-Hutt (255) Department of Psychology, University of 

Pennsylvania, Philadelphia, USA 

Birgitta S. Tullberg (7) Department of Zoology, Stockholm University, 

Stockholm, Sweden 

Julia C. Schechter (215) Department of Psychology, Emory University, 


Robert A. Schug (255) Department of Criminal Justice, California State 

University, Long Branch, USA 

William A. Searcy (23) Department of Biology, University of Miami, Coral 

Gables, Florida, USA 

Kristine Seitz (51) Department of Biology, Stony Brook University, Stony 

Brook, New York, USA 

Catherine Tuvblad (171) University of Southern California, Los Angeles, 

California, USA 

Moira J. van Staaden (23) Department of Biological Sciences and JP Scott 

Center for Neuroscience, Mind & Behavior, Bowling Green State 

University, Bowling Green, Ohio, USA 

Zuoxin W. Wang (121) Department of Psychology and Program in Neuroscience, 

Florida State University, Tallahassee, Florida, USA 

Yaling Yang (255) Laboratory of Neuro Imaging, University of California, 

Los Angeles, USA 

Rachel Yanowitch (151) Clinical Neuroscience Research Unit, Department of 

Psychiatry, The University of Chicago Pritzker School of Medicine, 

Chicago, Illinois, USA

1 

Aggression 

Robert Huber* and Patricia A. Brennan † 

*JP Scott Center for Neuroscience, Mind & Behavior, Biological Sciences, 

Bowling Green State University, Bowling Green, Ohio, USA 

† Department of Psychology, Emory University, Atlanta, Georgia, USA 

Aggression ranks among the most misunderstood concepts in all the behavioral 

sciences. It is commonly viewed by the general public as an aberrant form of 

behavior, with situations of conflict pictured as unfavorable and stressful circumstances, 

brought about by amoral urges, in critical need of our cognitive control, 

and with negative consequences for all involved. Such a view fundamentally 

misunderstands the biological significance of the behaviors that occur during 

conflict. Deeply rooted in the demands of the natural world, an individual must 

fulfill its demands for self-preservation, defend its interests, or compete for 

limited vital resources. Basic tendencies for aggression are virtually ubiquitous 

throughout the animal kingdom, regardless of its bearer’s neural or cognitive 

faculties, phylogenetic origins, or sociobiological circumstances. Just as widespread, 

however, are fundamental rules that govern physical conflict, such that 

cases of unbridled hostility are surprisingly rare. In most species, visual 

and elaborately ritualized displays effectively channel aggression, structure how 

individuals interact, and govern the conflict’s resolution. 

As we witness animals engaged in situations of conflict, we cannot help 

but be drawn in by the behavior’s inherent relevance to our own biological roots. 

The knowledge that human aggression arises from our genetic heritage makes 

it all the more likely that it is of an adaptive nature. As we study the 

individuals and environments where aggression is most commonly displayed, 

we gain a better understanding of when aggression and violence may serve 

an adaptive function and when it may not. Current research points to the 

importance of delineating subtypes of aggression, focusing on such concepts as 

proactive and reactive, direct and indirect, and adolescent limited versus life 

course persistent. Each of these types of aggression has a distinct etiology and 

Advances in Genetics, Vol. 75 0065-2660/11 $35.00 

Copyright 2011, Elsevier Inc. All rights reserved. 

DOI: 10.1016/B978-0-12-380858-5.00016-2

2 Huber and Brennan 

utility, depending upon the social environment in which the individual must 

function. For example, reactive aggression is aggression that occurs in response to 

a threat in the external environment. It is easy to see how this type of aggression 

may have its basis in our inherent survival instincts. Nevertheless, a propensity 

for reactive aggression may be truly dysfunctional in environments that pose low 

levels of threat, like many of those in which children in Western societies are 

now raised. A more comprehensive understanding of how biology, behavior, and 

environment intersect is paramount in the study of human violence and 

aggression. 

Studies of aggression, its motives, and its causes are of central interest to a 

wide range of academic disciplines—behavioral genetics, evolution, neuroscience, 

psychology, sociology, and criminology, to name just a few. Despite the 

wealth of empirical and theoretical attention, it is remarkable that a comprehensive 

synthesis of aggression has stubbornly remained elusive. This partly stems 

from the fact that the term “aggression” neither maps cleanly onto a monolithic 

behavioral phenomenon nor lends itself to representation by a simple explanatory 

concept. Another explanation for this paradox must reside in the absence of a 

unified, operational definition of aggression across disciplines, or even of a general 

agreement on what the term actually includes. For instance, most psychologists 

define aggression as “all behavior that is intended to cause bodily harm.” Other 

widely adopted classifications of aggression recognize subtypes, ranging from 

competition between males, a mother’s efforts to protect her offspring, or fighting 

as a learned response to cope with a particular situation. Biologists regard a 

definition focused solely on injury as insufficient as this excludes a wide range of 

threat behaviors directed at rivals, for example, birds that challenge their adversaries 

with song, an impala’s exaggerated strutting as a signal of strength, or a wolf’s 

territorial claims via scent markings. Moreover, there is little agreement on 

whether a predator’s hunting behavior should be included. A lion chasing and 

killing a gazelle undoubtedly inflicts injury, but is this more akin to a cow cropping 

the top off a clump of grass, or to an elephant bull inflicting serious injury to a rival 

in battle Moreover, behavior in aggressive encounters always balances contrasting 

impulses for approach and attack with a tendency to flee—rarely is either 

present entirely alone. To acknowledge the difficulty of disentangling these 

components, the term “agonistic behavior” has been introduced. The term specifically 

addresses the balance of forces for both attacking and fleeing and it accommodates 

all instances of attack and threat (i.e., offensive agonistic behavior) as 

well as escape and submission (i.e., defensive agonistic behavior). 

As with any other characteristic, natural selection is assumed to 

enhance aggression’s overall effectiveness. High ranking individuals are likely 

to display a favorable combination of strength, along with an ability to titer 

their levels of aggression, to pick fights that are winnable, and to only compete 

in those that are worth it. Hyperaggressive phenotypes exist in most systems.

1. Aggression 3 

These exhibit fighting that greatly exceeds the most effective norm, they 

readily launch the initial attack even in situations where they ought not to, 

are overly eager to escalate or retaliate, show a willingness to follow an 

excessively physical trajectory even when an opponent has already withdrawn, 

or fail to back down in situations where there is little prospect of winning. 

Such behaviors rarely make for an effective strategy, as they coincide with 

greater risk of injury or death, or in the best-case scenario, attaining a 

low rank. 

A thorough analysis of aggression minimally demands that we (1) 

capture the essence of an inherently multifaceted phenotype, (2) address underlying 

elements of motivation that are not always readily observed or elicited, 

(3) understand the various scenarios and contexts that influence its expression, 

(4) decipher the neural, hormonal, and genetic causes that are at work, and (5) 

explore how its components are shaped by evolution. The chapters in this 

volume aim to provide a comprehensive overview of these topics as their authors 

unravel the individual behavioral and neural strands constituting situations of 

conflict. 

Initial chapters of the volume characterize the elemental building 

blocks of aggression; they assess, precisely delineate, and account for aggression’s 

different and unique components, and explain how intricate behavioral constructs 

often emerge from much simpler roots. The initial chapters review 

aggression from a predominantly evolutionary perspective. Conflicts are energetically 

costly and carry inherent risks. Natural selection offers a powerful conceptual 

tool as it focuses on an individual’s behavioral strategies and decision 

making in ways that maximize its fitness. Evolution can only exert its influence 

on characters that depend, at least partially, on genetic underpinnings. Lindenfors 

and Tullberg (Chapter 2) discuss the significance of sexual selection as a key 

evolutionary structuring force in aggression. In most scenarios, ritualized displays 

take the place of unchecked, aggressive interactions. Game theory offers a 

powerful framework for why animals only tend to fight with great ferocity 

when a resource of exceptional value is at stake. Resources are rarely worth the 

risk of sustaining injury, and competing individuals will do best by resolving 

conflicts with ritualized displays only. Skill in assessing the relative strength of an 

opponent is key for navigating the demands, risks, and opportunities of social 

living. The review by van Staaden and colleagues (Chapter 3) discusses a 

prominent role for signaling aggressive behaviors, which permit individuals to 

obtain valid estimates of an opponent’s true strength. Once an animal is bested 

by an opponent, it is always better to adopt submissive behavior and accept 

subordinate status, rather than risk something far worse. A wide range of attributes 

decides between victory and defeat. With prominent asymmetries in the 

size of weapons, strength, or agility, fights are often quickly resolved. In many 

instances, though, social success will depend also on an ability to form successful


alliances, to harness cognitive skills, or to inherit status from high-ranking kin. A 

paired dominance relationship is established when prior encounters produce a 

lasting polarity in the outcome of future bouts. In its most common form, the past 

loser will be less likely to initiate further bouts against the winner or will retreat 

quickly if confronted. As individuals repeatedly meet and interact with others, 

higher order social organization emerges through a series of sequential dyadic 

interactions. Individuals of many species, including humans, tend to arrange 

themselves in largely linear social hierarchies. Although individual characteristics 

such as size, strength, or agility are relatively fixed and may indeed 

influence rank, Chase and Seitz (Chapter 4) illustrate that these qualities are 

more often overshadowed by contextual factors and chance events. 

The search for proximate mechanisms underlying aggression requires us 

to view aggression’s natural building blocks, to recognize the various factors that 

control them, and to effectively label their behavioral expression in the form of 

consistent and reliable phenotypes. Our understanding of the biological basis of 

aggression in all vertebrates, including humans, has been built largely upon 

discoveries first made in birds. An extensive literature indicates that hormonal 

mechanisms are shared between humans and many avian species. This recent 

development of hormonal, neuroendocrine, and genetic tools has established 

songbirds as powerful models for understanding the neural basis and evolution of 

vertebrate aggression. Maney and Goodson (Chapter 5) discuss the contributions 

of field endocrinology toward a theoretical framework linking aggression with sex 

steroids, explore evidence that the neural substrates of aggression are conserved 

across vertebrate species, and describe a promising new songbird model for 

studying the molecular genetic mechanisms underlying aggression. Voles have 

recently emerged as a key model for a genetic dissection of social behavior and its 

underlying neural mechanisms. Gobrogge and Wang (Chapter 6) discuss its 

utility for the study of aggression and review recent findings that illustrate the 

neurochemical mechanisms underlying pair bonding-induced aggression. Endogenous 

brain chemicals play a key role in the control of aggression in many taxa 

including humans. Neurotransmitters effectively pattern and modulate the expression 

of basic behavioral components. Genetic abnormalities in a number of 

neurotransmitter pathways have been implicated in aggression-related disorders. 

Yanowitch and Coccaro (Chapter 7) review work that demonstrates that neurotransmitter 

function is intricately linked to aggressive state. 

Subsequent chapters focus on human aggression, with an emphasis on 

genetic and other biological factors. Human ingenuity for inflicting intentional 

harm is without equal, although warring tendencies may already be rooted in a 

deep, prehuman past. Instances of violence have been documented for a range of 

nonhuman apes and may have arguably wired into our genes when our more 

aggressive ancestors won against our less aggressive ancestors in terms of survival 

and reproduction. Aside from an unprecedented potential for carnage and

1. Aggression 5 

destruction, humans are at the same time also capable of the most remarkable 

instances of compassion, understanding, and peaceful negotiation. The direction 

depends on each individual’s ethical codes and moral norms driven by the 

societal expectations, good parenting, or social contexts. A clear vision has 

emerged where “natural” tendencies for aggression appear to be ubiquitous, but 

so too are a plethora of sophisticated mechanisms that keep conflicts in check, 

channel aggression, negotiate fighting signals, resolve conflicts, and ultimately 

govern social group structure. 

Tuvblad and Baker (Chapter 8) demonstrate that genetic influences 

serve as powerful predictors of human aggression and violence. The relative 

influence of genetics depends upon developmental age, type of aggression, and 

the environmental context faced by the individual. LaPrairie and colleagues 

(Chapter 9) review research linking perinatal factors and aggression and conclude 

in a similar fashion that perinatal and neurodevelopmental factors 

influence the expression of aggressive behaviors. Nordstrom and colleagues 

(Chapter 10) further detail the importance of recognizing the role of brain 

functioning deficits in the risk for aggressive outcomes. Recent advances in 

imaging technology have enabled a far greater understanding of these influences 

on human behavior and the risks of criminal outcomes. Importantly, the chapters 

on human aggression also emphasize the fact that biology is not destiny and that, 

in the case of human aggression and violence, there is much that can and should 

be done in terms of early intervention and prevention. 

The list of significant challenges in aggression research remains daunting 

and the need to harness the full power of interdisciplinary approaches now 

appears more urgent than ever. Aside from our need to reconcile simple questions 

over terminology, a number of more serious impediments remain to be 

acknowledged. Concepts seem so intimately connected that we are tempted to 

view them as essentially overlapping, or to even use them synonymously (e.g., 

measures of an inherent tendency to fight, effectiveness in a contest, or the 

ability to socially dominate others). A common fallacy views these simply as 

separate perspectives onto the same, unitary phenomenon of aggression. For a 

synthesis to emerge we must accept aggression’s multidimensional nature and 

recognize that the term “aggression” simply serves as an overarching label for an 

entangled complex of multiple, distinct components, causes, and functions. This 

volume comes at a critical juncture for defining a broader view of aggression and 

with it we hope to help define the structural elements that comprise the behavior 

in its full complexity. 

The time is now right to bridge theoretical frameworks, combine 

experimental approaches, and relate significant findings across the many individual 

disciplines that are instrumental in the analysis of aggression. Center 

initiatives can serve as intellectual hubs for the comprehensive study of social 

conflict, violence, and related phenomena. Bringing together individual


researchers from a broad range of disciplines to foster integrative and overarching 

themes, such centers provide a forum for a rich exchange of ideas, the 

development of human resources, a clearinghouse for notable discoveries, and 

to publicize their societal relevance through public outreach. The development 

of viewpoints spanning formerly separate disciplines, such as the one aimed for 

in this book, is cause for optimism that the future is not quite as far off as we 

had feared.

2 

Evolutionary Aspects of 

Aggression: The Importance of 

Sexual Selection 

Patrik Lindenfors* ,† and Birgitta S. Tullberg* 

*Department of Zoology, Stockholm University, Stockholm, Sweden 

† Centre for the Study of Cultural Evolution, Stockholm University, Stockholm, 

Sweden 

I. Introduction 

II. Sexual Selection 

III. Mating Systems 

IV. When to Fight and When to Flee 

V. Case Studies: Sexual Dimorphism 

VI. Humans and the Mammalian Pattern 

Acknowledgment 

References 

ABSTRACT 

Aggressive behaviors in animals, for example, threat, attack, and defense, are 

commonly related to competition over resources, competition over mating 

opportunities, or fights for survival. In this chapter, we focus on aggressive 

competition over mating opportunities, since this competition explains much 

of the distribution of weaponry and large body size, but also because this type of 

competition sheds light on the sex skew in the use of violence in mammals, 

including humans. Darwin (1871) termed this type of natural selection, where 

differences in reproductive success are caused by competition over mates, sexual 

selection. Not all species have a pronounced competition over mates, however. 

Instead, this aspect of sociality is ultimately determined by ecological factors. 



DOI: 10.1016/B978-0-12-380858-5.00009-5

8 Lindenfors and Tullberg 

In species where competition over mates is rampant, this has evolutionary effects 

on weaponry and body size such that males commonly bear more vicious weapons 

and are larger than females. A review of sexual selection in mammals reveals how 

common aggressive competition over mating opportunities is in this group. 

Nearly half of all mammal species exhibit male-biased sexual size dimorphism, 

a pattern that is clearly linked to sexual selection. Sexual selection is also 

common in primates, where it has left clear historical imprints in body mass 

differences, in weaponry differences (canines), and also in brain structure differences. 

However, when comparing humans to our closest living primate relatives, 

it is clear that the degree of male sexual competition has decreased in the 

hominid lineage. Nevertheless, our species displays dimorphism, polygyny, and 

sex-specific use of violence typical of a sexually selected mammal. Understanding 

the biological background of aggressive behaviors is fundamental to understanding 

human aggression. ß 2011, Elsevier Inc. 

I. INTRODUCTION 

Why does aggression exist in nature Darwin (1859, 1871) pointed out that the 

ultimate explanation for any trait has to be found in the effect that it has on 

survival and reproduction. From an evolutionary standpoint, individuals should 

thus mainly be expected to fight over resources, for survival and for mating 

opportunities, because these are what mainly affect how many genes that individual 

contributes to the gene pool of the coming generation. Another prediction 

is that the amount of aggression displayed in the encounters should increase 

with increasing value of the fought-over resource. Aggressive behaviors are 

associated with costs, and individuals are simply expected to take higher risks, 

that is, pay potentially higher costs, with increasing potential gains. In this 

chapter, we focus on aggression over mating opportunities—sexual selection— 

in mammals in general and in primates in particular. We focus on sexual selection 

because evidence suggests that it is the primary reason why animals fight with 

conspecifics and because it is the most likely explanation of some aspects of 

human aggression, such as why males tend to be more aggressive than females. 

An important point about evolutionary explanations is the philosophical 

distinction between proximate and ultimate explanations. Take sex, for 

example. Do humans have sex because it feels good or in order to have children 

Most sexual intercourse in current society probably has very little to do with 

actual procreation; on the contrary, there are many birth control methods 

available to make it possible to have sex without this resulting in a pregnancy. 

Despite the fact that protected sex happens “because” it feels good, the evolutionary 

explanation of sexual intercourse is “because” of procreation. This is 

where the crucial distinction between proximate and ultimate explanations

2. Evolutionary Aspects of Aggression: The Importance of Sexual Selection 9 

comes into play. A proximate explanation is the explanation that is closest to the 

event that is to be explained. The higher, ultimate explanation is instead the 

deeper reason for why something happened. 

In biology, the division in ultimate and proximate explanations has 

been extended to what is usually termed “Tinbergen’s four questions” 

(Tinbergen, 1963); the four potential explanations of any behavior: (1) survival 

value or adaptive function, (2) phylogenetic history, (3) individual development, 

and (4) causal mechanisms such as hormonal mediation of behavior. The 

first two of Tinbergen’s questions are ultimate whereas the latter two are proximate. 

To fully shed light on a biological phenomenon all four types of questions 

are needed and the answers complement each other. However, in this chapter, 

we focus entirely on ultimate, evolutionary answers to the question of why 

aggression exists and takes the form it does. 

II. SEXUAL SELECTION 

Natural selection is all about who gets to reproduce and who does not (Darwin, 

1859). A central aspect of getting to reproduce is to survive until the opportunity to 

reproduce arises and to gain access to resources enabling you to do so, but another 

important aspect concerns direct competition in connection with the reproductive 

act itself. Darwin termed this second aspect “sexual selection”: differences in 

reproductive success caused by competition over mates (Darwin, 1871). 

Why did Darwin give a specific name to one part of natural selection: 

why not just stick to the umbrella term “natural selection” Darwin had noted 

that there often seems to be a conflict of interest between traits that increase 

survival and traits that increase reproduction; many traits that give an advantage 

in reproduction have negative consequences for survival. A male peacock’s large 

tail feathers are a prime example of such a trait. How can such a long colorful tail 

evolve when it makes the bearer simultaneously more visible and less adept at 

escaping predators When thinking about this problem before having formulated 

the theory of sexual selection, Darwin wrote in a letter to his friend, the botanist 

Asa Gray, the famous line: “The sight of a feather in a peacock’s tail, whenever 

I gaze at it, makes me sick!” (Darwin, 1860). 

To clarify this second aspect of natural selection—selection that has to 

do with competition over mates—Darwin wrote a follow-up to “On the Origin of 

Species” (1859), “The Descent of Man and Selection in Relation to Sex” (1871). 

In this book, Darwin points out that there are two potential kinds of competition 

over mates, two forms of sexual selection. Either individuals of one sex (usually 

males) can fight with each other over mating opportunities (intrasexual selection) 

or, alternatively, individuals of one sex (usually females) can choose 

individuals of the other sex on the basis of some trait (intersexual selection).


This second form of sexual selection is the explanation of the peacock’s tail: 

peahens simply find it attractive and prefer to mate with the peacocks with the 

most elaborate tail. Further, the tail provides information on the genetic quality 

of the male—it is an honest signal (Petrie, 1994). 

It is noteworthy that it was the idea of intersexual selection that caused 

the most furious debate in Darwin’s time, foremost because it was judged utterly 

questionable that female aesthetical judgment could be the ultimate explanation 

for so many conspicuous characters in nature. However, partner choice is a more 

peaceful process than direct competition within a sex. Thus, because it induces 

so much aggression in nature, we focus in this chapter mainly on intrasexual 

selection; physical competition over mating opportunities. It should be pointed 

out that the two forms of sexual selection sometimes occur simultaneously, for 

instance, in lekking species where females choose as mating partners the winning 

males from physical competition (Andersson, 1994). 

Sexual selection arises when one sex limits the reproductive success of 

the other. Most often it is females who are the limiting resource for the reproductive 

success of males due to a fundamental asymmetry between males and 

females in their defining characteristic, their gametes. Males are designated by 

their smaller, mobile gametes, called sperm cells. Females are designated by their 

larger, nutrition-carrying gametes, called eggs. Males can make more gametes 

than females, simply because sperm are energetically cheaper to make than eggs; 

thus, there is a fundamental reproductive difference between males and females. 

This initial asymmetry has consequences. Making sperm is cheap and easy, so 

this is not what limits the reproductive possibilities of males. Making eggs, on the 

other hand, is much costlier. Thus, sexual selection commonly—but not exclusively—affects 

males, because given an equal sex ratio, male reproductive success 

is limited by access to matings with females. Conversely, female reproductive 

success is limited by the number of eggs she can produce (Andersson, 1994). This 

sex specificity is so common that the reverse pattern, termed sex role reversal, is 

subject to intense interest from evolutionary biologists when it occurs (e.g., Ralls, 

1976; Vincent et al., 1992). 

An important experimental verification of this theoretical insight was 

made by the geneticist Bateman (1948), who experimented on fruit flies. Bateman 

noted a pattern demonstrating that the number of offspring a male fruit fly 

can have is directly correlated with his number of matings. The same does not 

hold true for females, who have roughly the same number of offspring no matter 

how many times they mate (as long as it is at least once). This pattern is termed 

Bateman’s principle. Later studies, however, have documented that a number of 

exceptions to Bateman’s principle exist in nature (Birkhead, 2001). Individuals 

are not only sperm and eggs; there are a number of additional factors that need to 

be incorporated to understand what is going on in different species. In mammals, 

especially, one needs to incorporate two unique adaptations. While the energy


investments in the mammal zygotes differ only marginally in relation to the body 

mass of most mammals, the cost to mammal females greatly exceeds that to males 

due to effects of pregnancy and lactation. This energy investment inequality has 

existed since the origin of the class Mammalia, 125 million years ago. 

There are some exceptions to the general mammalian pattern, however. 

For instance, some mammal babies are so expensive to bring up to maturation that 

both sexes have to partake in the upbringing for it to be possible. In these species, 

where males and females work together to guard and rear the young, intrasexual 

competition occurs just prior to pair formation. In these species, the two sexes are 

usually morphologically alike. In other mammal species, however, competition 

between males over mating opportunities is fierce. In some species this affects the 

entire social life of the species, in that males physically exclude other males from 

the group. The result is a social system akin to a harem structure, with immature 

males roaming outside the social gathering or forming bachelor groups. 

The importance of sexual selection in understanding aggression in 

mammals is most clearly illustrated by the presence and absence of weaponry. 

For example, male ungulates are commonly equipped with horns while females 

are not. Horns would be a good weapon to fend off predators, especially when you 

need to defend your young, or to fight off conspecific competitors. But most 

young are cared for by single mothers; the fathers—who have the weapons—are 

absent. Ungulate horns are commonly ready just in time for rutting season and 

are then shed (e.g., deer). Instead of predator defense, male ungulates mainly use 

their horns to fight each other (Caro et al., 2003; Stankowich and Caro, 2009). 

A similar case can be made for the large, sharp canines of primates (Thorén et al., 

2006), and large body size in male mammals in general (Lindenfors et al., 2007a). 

Such sex-skewed distribution of size and weaponry, in combination with observations 

of fierce aggression, is what enables us to assert that most serious conflict and 

aggression in mammals is over mating opportunities. 

Sexual selection acting primarily on one sex may have indirect but 

pronounced consequences for the relationship between the sexes. Thus, direct 

conflicts between males sometimes result in conflicts of interest between males 

and females. Early thoughts on this issue (Parker, 1979, Trivers, 1972; Williams, 

1966) have received much empirical support (Arnqvist and Rowe, 2005), and it 

now almost seems the norm rather than an exception that there exists such a 

conflict and that this becomes more severe under strong intrasexual competition. 

This can lead to the interesting phenomena of sexually antagonistic coevolution 

where males and females become involved in an arms race, as traits in one sex 

entice the evolution of resistance in the other (Holland and Rice, 1998; 

Gavrilets et al., 2001; and others). On the other hand, intrasexual competition 

can lead to one sex dominating the other. With regard to aggression and physical 

prowess, the common situation in mammals, including primates (Hrdy, 1981), is 

that males are physically dominant over females.


III. MATING SYSTEMS 

Not all animals have clear sexual differences (Fairbairn et al., 2007). In birds, for 

example, many species of gulls and penguins are so alike that it is impossible to 

determine the sex except by closer inspections of the genitals. At the other 

extreme are mallards, where the sexes are so different that Linnaeus classified 

them as two different species (Andersson, 1994). In mammals, we find the same 

variation even within a given mammalian order. Thus, within Pinnipedia we 

have, on the one hand, elephant seals where males may weigh up to five times as 

much as females and on the other hand, species such as Baikal seals where 

females are of similar weight as males (Lindenfors et al., 2002). These differences 

in dimorphism are due to differences in the degree of sexual selection. But why 

are there differences in the degree of sexual selection between species to start 

with 

Fundamentally, this question is about factors affecting male and female 

social group size. These issues are commonly addressed by focusing on the 

ecological variables that determine the spatiotemporal distribution of females, 

based on the expectation that resources and predation account for variation in 

female reproductive success. By comparison, access to females is generally assumed 

to be the major factor influencing male reproductive success (Emlen and 

Oring, 1977; Trivers, 1972; Wilson, 1975). After risks and resources have 

determined the spatiotemporal distribution of females, the distribution of 

females is in turn expected to influence the degree of male intrasexual competition 

(Emlen and Oring, 1977). For instance, a group of concurrently fertile 

females opens the field for male competition and monopolization. The general 

framework is therefore that social evolution is driven by females. 

The theoretical expectation that social evolution is ultimately driven by 

female distribution is empirically supported by comparative studies on primates, a 

group for which there is a significant correlation between evolution of male and 

female sociality (e.g., Altmann, 1990; Mitani et al., 1996; Nunn, 1999). Further, a 

phylogenetic investigation has shown that the evolution of female group size 

precedes the evolution of male group size, that is, that evolutionary changes in 

male group size lag changes in female group size (Lindenfors et al., 2004). 

Ecological factors determine whether it is possible for a male to monopolize 

several mating opportunities. For example, elephant seal females give birth 

on beaches. With a limited number of suitable beaches available in the elephant 

seal range, females tend to crowd together when giving birth. Elephant seals 

mate soon after they have given birth, so at the time of mating females are 

gathered tightly on limited stretches of beach. Males can exclude other males 

from a stretch of beach and thereby secure matings with a large number of 

females. Successful males in this competition gain all matings, while the losers 

get none. Fighting among elephant seals over mating opportunities is thus a


fierce and bloody affair, a scenario which has resulted in extreme size dimorphism. 

In other pinniped species, females give birth in isolated caves on the polar 

ice pack; thus, no opportunity exists to monopolize matings. Without evolutionary 

pressure for male fighting ability, the sexes are more equal in size (Lindenfors 

et al., 2002). 

In conclusion, the ultimate cause for differences in mating systems can 

be traced back to ecological circumstances. The differences in mating systems in 

turn trigger differences in aggressive competition for mating opportunities which 

is what drives the evolution of sex differences in size and weaponry. These 

morphological sex differences are clear indicators of the severity of male–male 

aggression. 

IV. WHEN TO FIGHT AND WHEN TO FLEE 

Given that fighting is most often about mating opportunities, how are they 

predicted to pan out in terms of ferocity, number of behaviors involved, length 

of time, and so on There are two things that determine the ferocity of fighting: 

the value of the object being fought over and the risks involved. The problem 

can be reduced to a cost-benefit analysis. A male can not give up at first instance 

to maximize his chances of survival, because that would result in total nonreproduction. 

Neither can he go “all-in” in just any aggressive encounter if there 

exists only a minute chance of success. Instead, males in competitive situations 

have to weigh the probabilities of success, injury, and survival against each other, 

while considering other factors such as energy expenditures and probabilities of 

success in future interactions with other competitors. It is important to note that 

animals make calculations and decisions about how to act, but such processes do 

not necessarily require the consciousness about the process usually ascribed to 

human decision-making. Rather, animals are believed to use cues with regard 

to the environment, as well as their own and the opponent’s current status, and 

to use this information in an unconscious way when making decisions. 

One consequence this accounting has had over evolutionary history is 

that competitive interactions often take the form of a “sequential assessment 

game”. Simply put, this prescribes that each competitor should attempt to assess 

his opponent’s strength using as little energy as possible. Escalation should only 

be initiated by the competitor that feels he has the upper hand, or by either 

opponent if they cannot determine who is superior (Enquist and Leimar, 1983). 

Thus, a meeting between two deer males often starts out with a stage of roaring, 

which acts as a forcedly honest signal of body size. If this does not settle who is 

the larger/stronger, it is followed by “parallel walking,” where each competitor 

tries to judge the size and strength of the other by walking back and forth in 

parallel. Only if it is still unclear who is the larger or stronger will the


Fight (8) 

Approach 

(50) 

Roar 

contest 

(33) 

No roar 

contest 

(17) 

Parallel 

walk 

(17) 

One stag 

withdraws 

(16) 

Parallel 

walk 

(7) 

One stag 

withdraws 

(9) 

Fight (5) 

One stag 

withdraws 

(2) 

No 

parallel 

walk 

(10) 

Fight (1) 

One stag 

withdraws 

(9) 

Figure 2.1. Sequential assessment in red deer (from Clutton-Brock and Albon, 1979). 

competition escalate to actual fighting (Clutton-Brock and Albon, 1979; 

Fig. 2.1). Thanks to this “game,” really fierce fights only happen between 

opponents of equal size—inferior competitors flee quickly to fight another day 

(and another opponent). 

There is a common interest among fighters in trying to expend as little 

energy as possible while simultaneously minimizing the possibility of injury. For 

example, wolves and other canids ritualistically greet each other several times 

each day and display dominance or submission on a regular basis—they do not 

determine their relationship at every encounter. Some cichlid fish have a system 

akin to that of red deer, with different stages of escalation (Brick, 1999). Male 

lions fight savagely only if they stand a good chance of winning a pride of females. 

Research shows that they determine the quality of their rivals on cues from each 

other’s manes (West and Packer, 2002). Lekking birds such as black grouse have 

distinctive courtship rituals where they make calls and visual displays, an odd 

mix of strength comparison and showing off, where females can pick winners 

according to some criterion, sometimes just by copying other females’ choices 

(Andersson, 1994; Dugatkin and Godin, 1993; Wade and Pruett-Jones, 1990). 

Seldom do fights turn into vicious fighting, and when they do it is usually because 

either the contestants are judged by each other to be of equal strength, or because


the benefit of winning—the value of the contested item—is much larger than the 

cost of losing. If the choice is reproduction or death, fights become deadly. This is 

why fights among elephant seals are so fierce and bloody. The chance to mate 

occurs only once per year and most males never even get close. For the successful 

males it is another story—in a study of Southern elephant seals, harem holders 

accounted for 89.6% of the recorded paternities (Fabiani et al., 2004; Fig. 2.2). 

The sequential assessment game is a variant of a game theoretical setup 

termed the “hawk-dove game” (see also Chapter 3). In this game, there are two 

possible strategies: always fight (“hawk”) and always yield (“dove”), where it is 

assumed that the two competitors have equal fighting ability. An Evolutionarily 

Number of males Number of males 

12 

8 

4 

0 

12 

8 

4 

RUB96 

SF96 

SF97 

0 1 2 7 0 1 12 1 24 

SI196 SI296 SI297 

0 

0 1 24 0 1 2 8 21 0 

12 

1 2 8 32 

Number of males 

8 

4 

SM96 

HH 

NHH 

0 

0 2 12 

Number of paternities 

Figure 2.2. Number of paternities achieved by the harem holder (HH) and the other males (NHM) 

associated with each harem in seven different populations of Southern elephant seals 

(from Fabiani et al., 2004).


Stable Strategy is a strategy which, if adopted by a population of players, cannot 

be invaded by any alternative strategy. It has been shown that the ESS is a mix of 

hawks and doves with proportions determined by the cost of fighting in relation 

to the benefit of winning (Maynard Smith, 1982). This game provides theoretical 

information that in a population of nonfighters it is profitable to be a fighter, 

and vice versa. If one extends the game to include a strategy called “assessor” that 

determines whether it will act as a “hawk” or a “dove” based on some criterion— 

for example, depending on priority at the resource—one can arrive at the 

sequential assessment game. The assessment strategy is also an ESS (Maynard 

Smith, 1982). 

The prediction from these game theoretical models is that populations 

where individuals compete over resources or matings should consist of individuals 

utilizing different strategies depending on situation, where important 

factors are the current size and physical state of self and opponents and the 

value of resources (for instance, the number of females in the group being fought 

over). In this context, it should be noted that some animal populations have 

evolved alternatives to fighting strategies, usually known as sneaker strategies. 

Such males are usually much smaller than fighting males and can covertly sneak 

matings from females while the fighters are occupied with physical combat 

(Gross, 1996). 

V. CASE STUDIES: SEXUAL DIMORPHISM 

As mentioned above, animal groups differ in both the way and the degree to 

which they are exposed to sexual selection, and this will have great effects on the 

evolution of sex differences (Fairbairn et al., 2007). Although mammals as a 

group are characterized by a high degree of intrasexual selection (as compared 

with, for instance, birds, where intersexual selection seems to be more common), 

there is variation in the strength of sexual selection both within and among 

mammalian orders. An example of this variation is the pinnipeds (seals, sea lions, 

and walruses) where there exists a clear relationship between harem size and 

sexual size dimorphism (Lindenfors et al., 2002; Fig. 2.3). 

In this section, we bring up some studies that have compared different 

mammalian groups with respect to the consequences of sexual selection on 

behavioral and morphological evolution. There are 4629 extant or recently 

extinct mammalian species, as listed by Wilson and Reeder (1993). In a survey 

of 1370 of these, Lindenfors et al. (2007a) showed that sexual selection is a 

prevalent selective force in mammals. With a cutoff point at a 10% size difference 

in either direction to “count” as sexual dimorphism, mammals were, on 

average, male-biased size dimorphic (average male/female mass ratio ¼ 1.184; 

paired t-test p0.001; Table 2.1) with males being larger than females in 45% of


0.8 

log(male/female weight) contrasts 

-1.5 

0.4 

0.0 

-1.0 -0.5 0.0 0.5 1.0 1.5 

-0.4 

-0.8 

log(harem size) contrasts 

Figure 2.3. Regression line through the origin on harem size and body weight dimorphism. The data 

points are from a phylogenetic independent contrasts analysis. There is a significant 

relationship between harem size and sexual size dimorphism (b¼0.376, p¼0.000, 

R 2 ¼0.577, n¼36) (from Lindenfors et al., 2002). 

extant species (Table 2.1). Systematists recognize 26 monophyletic mammalian 

orders (Wilson and Reeder (1993)). When investigating each order separately, 

the majority of orders also turned out to be significantly male-biased dimorphic 

(average male/female mass ratio >1.0 and p


Table 2.1. Summary of the Patterns of Dimorphism Found in Mammals 

Order 

Number of 

recognized 

species 

Number of 

species with 

body mass data 

Average 

dimorphism 

Sexual size 

dimorphism 

Mammalia 

All mammals 4629 1370 1.184 p 0.001 

Subclass Prototheria 

Monotremata (Monotremes) 3 2 1.273 – 

Subclass Metatheria 

Didelphimorphia (American 

63 13 1.323 p ¼ 0.002 

marsupials) 

Paucituberculata (Shrew oppossums) 5 2 1.840 – 

Microbiotheria (Monito del monte) 1 1 1.044 – 

Dasyuromorphia (Dasyuroids) 63 24 1.465 p 0.001 

Peramelemorphia (Bandicoots 

21 9 1.496 p ¼ 0.015 

and bilbies) 

Notoryctemorphia (Marsupial moles) 2 0 – – 

Diprotodontia (Kangaroos, etc.) 117 63 1.306 p 0.001 

Subclass Eutheria 

Insectivora (Insectivores) 428 59 1.048 p ¼ 0.081 

Macroscelidea (Elephant shrews) 15 5 0.964 p ¼ 0.142 

Scandentia (Tree shrews) 19 1 – – 

Dermoptera (Colugos) 2 0 – – 

Chiroptera (Bats) 925 354 0.999 p ¼ 0.091 

Primates (Primates) 233 198 1.247 p 0.001 

Xenarthra (sloths, armadillos, 

29 4 0.914 p ¼ 0.216 

and anteaters) 

Pholidota (Pangolins) 7 3 1.767 p ¼ 0.001 

Lagomorpha (Rabbits and pikas) 80 21 0.930 p ¼ 0.012 

Rodentia (Rodents) 2015 295 1.092 p 0.001 

Cetacea (Whales, dolphins, and 78 10 1.414 p ¼ 0.082 

porpoises) 

Carnivora (Carnivores) 271 180 1.476 p 0.001 

Tubulidentata (Aardwark) 1 0 – – 

Proboscidea (Elephants) 2 2 1.900 – 

Hyracoidea (Hyraxes) 6 1 1.111 – 

Sirenia (Dugongs and manatees) 5 0 – – 

Perissodactyla (Horses, rhinos, 

18 8 1.164 p ¼ 0.156 

and tapirs) 

Artiodactyla (Antelopes, 

camels, pigs, etc.) 

220 115 1.340 p 0.001 

Dimorphism is given as male mass/female mass. Mammals and the majority of mammalian orders 

are on average male-biased dimorphic (average dimorphism>1.0 and p0.05) or female-biased dimorphism (Lagomorpha: 

average dimorphism


“more” and “less” sexually selected (polygynous) sister taxa. These tests 

revealed that a higher degree of sexual selection was associated with a higher 

degree of male-biased dimorphism. More polygynous taxa not only had larger 

males but also larger females than their less polygynous sister taxa. These results 

indicate that sexual selection is a significant explanatory factor of both sexual 

dimorphism as such, and of the general size increase in many mammalian 

lineages. 

In primates, the mammal order humans belong to, the pattern is similar. 

Again using mating system as a three-state unordered categorical variable, 

testing for differences in dimorphism between “more” and “less” sexually selected 

sister taxa, a higher degree of sexual selection was associated with a higher degree 

of male-biased dimorphism. Again, more polygynous taxa also had larger males 

and females than their less polygynous sister taxa (Lindenfors, 2002; Lindenfors 

and Tullberg, 1998). Here, however, a novel method investigating temporal 

order of events revealed not only a correlation but also a causal link between 

sexual selection and sexual size dimorphism where changes in mating systems 

occurred before changes in the degree of sexual selection (Lindenfors and 

Tullberg, 1998). Using similar methods, sexual selection has also been shown 

to be an important determinant of sexual dimorphism in canine size in primates 

(Thorén et al., 2006), although primate canines are also of importance in 

predator defense (Harvey et al., 1978). Thus, both body size and canine size 

bear witness to an evolutionary history of male–male aggression in primates. 

This selection history has its grounds in a sexual difference in behavior. 

While males compete more over matings than females, female reproduction is 

instead limited by resource allocation (Emlen and Oring, 1977). These differing 

demands should be expected to produce variation in the relative sizes of various 

brain structures, just as they are expected to produce differences in other morphological 

structures. However, data on brain structures in primates are not 

available for males and females separately. Instead, investigating species differences 

in brain structures and comparing them on basis of differences in the 

species-typical degree of sexual selection, research has shown that the degree 

of male intrasexual selection is positively correlated with several structures 

involved in autonomic functions and sensory-motor skills, and in pathways 

relating to aggression and aggression control (Lindenfors et al., 2007b). 

The sizes of the mesencephalon, diencephalon (containing the hypothalamus), 

and amygdala, all involved in governing aggressive behaviors, are 

positively correlated with the degree of sexual selection, whereas the size of the 

septum, which has a role in facilitating aggression control, is negatively correlated 

with the degree of sexual selection. These correlations indicate that sexual 

selection affects physical combat skills. Moreover, male group size was positively 

correlated with the relative volume of the diencephalon and negatively 

correlated with relative septum size, further strengthening the conclusion that


aggression is an evolutionarily important component of male–male interactions 

(Lindenfors et al., 2007b). Thus, primate brain organization also reflects a history 

of male–male aggression. 

VI. HUMANS AND THE MAMMALIAN PATTERN 

So where do humans fit into this picture Humans are one of the sexually sizedimorphic 

species in the primate order in Table 2.1. But compared to our closest 

relatives (chimpanzees, bonobos, gorillas, and orangutans) humans have the 

lowest degree of size dimorphism (Lindenfors, 2002), indicating a decreasing 

degree of sexual selection over human evolution. Nevertheless, in all measurements 

of length that have ever been carried out in human populations, males 

have been taller than females. The average dimorphism in humans from these 

surveys is 1.07 (Gustafsson and Lindenfors, 2004). Does this mean that we 

exhibit a tendency toward the polygyny that accompanies such size dimorphism 

According to the Ethnographic Atlas Codebook (Gray, 1999), a database 

of cultural characteristics for 1231 comparable cultures from around the 

world, polygyny is common in 48% of human societies. In another 37% polygyny 

is allowed, and in only 15% is monogamy the norm. Only four reported societies 

are considered polyandrous. From these data and the degree of human size 

dimorphism, one may draw the conclusion that humans are at least more 

polygynous than monogamous (see also Low, 2000), and also that Western 

cultures fall within the monogamous 15% of the world. Interestingly, intergroup 

differences in size dimorphism are not correlated with differences in the degree of 

polygyny (Gustafsson and Lindenfors, 2004), a clear indication that cultural 

evolution proceeds faster than biological evolution. 

There are more indications that humans have an evolutionary history of 

sex differences as an explanatory factor in human aggression. For example, men 

commit most of the world’s violent acts that are reported to the police. Men are 

consequently overrepresented in the world’s prisons. Women typically make up 

only 10–15% of the prison population (Harrendorf et al., 2010). Further, 

soldiering is most often an all-male vocation (personal observation). Humans 

are, however, the products of both biological and cultural inheritance (Boyd and 

Richerson, 2005). Here, we have presented only the biological side of the story, 

but we agree with Archer (2009) that sexual selection probably is the best 

explanation for the magnitude and nature of human sex differences in aggression. 

Humans fit into the mammalian scheme of things very well. 

Acknowledgment 

This research was supported through a generous research grant from the Swedish Research Council 

(P. L.).

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3 

Signaling Aggression 

Moira J. van Staaden,* William A. Searcy, † 

and Roger T. Hanlon ‡ 

*Department of Biological Sciences and JP Scott Center for Neuroscience, 

Mind & Behavior, Bowling Green State University, Bowling Green, Ohio, 

USA 

† Department of Biology, University of Miami, Coral Gables, Florida, USA 

‡ Marine Resources Center, Marine Biological Laboratory, Woods Hole, 

Massachusetts, USA 


A. An ethological approach to aggression 

B. The classic game theory model 

C. Signaling games 

D. Threat displays and why they are part of aggression 

E. Evolutionary issues 

F. The challenge of “incomplete honesty” 

G. Case studies in aggressive signaling 

II. Bird Song Signals Aggressive Intentions: Speak Softly and 

Carry a Big Stick 

III. Visual Displays Signal Aggressive Intent in Cephalopods: 

The Sweet Smell of Success 

A. Cuttlefish agonistic bouts 

B. Squid agonistic bouts 

C. From molecules to aggression: Contact pheromone triggers 

strong aggression in squid 

D. Signaling aggression in humans 

Acknowledgments 

References 



DOI: 10.1016/B978-0-12-380858-5.00008-3

24 van Staaden et al. 

ABSTRACT 

From psychological and sociological standpoints, aggression is regarded as intentional 

behavior aimed at inflicting pain and manifested by hostility and attacking 

behaviors. In contrast, biologists define aggression as behavior associated with 

attack or escalation toward attack, omitting any stipulation about intentions and 

goals. Certain animal signals are strongly associated with escalation toward 

attack and have the same function as physical attack in intimidating opponents 

and winning contests, and ethologists therefore consider them an integral part of 

aggressive behavior. Aggressive signals have been molded by evolution to make 

them ever more effective in mediating interactions between the contestants. 

Early theoretical analyses of aggressive signaling suggested that signals could 

never be honest about fighting ability or aggressive intentions because weak 

individuals would exaggerate such signals whenever they were effective in 

influencing the behavior of opponents. More recent game theory models, however, 

demonstrate that given the right costs and constraints, aggressive signals 

are both reliable about strength and intentions and effective in influencing 

contest outcomes. Here, we review the role of signaling in lieu of physical 

violence, considering threat displays from an ethological perspective as an 

adaptive outcome of evolutionary selection pressures. Fighting prowess is conveyed 

by performance signals whose production is constrained by physical ability 

and thus limited to just some individuals, whereas aggressive intent is encoded in 

strategic signals that all signalers are able to produce. We illustrate recent 

advances in the study of aggressive signaling with case studies of charismatic 

taxa that employ a range of sensory modalities, viz. visual and chemical signaling 

in cephalopod behavior, and indicators of aggressive intent in the territorial calls 

of songbirds. ß 2011, Elsevier Inc. 


Although physical fighting, including the killing of conspecifics, is widespread in 

nonhuman animals just as it is in humans, the majority of contests and disputes 

in nonhuman animals are settled without physical fighting. Rather than resorting 

to immediate physical combat, nonhuman animals often engage instead in 

extended bouts of signaling, making prominent display of their weapons (e.g., 

antlers, claws, and teeth), or running through a repertoire of highly stereotyped 

agonistic signals. With their high cognitive capacity, primates (humans 

included) are particularly good at reducing social tensions and resolving conflicts 

using agonistic signaling as opposed to sheer physical force (Cheney et al., 1986).

3. Signaling Aggression 25 

Such aggressive signaling is found in virtually all of the multicellular 

taxa and can involve all communication modalities. Orthoptera (Alexander, 

1961; Simmonds and Bailey, 1993) and many other insects (Clark and Moore, 

1995; Jonsson et al., 2011) use aggressive song to defend resources, and the use of 

territorial song in birds is well known (Searcy and Yasukawa, 1990; Stoddard 

et al., 1988). Calls are employed to similar effect in the dramatic displays of large 

mammals or frog choruses (Bee et al., 1999; Reby et al., 2005; Wagner, 1992), 

and more subtly by other vertebrate taxa such as fish (Raffinger and Ladich, 

2009). In these scenarios, signaling can be just as effective as physical attack in 

intimidating opponents and winning contested resources. 

Chemical signals are widely used to signal resource defense and fighting 

ability, deposited either as scent marks in fixed locales by terrestrial species (Page 

and Jaeger, 2004) or contained in urine released during aggressive interactions in 

some aquatic organisms (Breithaupt and Eger, 2002). Visual signals are perhaps 

the most familiar and easily appreciated of aggressive displays, beginning with 

Darwin’s (1871) graphic illustration of aggression and fear in the facial expression 

of the domestic dog. Visual signs of aggression include variable pigment 

patterns of many fish and cephalopods (DiMarco and Hanlon, 1997; Moretz and 

Morris, 2003), and the ritualized display of weapons (Huber and Kravitz, 1995; 

Lundrigan, 1996) or inedible objects as “props” (Murphy, 2008). 

Phylogenetic comparative analyses demonstrate that many of these 

aggressive signals allowing opponents to resolve contests without physical 

harm evolved from nonsignaling behaviors through the process of ritualization 

(Scott et al., 2010; Turner et al., 2007). Whereas agonistic behavior runs the 

gamut from passivity, defense, and escape to full conflict, here, we reserve the 

terms aggressive/threatening behavior for that subset of agonistic behavior associated 

with the escalation toward physical fighting (Searcy and Beecher, 2009). 

A. An ethological approach to aggression 

The ethological approach to aggression derives historically from the traditional 

instincts and drives articulated by Lorenz (1978). Although the simple psychohydraulic 

model of motivation underlying this view proved inadequate in the 

long term, the idea that aggression is based on both internal state and external 

stimuli, and the proposed value of a comparative evolutionary approach, were 

both far-sighted and enduring. The classic On Aggression (Lorenz, 1963) which 

was written for a popular audience, highlighted aggression as a natural, evolved 

function, with a founding basis in other instincts, and a central role in animal 

communication. A more nuanced view is found in his work known as the Russian 

manuscript (Lorenz, 1995). In this, Lorenz discussed animals and humans separately, 

not because of any fundamental difference in their biology, but because 

he believed it necessary for the reader to have an adequate frame of reference.


Much current research on the biology of aggression focuses on identifying 

the physiological substrate to violence (i.e., on proximate cause and nonadaptive 

features). The ethological or sociobiological approach, in contrast, 

focuses attention on the ultimate causes and adaptive forms of aggressive behavior 

(e.g., Chen et al., 2002; Huber and Kravitz, 1995; Miczek, et al., 2007; Natarajan 

et al., 2009): how and why has evolution molded complex agonistic interactions 

built on reciprocal displays of threat or submission, affect or intent 

B. The classic game theory model 

Evolutionary fitness is measured in terms of the number of offspring an individual 

produces over the course of its lifetime. In the evolutionary race to transmit their 

genes to the following generations at a higher frequency than that of their 

conspecifics, these individuals must compete for access to all the resources 

necessary to create and raise their progeny, including mates, dominance rights, 

and desirable territory. Winners in this intraspecific competition thus stand to 

gain both immediate personal advantages such as food, space, and safety, as well 

as long-term evolutionary fitness, that is, more offspring and therefore copies of 

their genes in subsequent generations. Simulation approaches from game theory 

have long provided a theoretical framework for analyzing and predicting the 

outcomes of competitive interactions. The classic “Hawks” and “Doves” game 

(Maynard Smith and Price, 1973) considers symmetrical contests between pairs 

of individuals who are equivalent in every respect (equal size, strength, fighting 

ability, etc.), differing only in behavioral/fighting strategy in intraspecific 

encounters. Hawk strategists are those who will always choose to fight when 

they encounter a conspecific at a contested resource. Dove strategists, in contrast, 

always retreat from an individual behaving as a Hawk, rather than engage them 

in combat. Hawks always best Doves, but they incur costs when they compete 

against other Hawks. The outcome between two Dove strategists is randomly 

determined. Each conflict consists of a series of agonistic moves (incorporating 

provocation, escalation, retaliation, etc.) with rewards or costs assigned to each 

contestant according to a particular payoff matrix (Table 3.1). 

Populations are expected to converge on an evolutionarily stable strategy 

(ESS), strategies that once they are predominant cannot be invaded by any 

other strategy. The ESS depends critically on the ratio of what an individual 

stands to gain over what it stands to lose in a fight. Thus, in the common 

situation where the cost of injury exceeds the benefits of winning, populations 

are expected to adjust to balanced proportions of the two strategies with the 

majority of individuals behaving as Doves, while a smaller number of Hawk 

strategists persists. Only in extreme situations where the value of a resource 

greatly exceeds the cost of injury, will a Hawk strategy be superior and can 

become so widespread as to completely replace the Dove strategy. For instance,


Table 3.1. The Payoff Matrix for the Hawk–Dove Game Shows the Consequences that Result When 

a Player of a Given Strategy (Left Column) Encounters Another Player’s Strategy 

Hawk 

Dove 

Hawk Tie [(V C)/2] Win [V] 

Dove Lose [0] Tie [V/2] 

Choices are assumed to be rational where each individual would prefer to win, prefer to tie rather 

than lose, and prefer to lose over receiving injury. In this payoff matrix, V (value of the contested 

resource) and C (cost of an escalated fight) determines the net outcome when different strategies 

meet. In encounters between Hawks, the winner gains control over the value of the resource while 

the losing Hawk sustains an injury. In the common scenario, where the value of the resource is less 

than the cost of injury (i.e., C>V), average payoff in a Hawk meeting a Hawk is negative and 

less than that of a Dove meeting a Hawk. Only in rare situations, when the value of the resource 

exceeds the cost of injury, will Hawk be unequivocally the superior strategy. 

intense fighting among male elephant seals results in the victorious male both 

monopolizing a section of the beach and gaining sole reproductive access to the 

harem of females which resides there. In the vast majority of cases, however, 

resources are rarely worth the risk of injury, and competing individuals would do 

best to resolve conflicts via ritualized displays. 

C. Signaling games 

The earliest game theoretical analyses of aggressive signaling were pessimistic 

about the evolutionary stability of such systems (Caryl, 1979; Maynard Smith, 

1974, 1979). Their reasoning was that if we assume that signals can help in 

winning contests by conveying high levels of aggression or fighting ability, then 

it becomes advantageous for all individuals to give the highest levels of these 

signals. If all individuals signal maximally, then there is no information in the 

signal about either aggressive intentions or fighting ability. The first rigorous 

game theoretical model to demonstrate that reliable aggressive signaling could be 

evolutionarily stable was a mutual signaling game in which two interactants 

chose between two cost-free signals to create a stable global strategy (Enquist, 

1985). This model demonstrated how threat displays reveal information about 

the strength or condition of the contestants via their choice of action in 

aggressive encounters. The players in this game each have a hidden state 

(strength or weakness) which determines their ability to win physical fights. 

An honest weak individual gives a signal conveying weakness, and abandons the 

contest if the other individual gives a signal conveying strength. A dishonest 

weak individual can successfully bluff other weak individuals by giving the signal 

of strength, but at a cost of sometimes being attacked by a better fighter if the


opponent turns out to be strong. If the cost of being attacked by a stronger 

individual is high relative to the benefit of winning contests, then bluffing may 

not be advantageous, and honest signaling can be evolutionarily stable. 

There followed a slew of variant Hawk/Dove models which attempted to 

accommodate the diversity of interactions between senders and receivers (e.g., 

Enquist and Leimar, 1983; Leimar and Enquist, 1984; Maynard Smith and 

Harper, 1988; Skyrms, 2009). These models of communication may be classified 

into five structures based on the relative timing of the (signal and/or response) 

choices made by the two players during the game (reviewed in Hurd and Enquist, 

2005). Mutual signaling games, which most closely resemble agonistic interactions 

between animals, are increasingly being used as models (e.g., Kim, 1995; 

Számadó, 2000). In this structure, both players signal, and react to their opponent’s 

signal, in biologically realistic ways. Genetic algorithms are also being 

used to examine non-ESS solutions to these games (Hamblin and Hurd, 2007). 

Alternative approaches employ simulation methods and neural networks 

(Noble, 2000; Wheeler and de Bourcier, 1995) to explore communication in 

animal contests. 

D. Threat displays and why they are part of aggression 

Aggression is costly to participants not only in terms of energy expenditure and 

the potential for injury but also because of opportunity costs. Time spent in 

physical conflict is time that is not available for other vital activities such as 

exploring, feeding, or mating. Thus, there are selective advantages to reducing 

aggression. Threat displays are a critical component of aggression because they 

modulate competitive social interactions among conspecifics. If signaling is 

effectively delivered by a sender and appropriately interpreted by the intended 

receiver it might be so subtle that the interaction is rendered virtually invisible 

to an outside observer. Alternatively, if sender and receiver perceive the competitive 

difference between them to be slight, the social interaction is prolonged, 

escalates in intensity, and may ultimately culminate in levels of overt conflict 

that result in physical damage or death of one or both interactants. 

In such aggressive signaling contests, two kinds of information are 

important to receivers: information on the signaler’s willingness to escalate 

(aggressiveness motivation) and on its fighting ability (resource-holding potential) 

(Searcy and Beecher, 2009). Classification schemes based on the type of 

interaction in which communication takes place and the nature of the signals 

used converge on the following signal categories (Hurd and Enquist, 2005; 

Maynard Smith and Harper, 2003; Vehrencamp, 2000). 

Performance signals are signals constrained to a subset of signalers either 

by differences in the ability to perform them (Maynard Smith, 1982), or by 

possessing the information needed to produce them (Hurd and Enquist, 2005).


Performance displays (“index signals” of Maynard Smith and Harper, 2003) have 

excellent empirical support, as do models of their use (e.g., Enquist and Leimar, 

1983; Leimar and Enquist, 1984). Examples include the lateral displays of many 

fish (Enquist and Jakobsson, 1986) or the pitch of calls in many frog and mammal 

species (e.g., Bee et al., 1999; Reby et al., 2005), both “unfakeable” signals as they 

are determined by the sender’s size and fighting ability. 

Strategic signals are available to all signalers, and may be either classic 

handicaps or conventional signals (Hurd and Enquist, 2005). Classic handicaps 

have some inherent cost, independent of receiver response, and variation in the 

level of cost experienced by different individuals produces different optimum 

signaling levels (Grafen, 1990). Evidence for handicapped displays is theoretical 

(Zahavi, 1987) rather than empirical, though threat displays have been shown to 

advertise endurance in lizards (Brandt, 2002) and grasshoppers (Greenfield and 

Minckley, 1993). Conventional signals are arbitrary with respect to signal design 

and therefore dependent for meaning on an agreement between the signaler and 

receiver. Honesty of conventional signals in agonistic interactions is maintained 

by two forms of receiver-dependent stabilizing costs (Enquist, 1985; Guilford and 

Dawkins, 1995); receiver retaliation (Enquist, 1985) has empirical support 

(Molles and Vehrencamp, 2001) and vulnerability handicap (Zahavi, 1987) for 

which empirical support is contradictory (Laidre and Vehrencamp, 2008; Searcy 

et al., 2006). Most threat displays appear to be conventional signaling systems. 

Examples include color patches and song-type sharing in birds (Molles and 

Vehrencamp, 2001; Vehrencamp, 2000). Aggressiveness motivation (or willingness 

to escalate) is most likely to be encoded this way (Hurd and Enquist, 2005). 

E. Evolutionary issues 

Empirical analysis of aggressive signaling is more complex than the classic ESS 

modeling approach would suggest. This is in large part attributable to the fact 

that evolution is not necessarily equilibrial (Houston and McNamara, 1999). 

An individual’s success or failure in using signals depends upon how other 

individuals use and interpret those signals, that is, it is a trait under frequencydependent 

selection (Maynard Smith, 1982). In addition to frequency 

dependence of the signal phenotype itself, selection pressures acting on signaler 

and receiver in a communicating dyad may be distinct if their genetic interests or 

risk profiles (Searcy and Nowicki, 2006) are not identical, or if signals have dual 

functions, affecting both aggression and mate choice (Wong and Candolin, 

2005). Selection may also modify the responsiveness of other individuals to the 

signals (Arak and Enquist, 1995). Thus, like other significant evolutionary 

problems such as sexual selection and conflict, signaling strategies may lack 

stable equilibria and remain in constant evolutionary flux. Understanding the


evolution of behavioral phenotypes under such nonequilibrial conditions 

requires dynamic approaches which have yet to be adequately deployed in the 

game-theoretical modeling of biological signaling (Hurd and Enquist, 2005). 

F. The challenge of “incomplete honesty” 

In animal contests, selection should favor displays providing reliable information 

about the fighting ability or aggressive intent of competitors. However, considerable 

theoretical work predicts that low levels of deception may occur within 

otherwise honest signaling systems (Adams and Mesterton-Gibbons, 1995; 

Számadó 2000). Strategic signals (i.e., ones of intent) are particularly prone to 

such corruption because they typically involve low production costs (Maynard 

Smith, 1974, 1979, 1982). Testing for such incomplete honesty is challenging 

because it is difficult to distinguish dishonest signals from natural variation in 

signal size (Moore et al., 2009), and between a successful bluff and an honest 

signal, especially when signaled information is continuous rather than discrete. 

Hughes (2000) suggested that dishonesty could be detected by analysis of signal 

residuals, the residuals from a measure of the regression of signal structure on 

competitive ability. Whereas receivers take advantage of the strong relationship 

between signal and fighting ability, for example, signalers take advantage of the 

variation around this relationship. If individuals who exaggerate signals benefit 

from doing so, they should perform more repetitions of the signaling activity than 

those who do not exaggerate (Hughes, 2000). Empirical examples of incomplete 

honesty, though still comparatively rare, suggest this is not a fixed behavioral 

trait, and depends on context as well as signal residuals (Arnott and Elwood, 

2010; Hughes, 2000; Lailvaux et al., 2009). 

G. Case studies in aggressive signaling 

Using animal models and invasive techniques (e.g., drugs, hormones, brain 

lesions, and gene knockouts), we have made great strides in unraveling the 

mechanisms and internal states underlying aggression in controlled lab situations. 

This is true also with respect to aggressive signaling (see Chapter 5). 

Studies of nonmodel organisms are a necessary complement to this approach as 

these can provide the telling exceptions in field situations where more complex 

social/physical environments permit full expression of behaviors and analysis of 

adaptive function (see Logue et al., 2010). Below, we present two case studies of 

taxa employing multimodal signaling systems to artfully modulate aggressive 

interactions in complex social systems.


II. BIRD SONG SIGNALS AGGRESSIVE INTENTIONS: SPEAK SOFTLY 

AND CARRY A BIG STICK 

The use of song by songbirds provides an excellent illustration of how signals 

function in aggression in nonhuman animals. The songbirds (suborder Passeres) 

consist of over 4000 species of birds, which are distinguished in part by their 

intricate vocal musculature. This musculature functions most importantly in the 

production of the complex vocalizations from which the songbirds derive their 

name. Most species in the group are territorial and monogamous, and their songs 

are used in both territory defense and mate attraction (Catchpole and Slater, 

2008; Searcy and Andersson, 1986). At least in temperate zone species, songs are 

given mainly by males and mainly during the breeding season. Some attributes of 

song and singing behavior have evolved to function in attracting females and 

persuading them to mate, but others have evolved to function in aggressive 

communication between males in the context of claiming and defending 

a territory. 

Many of the signals employed by songbirds in aggressive communication 

can be illustrated using the signaling behavior of song sparrows (Melospiza melodia). 

Song sparrow songs (Fig. 3.1) are multiparted—that is, they contain multiple 

phrases differing in structure (Mulligan, 1963). Individual males sing several 

versions of the species’ song, each consisting of a distinct and largely nonoverlapping 

set of phrases. These distinct versions are called song types (Fig. 3.1), and the 

collection of song types sung by one male is his song repertoire. Repertoire sizes vary 

geographically in song sparrows, with averages in the range of 8–12 song types per 

male (Peters et al., 2000). Male song sparrows produce their repertoires with 

“eventual variety,” meaning that they sing several to many repetitions of 

one song type before switching to another. The successive repetitions of a song 

type are themselves typically not identical, but instead show differences that are 

audible (Borror, 1965; Saunders, 1924) but of lower magnitude than differences 

between song types (Nowicki et al., 1994). The minor variations of a song type are 

termed song variants (Fig. 3.1). Song sparrows respond to differences between song 

variants (Stoddard et al., 1988) but less strongly than to differences between song 

types (Searcy et al., 1995). 

In some species of songbirds, different song types have different functions; 

for example, in wood warblers (Parulidae) some song types may be 

specialized for male–female communication and others for male–male signaling 

(Byers, 1996; Spector, 1992; Weary et al., 1994; but see Beebee, 2004). In song 

sparrows, however, all song types are thought to be functionally equivalent, and 

in that sense “redundant.” Even with redundant song types, however, certain 

signals can be produced with a repertoire of song types that are not possible with 

a single type. Some of these signals have been suggested to be aggressive.


Figure 3.1. Spectrograms of two variants of each of three song types from a male song sparrow 

recorded in northwestern Pennsylvania. Each row shows two variants of one song type. 

Note that virtually every note differs between the different song types, whereas the two 

variants of any one song type tend to differ only in their endings. 

Singing behaviors associated with aggressive contexts in song sparrows 

include: 

1. Song-type switching. If a bird sings more than one song type, it can vary the 

frequency with which it switches between song types, and switching frequency 

becomes a possible signal. Song-type switching frequency has been suggested 

to be a conventional signal of aggression (Vehrencamp, 2000)—conventional 

in the sense that the meaning of the signal is arbitrary with respect to its form. 

In song sparrows, type-switching frequency increases in aggressive contexts, 

for example, during counter singing between territorial males or when an 

outside male intrudes on a territory (Kramer and Lemon, 1983; Kramer 

et al., 1985; Searcy et al., 2000). In other species, the opposite pattern 

holds—type-switching frequency decreases in aggressive contexts (Molles 

and Vehrencamp, 1999; Searcy and Yasukawa, 1990). The fact that either 

pattern can occur supports the arbitrariness of the signal (Vehrencamp, 2000). 

2. Variant switching. In song sparrows, variant-switching frequency also 

increases in aggressive contexts, and the increase is if anything more 

consistent than the increase in type switching (Searcy et al., 2000). Given


the evidence that male song sparrows attend to variant switching (Searcy 

et al., 1995; Stoddard et al., 1988), variant-switching frequency is another 

potential aggressive signal. 

3. Song-type matching. Matching is a behavior in which one male replies to a 

rival with the same song type that the rival has just sung. Matching can occur 

by chance, but in song sparrows it has been shown that when wholly or 

partially shared songs are played to males on or near their territories, those 

males match the playback songs at levels significantly higher than chance 

(Anderson et al., 2005; Burt et al., 2002; Stoddard et al., 1992). Song sparrows 

match strangers more than neighbors (Stoddard et al., 1992), and are more 

aggressive in general toward strangers (Stoddard et al., 1990), providing 

further support for matching as an aggressive signal. 

4. Song rate. The number of songs produced per unit time is a parameter that 

birds can vary even if they sing only a single song type. In some species of 

songbirds, territory owners consistently increase song rates in aggressive 

contexts (Vehrencamp, 2000). Song sparrows have shown this pattern in 

some experiments (Kramer et al., 1985) but not in others (Peters et al., 1980; 

Searcy et al., 2000). 

5. Soft song. In her classic monograph on song sparrow behavior, Nice (1943) 

noted that during intense aggressive encounters, male song sparrows produce 

songs of especially low amplitude. In some other songbirds, such soft songs are 

produced during courtship as well as during aggression (Dabelsteen et al.,1998), 

but in song sparrows they apparently are given only in aggressive contexts. 

Anderson et al. (2008) found that the amplitude of soft songs was as much as 

36 dB lower than the amplitude of the loudest normal or “broadcast” songs. 

The five singing behaviors listed above are all associated with aggressive 

contexts in song sparrows, but signals used in aggressive contexts can convey 

submission or escape as well as attack, in which case they would be considered 

“agonistic” but not “aggressive.” These alternative interpretations seem particularly 

likely a priori in the case of soft songs. To test whether a signal is aggressive 

rather than submissive, it is necessary to determine whether the signal predicts 

aggressive escalation (Searcy and Beecher, 2009). Aggressive escalation includes 

outright physical attack of course, but also includes other behaviors that lead up 

to attack, such as approach to a rival or giving signals that are higher in a 

hierarchy of aggressive signaling. 

A test of the predictive power of singing behaviors was carried out for 

song sparrows by Searcy et al. (2006). In this study, a brief playback of song 

sparrow song was used to elicit aggressive signaling from a territory owner. After a 

5-min period during which displays were recorded, a taxidermic mount of a song 

sparrow was revealed on the subject’s territory, posed above the loudspeaker, in 

conjunction with another brief playback. The subject was then given a set period


of time (14 min) to attack or not attack the mount. Of 95 males that were tested, 

20 attacked and 75 did not. The display behavior of attackers and nonattackers 

was then compared, focusing on the five singing behaviors discussed above, plus 

wing-waving, a display in which a male fans one or both wings while remaining 

perched; this is the most prominent visual display given by song sparrows during 

aggressive contests. For the initial recording period, none of the display measures 

differed significantly between attackers and nonattackers, though the number of 

soft songs approached significance. A second analysis focused on the 1-min period 

directly before attack in the attacking subjects, using a matching time period in 

nonattackers as the control. Here, number of soft songs was significantly higher in 

attackers than nonattackers, whereas none of the other five measures differed 

(Fig. 3.2). In single-variable discriminant function analyses, the number of soft 

songs was the only display that discriminated between attackers and nonattackers; 

this display correctly predicted presence/absence of attack in 74% of the tested 

males. Soft song is thus a reliable signal of aggressive intentions in song sparrows. 

A B C 

Soft songs 

5 

4 

3 

P = 0.00015 

2 

1 

0 

No Yes 

Type switching frequency 

0.2 

NS 

0.15 

0.1 

0.05 

0 

No Yes 

Variant switching frequency 

1 

0.75 

0.5 

0.25 

0 

NS 

No 

Yes 

D 

8 

E 

1 

F 

1.5 

Total songs 

6 

4 

2 

NS 

Matching songs 

0.75 

0.5 

0.25 

NS 

Wing waves 

1 

0.5 

NS 

0 

No 

Attack 

Yes 

0 

No 

Attack 

Yes 

0 

No 

Attack 

Yes 

Figure 3.2. Display measures (means.e.) for the 1 min just prior to attack for male song sparrows 

that attacked compared to a matching 1-min period for nonattackers. The display 

measures are (A) number of soft songs, (B) type-switching frequency, (C) variantswitching 

frequency, (D) total songs, (E) number of matching songs, and (F) number 

of bouts of wing-waving. Only soft songs showed a significant difference between 

attackers and nonattackers. Redrawn from data in Searcy et al. (2006).


The use of soft, low-amplitude vocalizations as the most threatening of 

signals is somewhat counterintuitive, but this result has since been replicated in 

additional species. Ballentine et al. (2008) did a parallel study of aggressive 

signaling in swamp sparrows (Melospiza georgiana), a close relative of song 

sparrows, using methods similar to those of Searcy et al. (2006). Swamp sparrows 

have simpler songs than song sparrows, but again have repertoires of apparently 

redundant song types. In addition to songs, males give two types of calls in 

aggressive contexts, buzzes and wheezes (Ballentine et al., 2008; Mowbray, 

1997). In swamp sparrows as in song sparrows, wing-waving is the most prominent 

visual display given during aggressive encounters. 

In 40 trials with swamp sparrows, 9 males attacked a taxidermic mount 

of a conspecific male and 31 did not. For the initial recording period, five of seven 

display measures did not differ between attackers and nonattackers; these were 

switching frequency, number of matching songs, number of broadcast songs, 

number of rasps, and number of wheezes. Two measures were significantly higher 

in attackers: number of soft songs and number of wing waves. In a forward, 

stepwise discriminant function analysis, soft songs entered first, followed by rasps, 

and these together correctly classified 83% of males as attackers or nonattackers. 

For the 1 min prior to attack, soft songs and wing waves were again the only two 

display measures that differed between attackers and nonattackers. For this time 

period, a discriminant function including soft songs and wing waves was the best 

predictor of attack, classifying 85% of males correctly. 

Hof and Hazlett (2010) have recently performed a similar experiment 

with black-throated blue warblers (Dendroica caerulescens), which are also in the 

songbird suborder but in another family (Parulidae). In 54 trials with blackthroated 

blue warblers, 19 males attacked the mount and 35 did not. Hof and 

Hazlett (2010) compared attackers and nonattackers for four display measures: 

type-switching frequency, total number of songs, number of soft songs, and 

number of ctuk calls. For both an initial recording period and the 1 min prior 

to attack, only the number of soft songs differed significantly between attackers 

and nonattackers, with attackers giving substantially more. In logistic regressions 

based on either time period, soft song was the only significant predictor of attack. 

In a logistic regression that incorporated displays for the entire trial, soft song 

correctly predicted attack behavior in a very impressive 93% of subjects. 

In all three of the songbird species reviewed above, most of the displays 

given in aggressive contexts are not predictive of attack. One theory about such 

displays is that they were at one time predictors of attack, but that over evolutionary 

time their reliability was undermined by the spread of bluffing 

(Andersson, 1980). If an aggressive display is beneficial in intimidating opponents, 

such that the benefit of giving it is greater than any costs, then selection 

will favor its use in individuals that do not intend to attack as well as in those 

that do. Use of the display will then increase in frequency among individuals not


intending attack, until at some point the signal ceases to be informative about 

attack likelihood. Another hypothesis is that these agonistic displays have 

evolved to convey messages other than imminent attack. Possible alternative 

messages include at one extreme retreat or submission, but another possibility is 

for a display to threaten a degree of aggressive escalation that falls short of attack. 

Song-type matching in song sparrows, for example, has been suggested to be part 

of a hierarchy of progressively more aggressive signals, which starts with singing a 

shared song, precedes to type matching, then to staying on the match, soft song, 

and finally attack (Beecher and Campbell, 2005; Searcy and Beecher, 2009). 

Because matching is low in this hierarchy of escalation, with several steps 

intervening between it and attack, matching would not be expected to be very 

informative about attack likelihood; nevertheless, it might still be predictive of 

the next level of escalation. Whether matching is predictive in this manner 

requires further testing. 

Among the small number of songbird species that have been studied in 

this regard, soft song has emerged as an unusually reliable predictor of attack. 

Why a display whose distinguishing characteristic is low amplitude should be 

consistently favored for the highest level of aggressive signaling is not well 

understood. One hypothesis is that by using soft song during an encounter with 

an intruder, a territory owner lowers the chance of interference from other rival 

males by preventing them from eavesdropping on the interaction (McGregor and 

Dabelsteen, 1996), thereby concealing from them that an intrusion is taking 

place. In contradiction to this idea, Searcy and Nowicki (2006) found that, in 

song sparrows, more intrusions by third party males occurred during simulated 

interactions between an owner giving soft songs and an intruder giving loud 

songs than during interactions in which both owner and intruder gave loud 

songs. In other words, use of soft songs if anything increased interference by 

other rivals. A second hypothesis is that soft song is favored as an aggressive 

signal because its low amplitude makes its target unambiguous: only the male 

that is being confronted can discern the signal, so only he can be the target. 

Another way of stating this is that soft song is a performance signal subject to an 

informational constraint (Hurd and Enquist, 2005) that forces it to be honest at 

least with respect to the identity of its target. 

If a display is a reliable signal of aggressive intentions, as is soft song, 

then theory predicts that it should be effective in changing the behavior of at 

least some opponents to the signaler’s advantage (Enquist, 1985). In other words, 

a believable threat should intimidate some opponents, presumably the weaker 

ones, causing them to concede whatever resource is being contested. Effectiveness 

in this sense has not yet been demonstrated for soft song, in part because 

arranging tests of the effectiveness of displays in territorial defense is quite 

difficult (Searcy and Nowicki, 2000). Recent work with corn crakes (Crex 

crex), which are not songbirds and do not sing, shows that low amplitude calls


predict attack, and suggests that these soft calls cause some receivers to retreat 

(Rek and Osiejuk, 2011). Effectiveness in intimidating opponents has been 

demonstrated in some other aggressive signaling systems (Dingle, 1969; Fugle 

et al., 1984; Wagner, 1992). 

III. VISUAL DISPLAYS SIGNAL AGGRESSIVE INTENT IN 

CEPHALOPODS: THE SWEET SMELL OF SUCCESS 

Cephalopods—squid, octopus, and cuttlefish—are marine molluscs with large 

complex brains and highly diverse behavior (Hanlon and Messenger, 1996). 

They are highly visual animals, exemplified partly by their huge optic lobes 

that represent more than half of their central nervous system. These soft-bodied 

cephalopods are renowned for their rapid adaptive coloration: individuals of each 

species can instantly (


Early game theory models of agonistic behavior predicted that animals 

should not signal their probability of attack to their opponents. As Maynard 

Smith (1982) argued, if animals signaled their aggressive motivation during a 

fight, there would be strong selective pressure for animals to “bluff” and to signal 

the highest motivational state possible; such a system would likely be invaded by 

cheaters and become unreliable. However, some animals do signal intent 

(Hauser and Nelson, 1991), and below we provide an unusual example of this 

in cuttlefish. 

As in birds, cephalopods signal aggressive intent but they do so with 

visual signals (chromatic skin patterns) as well as body postures (parallel positioning 

and arm postures). Two examples are given: one from cuttlefish (Order 

Sepioidea) and one from squid (Order Teuthoidea). In addition, a new finding is 

described in which a molecular trigger of aggression has been found in squid. 

A. Cuttlefish agonistic bouts 

In the Intense Zebra Display of the European cuttlefish, Sepia officinalis, the males 

turn on high-contrast stripes and dark eye ring and extend their large 4th arm 

toward the opponent (Fig. 3.3C). Such agonistic encounters between males can 

lead to aggressive grappling and biting. The experiments of Adamo and Hanlon 

(1996) showed that one visual component of the display—the facial darkness— 

was by far the most highly variable in expression, and was a good predictor of 

outcome in encounters in which one male withdrew. In non-escalated encounters, 

the male that ultimately withdrew always maintained a less dark face than 

its opponent (Fig. 3.3A). When the face of a displaying cuttlefish became lighter, 

the other male either remained in the Intense Zebra Display but did not 

approach closely or lightened the intensity of its own display within 15 s. 

When both males maintained a dark face, the agonistic encounters usually 

escalated to physical pushing, and sometimes to grappling and biting (Fig. 3.3B). 

Why would males show an agonistic display to a rival male but simultaneously 

signal their intent not to be aggressive Adamo and Hanlon (1996) 

pointed out that sexual recognition in cephalopods is poorly developed, and that 

the Intense Zebra Display (with 4th arm extended) identifies the signaler as a 

male. The authors suggest that male cuttlefish that are not prepared to attack an 

opponent still give the modified (i.e., light-faced) Intense Zebra Display to 

convey two messages: (1) that it is male, but (2) it is not prepared to escalate 

to aggressive physical contact. As the authors point out, when agonistic displays 

perform more than one function, signaling intent (i.e., signaling its likely 

subsequent behavior) can be an ESS. Unless the fight escalated to grappling 

and biting, there would be little cost to cheaters in this system since males that


A 

Darkness of face (pixel darkness) 

220 

210 

200 

190 

180 

170 

160 

4 

Non-escalated encounter 

6 8 10 12 14 16 

C 

B 

Darkness of face (pixel darkness) 

220 

210 

200 

190 

180 

170 

160 

4 

Escalated encounter 

6 8 10 12 14 16 

Time (s) 

D 

Percentage of losing males 

100 

80 

60 

40 

20 

0 

Intense 

Zebra 

Extended 

4th arm 

Winners 

Losers 

First encounter 

Second encounter (no copulation) 

Second encounter (after copulation) 

Figure 3.3. Cuttlefish signal intent to escalate a fight with a dark face component to their Intense 

Zebra Display. (A, B) Differences in facial darkness during a non-escalated versus 

escalated encounter. (C) Two males in Intense Zebra Display with different degrees of 

facial darkness. (D) When males that lost a fight copulated with a female, they became 

more aggressive in the successive fight. From Adamo and Hanlon (1996). 

bluffed (i.e., gave a dark-faced Intense Zebra Display but had little fighting 

motivation and/or ability) could withdraw at the next stage of agonistic behavior 

with little penalty. 

In the same study, the authors allowed losing males to copulate with a 

female after a bout, and retested them with the male each had lost to. The former 

losers increased facial darkness dramatically in those encounters, showed a longlasting 

Intense Zebra Display, and did not withdraw from an opponent 

(Fig. 3.3D), thus supporting the contention that facial darkness signals the 

animal’s motivational state (i.e., tendency to attack).


B. Squid agonistic bouts 

Male–male fights in Loligo plei are complex visual displays that include up to 21 

behaviors. There is a hierarchy of agonistic signals that sometimes culminates in 

an aggressive physical lateral display and fin beating (Fig. 3.4A and B), which are 

then followed by chase or flee. DiMarco and Hanlon (1997) tested whether 

dominance was based upon the duration or frequency of these behaviors, but it 

was not. Instead, they found that certain visual features such as the lateral flame 

markings (Fig. 3.4B, top squid) could be expressed with high contrast and that 

this was a visual factor in escalation of the agonistic bout. 

Two distinct tactics were exhibited by fighting males in this set of 

laboratory experiments: (1) long bouts with slow escalation from visual signaling 

to chasing and fleeing, or (2) short bouts with very rapid escalation from visual 

signaling to lateral displaying, aggressive physical fin beating, followed by chasing 

and fleeing (Fig. 3.4C). It is noteworthy that the second tactic occurred when 

a female was present (i.e., when a potential resource value was present). As shown 

in Fig. 3.4D, the presence of a female in various combinations had a dramatic 

effect on the nature and duration of the agonistic interactions. Longest bouts 

(mean 14 min) occurred when only two males were present. Bouts became 

progressively shorter when either two males and one female were assembled 

simultaneously, or two males were interacting and a female was then added 

(mean 9 and 3 min, respectively). But when a male and female were put in a 

tank and allowed to pair, and then a nonpaired male was added, tactic 2 was used 

and the highly aggressive interaction lasted only 30 s (a 28 difference over the 

simple two male scenario). As a control, when females were added to male/ 

female pairs, there were no agonistic interactions (Fig. 3.4D). 

In this squid species, the lateral display represents an escalation of 

aggression because it involves parallel posturing and the simultaneous expression 

of many high-contrast visual signals, which collectively give the impression of 

making the squid look larger (e.g., the mid-ventral ridge of the mantle protrudes 

vertically as in the dewlap extension of geckos). Fin beating is a physical, robust 

contest of pushing that can transmit information about strength and size of the 

competing individuals. 

C. From molecules to aggression: Contact pheromone triggers strong 

aggression in squid 

In the squid Loligo pealei, which conducts visual agonistic bouts similar to L. plei 

(above), it was found recently that females deposit a contact pheromone in the 

outer tunic of egg capsules that they lay on the sea floor. When males see the egg 

capsules (even in the absence of females), they are visually attracted to them and 

then physically contact the eggs, which leads to extremely aggressive fighting

A 

B 

Escalation 

Miscellaneous visual signaling 

Visual signaling and 

lateral display 

First 

parallel positioning 

First 

fin beating 

Lateral display and 

fin beating 

Last 

fin beating 

Chase and flee 

Contest duration 

C 

Mean contest duration (min) 

12 

10 

8 

6 

4 

2 

0 

Misc. visual signaling 


Misc. visual signaling 

Lateral display 

Fin beating 


Alternative fighting tactics 

D 

Average contest duration (min) 

20 

18 

16 

14 

12 

10 

8 

6 

4 

2 

0 

/ +/ /+ /+/ / 

Combination 

Figure 3.4. Male squid (Loligo plei) use complex lateral displays to conduct shorter fights with higher aggression when a resource value (i.e., a female mate) is 

present. (A) Schema depicting the escalation pathway to a typical fully escalated agonistic contest. (B) Photograph of a fully deployed lateral 

display and fin beating. The display comprises six visual components: arm spots, dorsal arm iridophores, stitchwork fins, mid-ventral ridge, 

tentacular stripe, and lateral flame. (C) Short fights are more complex and involve lateral displays and physical fin beating. (D) The shortest, most 

dramatic fights occur when a mating pair is already formed, and a rival male is introduced to the tank (♂♀þ♂).


2. Physical 

contact 

3. Extreme 

aggression 

1. Visual 

attraction 

Aggressin 

Human b-microseminoprotein 

N 

N 

s s sss 

ss s s s 

s s sss 

ss s s s 

Figure 3.5. When male squids see egg capsules on the sea floor, then approach and touch them, this 

leads to immediate and dramatic change from calm swimming to extreme fighting. The 

contact pheromone (“aggressin” or Loligo b-MSP) is in the tunic of the egg capsules and 

is similar in structure to that found in humans, mice, and other vertebrates. 

C 

C 

within a minute or two (Fig. 3.5) (Cummins et al., 2011). Thus, there is a twostep 

sensory process: visual attraction to eggs followed by contact chemoreception 

that induces onset of aggression. 

In controlled experiments, the 10 kDa protein pheromone (termed 

Loligo b-microseminoprotein, b-MSP) was isolated and coated onto a clear 

glass flask containing egg capsules, and males that touched the glass (but not 

the eggs) began to signal, fight, and bite each other violently within seconds. 

Glass flasks without the pheromone coating failed to elicit those aggressive 

behaviors. Thus, direct contact with the protein molecules immediately led to 

the full cascade of complex aggressive fighting in the absence of females. Given 

that aggression is often considered to be a result of multiple interactions of 

physiology, hormones, sensory stimuli, etc., this finding reminds us that perhaps 

in some cases there are straightforward pathways to aggression. In fact, the 

proximate mechanisms that trigger or strengthen aggression are not well 

known for many taxa (Wingfield et al., 2005). 

There is a noteworthy vertebrate/mammalian connection to this 

finding. As shown in Fig. 3.6, the b-MSPs are highly conserved throughout the 

animal kingdom. The greatest known concentration of b-MSPs is in human and 

rodent seminal fluid, yet regrettably the functions of b-MSPs are unknown in any 

taxa except cephalopods, as explained above (Cummins et al., 2011). As those 

authors suggest, it would be worthwhile to look for an aggression function for


0.1 

Human (Homo sapien) 

Other primate (consensus) 

Pig (Sus scrofa) 

Rat (Rattus norvegicus) 

Mouse (Mus musculus) 

Red jungle fowl (Gallus gallus) 

Zebra finch (Taeniopygia guttata) 

Ostrich (Struthio camelus) 

Northern pike (Esox lucius) 

Atlantic salmon (Salmo salar) 

Zebrafish (Danio rerio) 

Lancet (Branchiostoma belcheri) 

California mussel (Mytilus californianus) 

Pacific oyster (Crassostrea gigas) 

Bay scallop (Argopecten irradians) 

Limpet (Lottia gigantea) 

Longfin squid (Loligo pealeii) 

Abalone (Haliotis diversicolor) 

Bobtail squid (Euprymna scolopes) 

Rotifer (Adineta vaga) 

Human (Homo sapien) CRISP 

Mouse (Mus musculus) CRISP 

Snake (Rhinoplocephalus nigrescens) CRISP 

Frog (Xenopus laevis) CRISP 

Phylum Chordata Phylum Mollusca Phylum Rotifera 

Figure 3.6. Evolutionary origins and conservation of b-microseminoproteins. The tree shows 

phylogenetic relationships among the protein sequences. The b-MSPs identified in 

the Cummins et al. (2011) study are within the dotted lines. 

b-MSPs in mammals and other vertebrates, given the molecular similarity and 

unique structure of these proteins, all of which seem to be most concentrated in 

exocrine glands in many taxa. Such findings remind us that multisensory cues are 

often involved in stimulating behaviors and that a good deal more research is 

needed before we understand subjects such as aggression. 

D. Signaling aggression in humans 

In humans, as in other species, signaler and receiver have both evolved to use 

variation in aggressive signal structure to their own advantage. In the case of 

human speech, fundamental vocal frequency is perceived to be associated with 

social cues for dominance and submissiveness (Bolinger, 1978; Huron et al.,2009; 

Ohala, 1994), with vocal pitch height used to signal aggression (low pitch), or


appeasement (high pitch). Moreover, a strong correlation with eyebrow position 

suggests an intermodal linkage between vocal and facial expressions (Huron et al., 

2009). Evidence implicates male dominance competition (Puts et al.,2006), rather 

than intersexual selection (see Chapter 2), as the selective origin of this performance 

signal. Similarly, handgrip strength is correlated with level of aggression 

and appears to be an honest signal for quality in males (Gallup et al., 2007). 

Mathematical models show, however, that the tradeoff of deceptive efficacy and 

dishonest signals of intent often favors signalers who produce imperfectly deceptive 

signals over perfectly honest or perfectly deceptive ones (Andrews, 2002). 

Competition among coalition groups (a characteristic shared with chimpanzees) 

initiated a social arms race, culminating in extraordinary human cognitive abilities 

(Flinn et al.,2005), capable of parsing aggressive signals (Paul and Thelen, 1983), 

and competitive displays (Hawkes and Bird, 2002). This great capacity for signaling 

is outstripped only by the uniquely human ability to extend our phenotype 

with weaponry—with the unfortunate consequence that our potential to inflict 

damage frequently exceeds our ability to control aggression. 

Rather than maximizing its absolute amount, natural selection enhances 

the overall effectiveness of aggression. In invertebrates, where individuals generally 

pursue a solitary existence, physical superiority primarily determines the eventual 

outcome of contests, and most fights are quickly resolved on the basis of prominent 

asymmetries in body or weapon size. In vertebrates, which must navigate the 

demands and opportunities of social living, aggressive success is largely contingent 

on the development of social competence. In this case, natural selection favors 

those with an ability to effectively anticipate their chances well in advance of a 

contest, and to signal strength while hiding any intentions to eventually withdraw. 

Generating and interpreting aggressive signals to form successful alliances and to 

inherit status from high-ranking kin, is thus key to winning both short-term 

contests and long-term evolutionary success. 


Production of this chapter was partially supported by funding from NSF grant DUE-0757001 (to M. v. S.). 

W. A. S. thanks his collaborators on the sparrow signaling research including Steve Nowicki, Rindy 

Anderson, Barb Ballentine, Mike Beecher, and Susan Peters. R. T. H. is grateful for partial funding from 

NSF grant IBN-0415519 and many wonderful colleagues who participated in these experiments and field 

observations. 

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4 

Self-Structuring Properties of 

Dominance Hierarchies: A New 

Perspective 

Ivan D. Chase* and Kristine Seitz † 

*Department of Sociology, Stony Brook University, Stony Brook, 

New York, USA 

† Department of Biology, Stony Brook University, Stony Brook, 

New York, USA 


II. Definitions 

A. Dominance relationships 

B. Dominance hierarchies 

III. Animal Models 

A. Chickens 

B. Fish 

C. Crustaceans 

D. Primates 

IV. Factors Affecting Dominance Relationships in Pairs of Animals 

A. Physical differences 

B. Physiology 

C. Genetics 

D. Behavioral states: Winner, loser and bystander effects 

V. Formation of Dominance Relationships 

and Dominance Hierarchies in Groups 

A. Differences in individual attributes and hierarchy formation 

B. Influence of social factors on linear hierarchy formation 

VI. A New Approach to Explaining the Formation 

of Linear Hierarchies: Behavioral Processes 

A. Modifications of the jigsaw puzzle model 

B. Experimental evidence concerning animal cognitive 

abilities and processes of interaction 



DOI: 10.1016/B978-0-12-380858-5.00001-0

52 Chase and Seitz 

VII. Conclusion 


References 

ABSTRACT 

Using aggressive behavior, animals of many species establish dominance hierarchies 

in both nature and the laboratory. Rank in these hierarchies influences 

many aspects of animals’ lives including their health, physiology, weight gain, 

genetic expression, and ability to reproduce and raise viable offspring. In this 

chapter, we define dominance relationships and dominance hierarchies, discuss 

several model species used in dominance studies, and consider factors that 

predict the outcomes of dominance encounters in dyads and small groups 

of animals. Researchers have shown that individual differences in attributes, as 

well as in states (recent behavioral experiences), influence the outcomes of 

dominance encounters in dyads. Attributes include physical, physiological, and 

genetic characteristics while states include recent experiences such as winning or 

losing earlier contests. However, surprisingly, we marshal experimental and 

theoretical evidence to demonstrate that these differences have significantly 

less or no ability to predict the outcomes of dominance encounters for animals 

in groups as small as three or four individuals. Given these results, we pose an 

alternative research question: How do animals of so many species form hierarchies 

with characteristic linear structures despite the relatively low predictability 

based upon individual differences In answer to this question, we review the 

evidence for an alternative approach suggesting that dominance hierarchies 

are self-structuring. That is, we suggest that linear forms of organization in 

hierarchies emerge from several kinds of behavioral processes, or sequences of 

interaction, that are common across many different species of animals from ants 

to chickens and fish and even some primates. This new approach inspires a 

variety of further questions for research. ß 2011, Elsevier Inc. 


Both humans and animals use aggression in many contexts as discussed in this 

volume. In this chapter, we talk about aggression as it is used in the social 

context of establishing dominance relationships and dominance hierarchies. 

A broad range of species—from insects to humans—form these types of relationships 

and hierarchies, and where they occur, hierarchy rank has wide-ranging 

and serious consequences for individuals (Addison and Simmel, 1970; Barkan

4. Self-Structuring Properties of Dominance Hierarchies 53 

et al., 1986; Goessmann et al., 2000; Hausfater et al., 1982; Heinze, 1990; 

Nelissen, 1985; Post, 1992; Savin-Williams, 1980; Vannini and Sardini, 1971; 

Wilson, 1975). These consequences include variation in physiology, stress, 

health, growth rate, access to sexual partners, ability to raise viable offspring, 

and even in the thickness of nerves leading from the hypothalamus to the 

pituitary gland (Clutton-Brock et al., 1984; Ellis, 1995; Francis et al., 1993; 

Holekamp and Smale, 1993; Post, 1992; Sapolsky and Share, 1994). 

Our discussion centers on dominance in less complex animals such as 

chickens, fish, and nonprimate mammals. We begin with behavioral definitions 

of dominance relationships and hierarchies. We then move on to the factors that 

predict dominance in pairs of animals including differences in both traits and 

behavioral states. Traits include genetic, physical, physiological, and “personality” 

attributes; behavioral states include the influences of winning and losing contests, 

as well as observing the contests of other individuals. Next, we review the 

research that demonstrates, very surprisingly, that factors affecting dyadic 

encounters are poor predictors of outcome in dominance encounters within 

groups of any size, even as small as three or four individuals. Consequently, 

researchers should not expect that findings from dominance in pairs of animals 

will easily generalize to small groups of animals. 

Finally, we suggest that rather than trying to predict the ranks of 

individuals in groups, a more appropriate research question is to ask how these 

hierarchies often come to have a linear structure (defined below) across many 

species. We discuss recent experimental findings that conclude that these linear 

hierarchies are self-structuring or self-organizing. Self-structuring hierarchies are 

common across a range of species. They emerge from the repeated use of several 

characteristic, small-scale behavioral processes, or sequences of behavior. We 

describe how these processes generate linear hierarchies and discuss some unresolved 

experimental questions suggested by these behavioral processes. 

II. DEFINITIONS 

A. Dominance relationships 

While researchers have proposed a variety of definitions, in this chapter, we will 

be using a strictly behavioral measure of dominance relationships. More specifically, 

we will define a dominance relationship as characterized by an asymmetry 

of aggressive behaviors by one animal toward another. Typically, both noncontact 

and contact behaviors are involved. Common noncontact type behaviors 

are chasing, displacement, or the threat of aggressive contact. Threat behaviors 

vary by species and include gill flaring in fish; certain vocalizations and gestures 

in primates; and short, rapid movements toward the threatened individual in a


variety of species. Aggressive contact behaviors also vary by species and include 

pecking in the case of chickens and other birds; biting in fish, rodents, and 

primates; and grasping with claws in crayfish, lobsters, hermit crabs, and other 

crustaceans. 

There is no established standard that defines the number of acts in a row 

that are recorded to determine dominance in different species. However, the 

general rule is to use a sufficient number such that, when it is reached, a stable 

relationship has been revealed with very little likelihood of the animal declared 

subordinate beginning to attack the one declared dominant. For example, 

in determining the presence of dominance relationships, Chase et al. (2002) 

declared that one cichlid fish was dominant over another if it bit or chased 

the other fish six times in a row without the other fish initiating an aggressive 

action in return. 

Other methods for determining dominance, such as recording which of 

two animals obtains a desired piece of food, do not necessarily reflect the kind of 

relatively stable social relationships that are indicated by asymmetries in aggressive 

behavior in pairs of animals. For example, when two monkeys are competing 

for a peanut, the winner may be an otherwise subordinate animal that is quicker 

and ready to withstand the chasing and harassing it will receive from the 

normally dominant animal with which it lives in order to secure the peanut. 

Researchers also sometimes determine dominance by observing which individual 

delivers the majority, rather than an uninterrupted sequence, of aggressive acts 

over a period of observation. A measure of dominance such as this may be 

appropriate in some species, such as pigeons and young children, who do not 

always form completely asymmetric relationships. Such measures, however, can 

be misleading if used when animals meet for the first time. When animals meet 

initially, there is often a trading back and forth of aggressive actions before one 

individual begins to deliver all the actions and clearly becomes dominant over 

the other. Figure 4.1 is a music notation graph showing the interactions of two 

0 0:10 0:20 

A 

Figure 4.1. Graphic display of the record of interaction between two hens using music notation. 

Horizontal lines represent individuals, ordered by eventual dominance rank. Each 

aggressive act between individuals is indicated by a vertical arrow from the line 

representing the initiator to the line representing the receiver. The time in minutes 

since the assembly of the pair appears above the graph. Letters at the ends of the 

horizontal lines identify the hens. See Chase (2006) for more information about the 

uses of music notation in visualizing interactions in groups of animals and humans. 

B


chickens setting up a relationship (Chase 2006). If only the first 10 min of 

interactions are considered, then chicken B is dominant over A since B delivers 

83% of the aggressive interactions and chicken A only 17%. However, as time 

goes on, the back and forth actions stop, and chicken A is soon delivering 

all aggressive acts. If a researcher had only considered which individual initiated 

the majority of acts during the initial phases of the interaction, an incorrect 

indication of dominance would have resulted. 

B. Dominance hierarchies 

A dominance hierarchy is the overall collection, or network, of dominance 

relationships among the pairs of individuals in a group. In many small groups 

of animals and human children of around eight or ten members or less, dominance 

hierarchies often take a classical linear form (Addison and Simmel, 1970; 

Barkan et al., 1986; Goessmann et al., 2000; Hausfater et al., 1982; Heinze, 1990; 

Nelissen, 1985; Post, 1992; Savin-Williams, 1980; Vannini and Sardini, 1971; 

Wilson, 1975). In a linear hierarchy, there is one individual who dominates all 

the other group members, a second who dominates all but the top individual, and 

so on, down to the last individual who dominates no one. In larger groups, there 

is often the skeleton of a linear structure, but even with extensive observations, 

researchers do not see interactions between some pairs, especially those that 

seem distant in rank. In hierarchies that are not linear, there are inconsistencies 

in rank showing intransitive relationships (A dominates B, B dominates C, but 

C dominates A). The hierarchies in some animals, especially those with more 

complex social organization such as dolphins, chimpanzees, hyenas, baboons, 

and macaques, are often too complex to be simply classified as linear (Holekamp 

and Smale, 1993; Kummer, 1984; Möller et al., 2001, 2006; Surbeck et al., 2011; 

Widdig et al., 2001, among many others). Our discussion here will concentrate 

on those animals forming more linear hierarchies. 

III. ANIMAL MODELS 

Animal behaviorists have shown that a huge range of animals establish dominance 

relationships and dominance hierarchies in the wild and in the laboratory. These 

include insects such as fruit flies and some ants, wasps and cockroaches; crustaceans 

such as hermit crabs, crayfish, and lobsters; reptiles such as anoles; many 

species of fish, birds, and mammals; and even human preschoolers and adolescents 

(Addison and Simmel, 1970; Barkan et al., 1986; Clark, 1998; Goessmann et al., 

2000; Hausfater et al., 1982; Heinze, 1990; Nelissen, 1985; Post, 1992; Queller 

et al., 2000; Savin-Williams, 1980; Vannini and Sardini, 1971; Wilson 1975).


In biomedical research, an animal model is usually an animal species 

used for research on a human disease or other condition. Dominance researchers 

do not often use specific species in the strict sense of models for human conditions, 

but instead as models for dominance in animals more broadly. The partial 

exception to this is that some researchers have studied dominance in primates to 

discover information about how dominance processes may work in human groups 

(see below). Below is a brief description of animals or animal groups used 

frequently in dominance research and a representative, but by no means 

comprehensive, sampling of work done with these animals. 

A. Chickens 

Chickens were among the first animals to be studied for their dominance 

relationships. Schjelderup-Ebbe (1922) introduced dominance hierarchies into 

the modern study of animal behavior and coined the term “peck order” (or 

Hackordnung in the original German in which he wrote). Schjelderup-Ebbe 

(1922) was among the first researchers to observe the highly linear structure of 

pecking orders. He noted that a number of factors influenced rank in the flock, 

including stress, prior experience, overall health, mating condition, and age. He 

further concluded that dominance is based, not just on the size and strength of 

the combatants but also on the perception of fellow flock members (Schjelderup- 

Ebbe, 1922). 

Other early researchers used chickens to explore the relationship 

between stress and dominance. Sactuary (1932), for example, showed that 

hens that mysteriously molted out of season and went out of laying condition 

had been relegated to the lower ranks of the flock. Thus Sactuary (1932) linked 

rank to both fitness (ability to produce offspring) and stress levels. 

Some more recent investigations in chickens have focused on the 

relationship between dominance, aggression, and selective breeding. These 

lines of inquiry began with the rise of the factory farms, in which aggression 

leading to deaths and lowered egg production is of great concern (Craig and 

Muir, 1996; Craig et al., 1965, 1969, 1975, among others). 

B. Fish 

Fish have recently become one of the most popular vertebrate models for 

dominance research. The fish model system is comparable to chickens, in that 

fish possess easily observed dominance behaviors (chases, bites, and threat 

behaviors), recognize members of their group as individuals, and can maintain 

their dominance hierarchies for extended periods of time. Fish, however, are 

easier to maintain in the laboratory than chickens. They have been used for a 

variety of studies relating to dominance which we can only briefly cover here.

One common type of study of fish explores how differences in behavioral 

states and individual attributes affect the outcome of dominance contests. For 

example, researchers have used fish to investigate the so-called winner, loser, and 

bystander effects (defined below) (Chase et al., 1994, 2002; Hsu and Wolf, 1999; 

Hsu et al., 2006; Oliveira et al., 2009, among others); prior residency, a kind of 

home field advantage assumed to confer benefits in social contexts (Beaugrand 

and Beaugrand, 1991); and the effects of differences in size and prior social 

experience (Beaugrand and Cotnoir, 1996). 

Besides studying factors affecting the outcome of contests, researchers 

have utilized fish in selection experiments studying the heritability of dominancerelated 

aggression (Bakker, 1985, 1986; Francis, 1984, 1987) and in investigations 

into physiological and genetic components of dominance (see Sloman and 

Armstrong 2002 for a review of physiological aspects). 

C. Crustaceans 

Crustaceans are a unique model system that allows researchers to study chemical 

signaling behaviors, and the anatomy of their nervous systems enables researchers to 

study the neural underpinnings of dominance relationship formation (Moore and 

Bergman, 2005). One of the most commonly studied chemical signals in this group 

of species is the release of urine during agonistic behaviors. In lobsters, this signal has 

been implicated in the maintenance of dominance hierarchies (Breithaupt and 

Atema, 2000; Karavanich and Atema, 1998), and in crayfish, it has been shown to 

reduce aggression in opponents during dominance bouts (Breithaupt and Eger, 

2002). Yeh et al. (1997) showed that changes in dominance status altered levels of 

serotonin in the crayfish, Procambarus clarkii. These changes caused modifications in 

the command neuron involved in escape behaviors in this species and were found to 

be reversible and linked to changes in the population of serotonin receptors. 

D. Primates 


The dominance systems of primates are often more complex than the other 

model systems just discussed. As a result, their dominance behavior can more 

easily be generalized to humans. One of the most important lines of research in 

primates has shown how stress affects the hormonal responses of animals of 

different ranks. Sapolsky (1982) studied wild olive baboons (Papio anubis) and 

found that high-ranking males showed a low initial level of cortisol, but in 

response to stress, they had faster and larger spikes of cortisol than their less 

successful counterparts. Sapolsky (1982) suggested that the high ranking member’s 

cortisol responses might be more adaptive to their social environments, 

because their usual, lower cortisol levels conferred immunological and other 

health benefits. A general review of the influence of hierarchies on primate 

health can be found in Sapolsky (2005).


IV. FACTORS AFFECTING DOMINANCE RELATIONSHIPS 

IN PAIRS OF ANIMALS 

In attempting to predict the outcomes of dominance contests in pairs of animals, 

researchers have used two broad classes of variables: differences in attributes or 

traits and differences in behavioral conditions or states. Attributes are relatively 

long-lasting characteristics, while states are shorter-term conditions often influenced 

by behavioral events. 

A. Physical differences 

Differences in physical attributes often have a considerable impact on the 

outcome of dominance encounters. One common characteristic used is differences 

in the sizes of the organisms, which can be broken down into two 

categories: differences in weights and differences in lengths or heights. Researchers 

have found that larger, heavier animals usually dominate animals that are 

smaller and lighter (Frey and Miller, 1972; Houpt et al., 1978; Nakano and 

Furukawa-Tanaka, 1994; Knights, 1987; Lott and Galland, 1987). However, 

when size differences are smaller, other factors can influence the outcomes of 

contests. For example, in male green swordtail fish, a difference of 20–30% in the 

size of the lateral surface area of fish meeting in dyadic dominance contests 

generally resulted in the larger fish becoming dominant over the smaller 

(Beaugrand et al., 1996). Contests between fish with size differences of 

10–20%, however, showed that other factors such as prior social experiences 

(winning or losing) and prior residency influence the outcome of contests. 

Size differences below 10% do not influence dominance contests at all. Instead, 

the social experience (discussed below) of the fish is usually the deciding factor in 

dominance contests (Beaugrand et al., 1996). Similar to standard length, the 

effects of weight on dominance success can be ameliorated by other factors such 

as having won or lost a prior contest (Beacham, 1988; Schulte-Hostedde and 

Millar, 2002). 

Although size and weight are, perhaps, the physical attributes most 

widely studied for their effect on dominance contests, other physical features 

and conditions have also been implicated in dominance success. One example 

that has been studied extensively is the dominance badge, an area of color on the 

body of an animal that acts to indicate dominance to conspecifics (see Senar, 

1999 for a review). Other examples include the state of molt and the size of 

combs in chickens (Collias, 1943), the size of genital papilla in fish (Schwanck, 

1980), and the bill size in birds (Shaw, 1986).


1. Behavioral profile or personality 

Repeatable behavioral type or personality can be defined as suites of behaviors 

that differ among individuals but are consistently repeatable in multiple contexts 

over time (Bell et al., 2009; Boon et al., 2007; Groothius and Carere, 2005; 

Martin and Réale, 2008; Sih et al., 2004; Sinn and Moltschaniwskyj, 2005; 

Svartberg et al., 2005). Researchers have demonstrated that behavioral profiles 

can predict the outcome of dyadic dominance encounters in a variety of species 

with high accuracy. For example, in fish, brown trout that scored higher in 

boldness were more likely to dominate those that scored lower (Sundström 

et al., 2004), and rainbow trout that had shorter or more proactive responses to 

stress were more likely to dominate those with longer or reactive responses 

(Øverli et al., 2004; Schjolden et al., 2005). In birds, mountain chickadees 

classified as high-exploring individuals (those that visited more sites within a 

strange area) dominated low-exploring individuals, and in great tits, fast 

explorers dominated slow explorers (Fox et al., 2009; Verbeek et al., 1996). 

Interestingly, Verbeek et al. (1999) found that the same behavioral profiles in 

great tits that predicted dominance in dyads gave opposite results in groups of five 

to eight great tits. Here, the slow explorers had higher average dominance scores. 

B. Physiology 

Whether or not physiological differences can predict the outcome of dyadic 

dominance encounters is an extremely vexed question. In the mid-twentieth 

century, researchers thought that differences in testosterone, among other 

hormones, were reliable determinants of dominance (For recent work see 

Huber et al., 1997). However, subsequent research demonstrated that the causal 

direction is often reversed—in many species, the ranks of individuals in hierarchies 

has a strong influence on the levels of their hormones and other physiologically 

active chemicals rather than vice versa (see, e.g., Eaton and Resko, 

1974; Sapolsky, 1982; Trainor and Hofmann, 2007). Further, Sloman and 

Armstrong (2002), in a general review, suggest that at least for fish, the physiological 

effects of dominance encounters in simple laboratory settings may be 

stronger than those observed in more complex laboratory or natural habitats. 

These caveats notwithstanding, there is a considerable recent literature 

on physiological predictors of dominance in the dyadic encounters of fish, chiefly 

in trout and salmon. For example, Metcalfe et al. (1995), Cutts et al. (1999), and 

McCarthy (2001) find that fish with higher relative metabolic rates dominate 

those with lower relative rates. In tests of responses to stress, Øverli et al. (2004) 

and Schjolden et al. (2005) report that trout with lower levels of cortisol defeat 

those with higher levels. In experiments in which Arctic charr are dosed with


L-dopa, the immediate precursor of the neurotransmitter dopamine, and trout are 

dosed with growth hormone, treated fish dominated control fish at significant 

rates (Johnsson and Björnsson, 1994; Winberg and Nilsson, 1992). 

We obviously need further research to untangle the complicated chains 

of cause and effect among various physiological variables and outcomes in 

dominance relationships. 

C. Genetics 

The inheritance of dominance and aggressiveness has been a topic of interest 

since the field’s inception. In artificial selection experiments, Craig et al. (1965) 

were able to produce hens with diverging dominance abilities. In dyadic contests, 

hens of high dominance ability usually defeated those of low dominance ability. 

Even based on these early findings, however, Craig et al. (1965) concluded that 

variations caused by interactions between genes (nonadditive genetic variation) 

and environmental factors were likely to be important in the inheritance of 

dominance. Similar studies of paradise fish (Francis, 1984, 1987), cockroaches 

(Moore, 1990), and deer mice (Dewsbury, 1990) confirmed that dominance 

could be artificially selected in a variety of species. Artificial selection, however, 

can only imply a genetic basis for dominance and cannot identify which genes 

are responsible for dominance or subordination. An alternative explanation for 

at least some of these results is that the social environment of mothers (including 

their levels of aggression and dominance ranks) can expose prenatal young to 

androgens that can influence their offsprings’ behavior. Such maternal influences 

operate independently of genotype and have been implicated in the inheritance 

of rank-related behavior. For example, the level of female aggression affects the 

amount of maternally derived testosterone in tree swallow eggs, which, in turn, 

influences the growth and dominance of the hatchlings (Whittingham and 

Schwabl, 2002). In mammals, higher ranking female hyenas (Crocuta crocuta) 

have higher levels of in utero androgens causing their cubs to more aggressive 

than those of lower ranking females (Dloniak et al., 2006). 

To begin to tease apart these and other influences on rank order, the 

newest technological advances in molecular biology are being employed to 

investigate which genes influence social behavior. Sociogenomics, the study of 

social systems at a molecular level, can offer us insights and information never 

before available to behavioral scientists. A variety of unique insights have arisen 

from this new way of studying social dominance and are revealing two major 

themes: one theme is that genes involved in nonsocial behaviors are often also 

implicated in social behaviors; the second is that genes are highly sensitive to 

social influences, and regulation of gene expression by social factors heavily 

influences behavior (Robinson et al., 2005).


An outstanding example of the interplay between genetic expression 

and social factors occurs in the cichlid fish Astatolapia burtoni. In this fish, 

dominant males are brightly colored and actively defend territories for mating. 

Subordinate males are nonreproductive, move about in schools and mimic 

females’ cryptic coloration. Subordinate males, however, grow faster than dominant 

males, giving subordinates the opportunity to depose dominant males from 

their territories. These phenotypes are plastic and males may switch back and 

forth between phenotypes several times in a life span, depending on the availability 

of suitable territories to defend (Burmeister et al., 2005; Renn et al., 2008). 

Burmeister et al. (2005) investigated the neural mechanisms linking 

social environment to physiological changes associated with dominance. They 

found that when a subordinate male perceives an opportunity to move to a 

territory and become dominant, he begins to produce dominant coloration and 

some initial behavioral changes in as little as a day (Burmeister et al., 2005). 

It takes about 7 days, however, for males ascending to dominance to produce the 

same amount of gonadotropin-releasing hormone (GnRH1) as a dominant male, 

during which time the size of testes and GnRH1 neurons increase to sizes 

comparable to dominants (Burmeister et al., 2005). In A. burtoni, GnRH1 is 

produced by neurons in the anterior parvocellular preoptic nucleus (aPPn), the 

most anterior part of the preoptic area in teleosts. To study the behavioral and the 

genomic response to social opportunity, researchers chose to focus on the gene 

egr-1, which codes for a transcription factor involved in neuronal plasticity and 

links membrane depolarization to late-response target genes. Expression of this 

gene was compared in socially ascending males and dominant and subordinate 

males in stable hierarchies (Burmeister et al., 2005). Their results show that 

socially ascending males had a twofold induction of egr-1 in the aPPn, compared 

to the both dominant and subordinate males in stable positions. Expression levels 

in other parts of the brain did not differ with social status or opportunity 

(Burmeister et al., 2005). Stable dominant males do not show this spike in 

egr-1, suggesting that this change is a response to social opportunity rather 

than a response to dominance itself. Although socially ascending males also 

show a difference in physical activity (e.g., more threat displays), it is not clear 

whether there is a simple relationship between egr-1 expression and increased 

motor activity. Instead, Burmeister et al. (2005) conclude that the relationship of 

social context, expression of egr-1, and activity differences have a complex 

relationship that cannot be adequately explained by the simple functional 

motor and sensory aspects of the experience (Burmeister et al., 2005). 

Renn et al. (2008) studied how social context affects physiology, but in 

this case, a microarray was used to investigate coregulated gene sets that might 

differentiate dominant males, subordinate males, and brooding females. The 

results show that there are, indeed, gene sets that are common to each of these 

phenotypes, with males (both dominant and subordinate) and females having


the largest (16%) difference in gene expression (Renn et al., 2008). Twenty-one 

genes were found to be upregulated in the subordinate male phenotype, and it 

was hypothesized that downregulation of these genes would lead to the dominant 

phenotype. Additionally, subordinate males and brooding females were found to 

have a similar expression pattern for 16 genes, possibly suggesting a type of 

subordination module (Renn et al., 2008). Interestingly, although gene sets for 

phenotypic traits were found, results also showed that there was as much variation 

in gene expression between individuals of the same phenotype as there was 

between the phenotypes themselves. This suggests that widely variant gene 

expression in individuals can still yield reliable, easily identifiable phenotypes 

(Renn et al., 2008). 

Trainor and Hofmann (2007) investigated the neuropeptide hormone 

somatostatin, and its receptors, for possible involvement in social behavior. This 

hormone and its numerous receptor subtypes have been shown to play a role in 

the inhibition of growth hormone secretion, among other more diverse effects. 

The relationship between somatostatin gene expression and body size differed 

between dominant and subordinate individuals. In dominant males, the gene 

expression of one subgroup of receptors in the hypothalamus was negatively 

associated with body size. In subordinate fish, however, gene expression was 

positively correlated with body size. This suggests that growth in this animal 

may be socially mediated at the genetic level (Trainor and Hofmann, 2007). 

D. Behavioral states: Winner, loser and bystander effects 

In addition to differences in attributes or traits, considerable research also 

demonstrates that differences in states can influence the outcomes of dominance 

encounters in pairs of animals. Most of this research has examined what are 

known as winner, loser, and bystander effects. In a winner effect, an animal that 

has won an earlier contest with one individual has an increased probability of 

winning a second contest with another individual. In a loser effect, an animal 

that has lost a dominance encounter with one individual has an increased 

probability of losing a subsequent contest with another individual. In a bystander 

effect, an animal that has observed a dominance contest between two others 

alters its behavior, compared to a nonobserver, when it meets either of the 

animals that it observed interacting. 

Researchers have discovered loser effects in a broad range of species, 

and there is some evidence that these effects may last for several days (see, e.g., 

Chase et al., 1994; Hsu et al., 2006). Winner effects seem to be less common 

across species and not as strong as loser effects. Further, some species seem not to 

have them at all (Chase et al., 1994; Rutte et al., 2006). In particular, Fuxjagera 

and Marlera (2010) show that winner effects can be documented in some species


but can be nonexistent in other, closely related species. Where winner effects 

occur, there is some evidence that they are of much shorter duration than loser 

effects, lasting perhaps less than an hour or so after an individual’s initial winning 

experience (Bergman et al., 2003; Chase et al., 1994). Oliveira et al. (2009) have 

shown that winner effects can be ameliorated with antiandrogen drugs, but loser 

effects are unchanged. Clearly, additional work is needed in this area to elucidate 

the role these effects have on the formation of dominance relationships in pairs 

of animals. 

Research indicates that animals in many species are attentive observers 

of other individuals and that they use the information gained in their observations 

in shaping their future behavior with those observed. For example, a 

bystander fish may be less aggressive when it meets another fish it has observed 

winning a contest. Bystander effects have been observed in a broad range of 

species (see, e.g., Oliveira et al., 1998; Oliveira et al., 2001; Danchin et al., 2004; 

Peake and McGregor, 2004). 

V. FORMATION OF DOMINANCE RELATIONSHIPS 

AND DOMINANCE HIERARCHIES IN GROUPS 

Given the research that we have just reviewed, it would seem natural to assume 

that the same factors that strongly predict the outcomes of dominance encounters 

in pairs of animals by themselves should also work for dominance encounters 

between pairs of animals in groups. That is, the factors that predict dominance 

in isolated pairs should also predict dominance for socially embedded pairs. 

Predicting the outcome of dominance encounters for all the embedded pairs in 

a group would allow us to rank individuals within the dominance hierarchy and 

reveal the hierarchical structure. Surprisingly, while individual differences 

in attributes and states do have some influence on rank in hierarchies, that 

influence is significantly less in groups than it is in dyadic pairs. Consequently, 

other factors must be at work in determining individual ranks within hierarchies 

and in generating hierarchical structure. Unraveling that paradox—how individuals 

can be clearly differentiated by rank, but with that differentiation not 

strongly based upon individual differences—is a great challenge in the study of 

dominance hierarchies. 

In the next section, we present evidence demonstrating that individual 

differences can neither adequately predict the places of individuals within 

hierarchies nor explain their overall linear structure. Following that, we describe 

a new approach that we believe can account for the common formation of linear 

hierarchies across a variety of species.


A. Differences in individual attributes and hierarchy formation 

The prior attributes hypothesis proposes that differences in the characteristics 

that animals possess before forming a hierarchy predetermine their resulting 

hierarchy ranks. Figure 4.2 illustrates this hypothesis in graphical form. In the 

hypothesis, the individual ranking highest on attributes takes the top position 

when the hierarchy forms; the individual ranking second-highest takes the 

next-to-the-top position; and so on. Rank based on prior attributes could be 

determined by any set of characteristics: physical ones such as weight, personality 

ones such as aggressiveness or boldness, genetic ones such as overall genotype or 

specific genetic markers, social ones such as the conditions of rearing or family 

background, physiological ones such as various hormone levels, and so on. 

Prior 

attribute 

score 

Hierarchy 

rank 

Figure 4.2. Graphical illustration of the prior attributes hypothesis. Size indicates relative prior 

attribute value; larger size indicates higher rank on prior attributes. Figure adapted from 

Figure 24.1, p. 570 in “Dominance hierarchies” by Ivan D. Chase and W. Brent 

Lindquist from Oxford Handbook of Analytical Sociology ed. by Hedström, P. and Bearman, 

P. (2009), by permission of Oxford University Press.


The problem in testing the prior attributes hypothesis is that although 

an experimenter might know some of the traits that influence dominance, he or 

she might not know all those involved or the size of the contribution of a specific 

trait to dominance outcomes. In order to get around this problem, Chase et al. 

(2002) designed an experiment to test the prior attributes hypothesis without 

knowing which attributes or the sizes of their contributions that might be 

involved in hierarchy formation. 

In their experiment, they brought together groups of four cichlid fish 

and let them form hierarchies, separated the fish for two weeks, which was 

sufficient time for them to forget one another as individuals, and then reassembled 

them to form second hierarchies. The plan was to let the fish form a 

hierarchy and then, to the extent possible, “rewind their tape,” removing all 

memory of recent social experience before letting them form a second hierarchy. 

If prior attributes, whatever they might have been, determined the ranks of the 

fish in the first hierarchy, the attributes, provided they were reasonably stable, 

should also have determined the ranks of the fish in the second hierarchies. 

Consequently, by the prior attributes hypothesis, the positions of the fish in the 

first and second hierarchies should have been the same for all, or at least most, of 

the groups. 

The results of this experiment are shown in Fig. 4.3 and Table 4.1. 

Instead of a high proportion of groups having identical first and second hierarchies, 

the experimenters found that only about a quarter (26%) of the groups did 

so. In nearly three-quarters of the groups, two, three, or even all four fish had 

different ranks in the two hierarchies. Prior attributes did, however, have a 

moderate influence on the ranks of the fish within the hierarchy—more groups 

formed identical first and second hierarchies than expected by chance alone, and 

there was, on average, moderate rank order correlations between the ranks of 

individuals in the two hierarchies. However, the lack of a high proportion of 

groups with identical first and second hierarchies indicated that some other 

factor played a substantial part in the formation of linear hierarchies and the 

ranks of individuals within them. 

One question that can be raised about the interpretation of these results 

is, what if the fish changed after the first hierarchy so that their attribute ranks 

were different before they formed their second hierarchy For example, for 

simplicity consider just one attribute called dominance ability. What if the 

rank on dominance ability before the first hierarchy had been A, B, C, D, but 

before they formed the second hierarchy their order had changed to give a new 

ranking D, C, A, B The difference in dominance ability could still have 

accounted for the linear hierarchies but the fish would have different ranks in 

the second hierarchy than the first. This question is discussed in some detail in 

Chase et al., (2002), which argues against this counter-explanation. In addition 

to that discussion, some more recent experimental work also suggests a lack of


1st 

Hierarchy 

2nd 

Hierarchy 

1st 

Hierarchy 

2nd 

Hierarchy 

A 

B 

C 

D 

(6) 

A 

B 

C 

D 

A 

B 

C 

D 

(1) 

B 

A 

C 

D 

A 

B 

A 

A 

B 

A 

B 

C 

C 

C 

C 

B 

D 

(4) 

D 

D 

(1) 

D 

A 

B 

C 

D 

A 

B 

C 

D 

A 

B 

C 

D 

A 

B 

C 

D 

D 

B 

A 

C 

A 

C1 C2 C3 

(1) 

(1) 

C 

A 

A 

B 

B 

C 

D 

D 

(1) (2) 

B 

A 

B 

C D 

C 

D 

(1) (2) 

D 

A 

A 

B 

C1 C2 C3 

C 

(1) 

(1) 

A 

C2 

C3 

C1 

B 

C 

A 

D 

C 

A 

D 

B 

C2 

C3 

A 

C1 

Figure 4.3. Transition pattern between the ranks of the fish in their first and second hierarchies. 

The total number of groups in the experiment was 22; the number of groups showing a 

particular transition pattern is indicated in parentheses below each pattern. Fish that 

have an intransitive dominance relationship (A dominates B, B dominates C, and 

C dominates A) share the same rank. Intransitive relationships are discussed below.


Table 4.1. Percentage of Groups with Different Numbers of Fish 

Changing Ranks Between their First and Second Hierarchies 

(n¼22) 

No. of fish changing ranks 

Percentage of groups 

0 27.3 

2 36.4 

3 18.2 

4 18.2 

support for this counter-explanation. When isolated pairs of fish are tested under 

the same experimental conditions as the groups forming and reforming hierarchies, 

they have an extremely high rate (94%) of forming the same dominance 

relationship each time. If A dominated B when they met the first time, 

A virtually always dominated B the second time they met. However, at 76%, 

the replication rate for socially embedded pairs in the hierarchy groups was 

significantly less than that of isolated pairs. If the rank of the fish on attributes 

changed between meetings so that they did not always dominate the same fish 

when their hierarchies formed the second time, then likewise there should have 

been a similarly low rate of replication in relationships when the isolated pairs 

met for the second time. But this did not occur, so the changes in the relationships 

and ranks of the fish must be accounted for by other factors rather than 

changes in ranks on attributes. 

B. Influence of social factors on linear hierarchy formation 

In order to discover what factors were necessary for the formation of linear 

hierarchies, Chase et al. (2002) carried out a second experiment with cichlid 

fish. In this experiment, they set out to test that social processes, behavioral 

processes that could only take place in a group context, were crucial for linear 

hierarchy formation and that they contributed more to linearity than prior 

attributes. In this experiment, they allowed groups of four and five fish to form 

hierarchies by two means: round-robin competition and group assembly. In roundrobin 

competition, the fish in a group met only as isolated pairs, out of sight of the 

other members of their group. The sequence of meeting was as follows: first, A and 

B met, then C and D, A and C, D and B, and so on. In this way, differences in 

individual attributes could determine which one of a pair would dominate. If, say, 

A was superior in dominance attributes to B, A could dominate when they met as a 

pair. However, social processes such as C getting information by observing the 

outcome of a contest between A and B and then using that information in


interacting with either A or B was not possible, since each pair formed a relationship 

in isolation from other group members. In group assembly, all the members of 

a group met in an aquarium at the same time. This allowed fish to use whatever 

social process they were capable of in forming their hierarchies. 

Table 4.2 shows the results of this experiment. When groups of fish 

established their hierarchies using round-robin competition, only about half of 

them formed linear hierarchies (but see McGhee and Travis 2010 for contrasting 

results). When they established their hierarchies using group assembly, nearly all 

of the hierarchies were linear. Behavior that only occurred in a group context 

ensured the development of linear hierarchies, while differences in individual 

attributes did not. However, differences in individual attributes still had some 

influence on the production of linear hierarchies: the proportion of linear 

hierarchies with round-robin competition was higher in groups of five fish than 

would be expected by chance alone. 

Although the experiments just described demonstrated that differences 

in the attributes of individuals were of some importance in generating linear 

hierarchy structures, social processes of some sort were necessary to ensure the 

formation of the structures. Another way to look at these findings is that, given 

the attributes of individuals, there was still considerable randomness in their 

positions in the hierarchies. It was far from total randomness, but the amount of 

chance in dominance rank was still substantial. In spite of this degree of 

randomness, the hierarchy structures themselves were almost always linear. 

What social processes could ensure the common formation of these linear 

forms of social organization in spite of the lack of predictability concerning the 

individuals in the structure 

Chase (1982) proposed that winner, loser, and bystander effects together 

might be the social processes largely accounting for the formation of linear hierarchies 

across a variety of species. The basic idea was that even if you started with a 

group of animals of equal prior attributes, they could eventually be differentiated in 

terms of dominance through feedback during the course of their interactions. For 

example, assume that there are both winner and loser effects for some species and 

that A and B have the first interaction when a group is assembled. If A defeats B, A 

Table 4.2. Percentage of Linear Structures Expected in Random Hierarchies and Observed in 

Round-Robin Competition and Group Assembly in Groups of Four and Five Fish 

Method of forming hierarchy 

Size of group 

Random (%) Round robin (%) Group assembly (%) 

4 37.5 56.2 (n¼16) 92.0 (n¼25) 

5 11.7 50.0 (n¼12) 90.9 (n¼11)


increases her probability of winning her next encounter and B decreases hers. A next 

meets C, defeats her, and again increases her probability of winning, while B 

encounters D, loses, and decreases her probability further. 

A number of researchers have developed mathematical models and 

computer simulations to show that feedback from winner and loser effects, either 

working by themselves or together, can, at least in theory, produce highly linear 

hierarchies (e.g., Bonabeau et al., 1999; Dugatkin, 1997; Hemelrijk, 1999; Hock 

and Huber, 2006; 2007; 2009; Skvoretz and Fararo, 1996; Skvoretz et al., 1996). 

However, these models were not tested against actual interaction records of real 

animals forming dominance hierarchies. When Lindquist and Chase (2009) did 

evaluate three (Bonabeau et al., 1999; Dugatkin, 1997; Hemelrijk, 1999) of the 

most prominent of these models and simulations using detailed data records for 

hens establishing hierarchies (Chase 1982), they found little support for the idea 

that winner and loser effects were responsible for the formation of linear dominance 

structures. In addition, when Lindquist and Chase (2009) examined the 

background assumptions on which these models and simulations were based, 

they found little support for these assumptions in the experimental literature. 

Assumptions in the models and simulations include animals not remembering 

one another as individuals, outcomes of earlier dominance contests during 

hierarchy formation not influencing the outcomes of later contests, and most 

important, winner and loser effects actually occurring in groups forming hierarchies. 

In fact, the literature indicated that the actual experimental findings 

were in virtually all cases directly opposite to the assumptions of the models and 

simulations. For example, animals setting up hierarchies do remember one 

another as individuals—even in the case of fruit flies (Yurkovic et al., 2006). 

The outcome of earlier contests do influence the later ones, and perhaps most 

striking of all, winner and loser effects do not seem to occur in groups forming 

hierarchies (Brown and Colgan, 1986; Chase et al., 2003; Cheney and Seyfarth, 

1990; D’Eath and Keeling, 2003; D’Ettore and Heinze, 2005; Gherardi and 

Atema, 2005; Karavanich and Atema, 1998; Lai et al., 2005; McLeman et al., 

2005; Tibbetts, 2002; Todd et al., 1967; Yurkovic et al., 2006). 

In particular, Chase et al. (2003) investigated several basic aspects of 

dominance relationships in isolated versus socially embedded pairs in groups of 

three and four fish. These aspects of relationships included winner and loser 

effects, stability of relationships over time, and the ability of pairs to replicate a 

relationship after a separation of two weeks (as described above). Specifically, 

while there was a strong loser effect in isolated pairs of fish, this effect was not 

above chance for socially embedded pairs. There was no winner effect in either 

isolated or socially embedded pairs. In addition, dominance relationships were 

much less stable over time for pairs within groups (a significant proportion of 

these relationships reversed over 24 h) compared to no relationships reversing 

in isolated pairs, and a significantly smaller proportion of pairs within groups


did not form the same relationships when they met a second time after a 

separation of two weeks as compared to isolated pairs. In summary, all the 

aspects of relationships the researchers tested either disappeared or were significantly 

reduced for socially embedded pairs as compared to pairs by themselves. 

This experiment provides a strong warning of the danger of simply assuming 

that experimental results for isolated pairs can be automatically generalized 

to animals that are part of groups—even those as small as three or four 

individuals. 

Given the lack of fit between these three prominent winner/loser 

models and actual data on the formation of hierarchies in real animals, and the 

almost total absence of experimental support for the basic assumptions of the 

models, it seems reasonable to suggest that winner and loser effects cannot 

account for the common occurrence of linear hierarchies in animal groups. But 

could some other models, based upon states, still satisfactorily explain linear 

structures For example, what about bystander states These states have also been 

used in models, both for animals and humans, as a way to account for linear 

hierarchies (e.g., see Dugatkin and Earley, 2003; Skvoretz and Fararo, 1996; 

Skvoretz et al., 1996). Although Lindquist and Chase (2009) did not look at 

bystander effects per se, they did point out that a bystander effect can often be 

decomposed into winner and loser effects; for example, a bystander increases its 

probability of winning over an individual that it has observed losing a contest 

and decreases its probability of defeating an individual that it has observed 

winning a contest. In cases of this sort, Lindquist and Chase’s (2009) results 

also indicate the difficulty of bystander effects in explaining the common presence 

of linear structures. 

While it is impossible to prove categorically that no differences in states 

for individuals could ever account for the forms of hierarchy structures, winner, 

loser, and bystander effects are the best candidates that have been proposed so 

far. Given the lack of support for them, it appears doubtful, at least to us, that 

differences in the states of animals can be adequate explanations for the social 

organization of hierarchies. 

VI. A NEW APPROACH TO EXPLAINING THE FORMATION 

OF LINEAR HIERARCHIES: BEHAVIORAL PROCESSES 

Given the apparent absence of support for differences in individual attributes and 

states as satisfactory explanations for linear hierarchies, we now review an 

alternative view: that the social organization of hierarchies can be explained 

by characteristic behavioral processes that commonly occur across many species 

during hierarchy formation.


Chase’s (1982) “jigsaw puzzle” model presented the original version of 

this idea. The jigsaw puzzle model suggested that like the picture in a real jigsaw 

puzzle, a linear hierarchy forms when the “right” small pieces, in this case of 

social interaction, are put together in the correct manner. In this way, the model 

sees the dominance hierarchy as self-organizing or self-structuring. More specifically, 

the model indicates four possible sequences for the formation of the first 

two dominance relationships in subgroups of three animals making up a larger 

group. These four sequences, shown in Fig. 4.4, have different implications for 

the formation of linear hierarchies. The two patterns on the left, Double Dominance 

and Double Subordinance, guarantee transitive dominance relationships, 

regardless of the direction that the missing third relationship in those sequences 

takes when it fills in later. In a transitive relationship, individual X dominates 

individual Y, individual Y dominates individual Z, and individual X also dominates 

individual Z. For example, in Double Dominance, if B later comes 

to dominate C, the transitive relationship is A dominates B, B dominates C, 

and A dominates C. If C later comes to dominate B, the transitive relationship is 

A dominates C, C dominates B, and A dominates B. The fact that Double 

Dominance and Double Subordinance guarantee transitive relationships is very 

important because transitive relationships are the building blocks of linear 

hierarchies. By mathematical definition, if all the subgroups of three individuals 

in a larger group have transitive relationships, the hierarchy is necessarily linear. 

Thus the presence of only Double Dominance and Double Subordinance 

sequences in the subgroups of three animals (component triads) making up a 

larger group guarantees that a hierarchy will be linear, even before the missing 

third relationships in the component triads have formed. 

A A A A 

1 2 

1 1 2 

1 

B C B 

2 

C B C B 

2 

C 

Double 

dominance 

Double 

subordinance 

Bystander 

dominates 

Initial 

subordinate 

initial dominant dominates 

bystander 

Figure 4.4. The four possible sequences for the first two dominance relationships in a component 

triad. Arrows show the direction of dominance relationships between the members of a 

triad. The number 1 indicates the first relationship to form in a triad and 2 indicates the 

second relationship. In all triads, A is the initial dominant, B is the initial subordinate, 

and C is the bystander. Figure adapted from Figure 24.2, p. 574, in “Dominance 

hierarchies” by Ivan D. Chase and W. Brent Lindquist from Oxford Handbook of 

Analytical Sociology ed. by Hedström, P. and Bearman, P. (2009), by permission of 

Oxford University Press.


On the other hand, if a hierarchy is nonlinear, it contains at least one 

component triad with an intransitive dominance relationship; the more intransitive 

triads, the further the hierarchy is from linearity. In an intransitive 

relationship, X dominates Y, Y dominates Z, but Z dominates X. The two 

sequences on the right of the figure, Bystander Dominates Initial Dominant 

and Initial Subordinate Dominates Bystander, can lead to either transitive or 

intransitive relationships depending upon how the third dominance relationship 

eventually fills in. For example, in Bystander Dominates Initial Dominant, the 

relationship is transitive if C later dominates B (C dominates A, A dominates B, 

and C dominates B), but intransitive if B later dominates C (A dominates B, 

B dominates C, C dominates A). If a group had one or more Bystander Dominates 

Initial Dominant and Initial Subordinate Dominates Bystander sequences, 

the chance for a nonlinear hierarchy would be increased when the third relationships 

in the triads eventually formed. 

In a study of groups of three hens forming hierarchies, Chase (1982) 

found that almost all relationships were established using Double Dominance 

and Double Subordinance sequences. In 23 groups of three hens, 91% of the 

groups used Double Dominance and Double Subordinance together, while only 

8% used the sequences not ensuring transitivity. In a second study of 14 groups of 

four hens (Chase, 1982), approximately 87% of the component triads in the 

groups (each group of four had four subgroups of three for 56 triads altogether) 

used Double Subordinance and Double Dominance, while approximately 13% 

had sequences not guaranteeing transitivity. These results are in contrast to those 

expected by chance, in which each sequence would have occurred about 25% of 

the time (or 50% combined for the two ensuring transitivity and 50% for the two 

not doing so). 

Thus, the jigsaw puzzle model indicated that the hens established 

dominance relationships largely through behavioral sequences that guaranteed 

transitivity in their triads, and transitivity in their triads in turn guaranteed 

overall linear hierarchy structures. After Chase’s (1982) application of the model 

to hens, other researchers used the original model and some modifications of it to 

examine dominance interactions in a broad range of species including rhesus 

monkeys, Japanese macaques, Harris sparrows, crayfish, and ants (Barchas and 

Mendoza, 1984; Chase and Rohwer, 1987; Eaton, 1984; Goessmann et al., 2000; 

Heinze, personal communication; Mendoza and Barchas, 1983). In spite of the 

great differences among these species in phylogenetics, intelligence, and ways of 

making a living, all showed highly significant use of sequences ensuring transitivity, 

although this was somewhat lower in crayfish and large groups of Harris 

sparrows (Chase and Rohwer, 1987; Goessmann et al., 2000). These results 

suggest that behavioral sequences ensuring transitive dominance relationships 

may be common for many species that form dominance hierarchies. Further 

research to confirm this possibility would be helpful.


A. Modifications of the jigsaw puzzle model 

In recent work, Lindquist and Chase (2009) reanalyzed Chase’s (1982) original 

data for groups of four hens forming dominance hierarchies and discovered two 

additional behavioral processes promoting the efficient formation of linear hierarchies 

in addition to those described above under the jigsaw puzzle model. The 

first additional process is the relative lack of back and forth fighting in pairs of 

animals within a group establishing a dominance hierarchy. Lindquist and Chase 

(2009) referred to back and forth fighting as pair flips—first A attacks B, then B 

attacks A, and so forth. Consider two groups forming a dominance hierarchy: in 

one group, there are many pair flips before they eventually form a stable linear 

hierarchy. In the second group, there are no counterattacks, and the group forms a 

stable linear hierarchy without pair flips. The formation of dominance relationships 

and their linear hierarchy is much more “efficient” in the second group. 

In their analysis, Lindquist and Chase (2009) found that the hens 

formed their relationships with a high level of efficiency—one approaching 

that of the hypothetical second group just mentioned. Of the 7257 aggressive 

acts recorded over the 12 h of observation for each of the 14 groups of four hens 

(168 h of observation, total), only 138 interactions (1.9%) involved pair flips. 

The second additional behavioral process was the rapid conversion of 

intransitive dominance relationships to transitive ones. As indicated above, the 

original application of the jigsaw puzzle model to the hen data showed that the 

great majority (87%) of the behavioral sequences in the component triads for the 

groups of four hens were those ensuring transitivity. However, a more detailed 

reanalysis of the data indicated that a few triads did initially form intransitive 

relationships and that several others that initially had transitive relationships 

later developed intransitive ones. For example, if the triad ABC initially had a 

transitive relationship A>B, B>C, and A>C, it would become intransitive if 

C reversed its relationship with A to give A>B, B>C, and C>A. 

In their analysis, Chase and Linquist, (2009) found that, in virtually all 

cases, intransitive relationships were unstable and quickly converted to transitive 

ones, returning hierarchies to linearity after brief episodes of nonlinearity. 

The average number of dominance interactions (pecks, feather pulls, etc.) that 

occurred among group members before an intransitive triad was converted back 

to a transitive one was approximately 5.2. In contrast, the average number of 

interactions occurring before a transitive triad was converted into an intransitive 

one or into a different transitive one was approximately 54.3 interactions or over 

10 times as many. Research by Chase and Rohwer (1987) on Harris sparrows 

supports these findings: they also found a strong tendency for intransitive dominance 

relationships to be unstable and to convert to transitive ones. Further 

experimental work is needed to determine whether the instability of intransitive 

relationships and their reformation as transitive ones are found in other species.


B. Experimental evidence concerning animal cognitive abilities 

and processes of interaction 

In order for animals to carry out the kinds of behavioral processes that we have 

just discussed, they must possess an array of quite complex cognitive abilities. 

These include the abilities to remember one another as individuals, to make 

inferences about their own interactions and the interactions of others, and to use 

those inferences in adjusting their future dominance behavior. We have already 

discussed the extensive experimental evidence concerning the ability of animals 

to identify and remember one another as individuals, and to make inferences 

about certain kinds of interactions. In particular, we know that a broad range of 

species can infer transitivity (Bond et al., 2003; Davis, 1992; Gillian, 1981; 

Grosenick et al., 2007; Lazareva, 2004; Paz-y-Mino et al., 2004; Roberts and 

Phelps, 1994; Steirn et al., 1995; von Fersen et al., 1991). For example, if B has 

dominated C, and C observes A dominating B, C will act less aggressively toward 

A when they meet than C will toward an animal that it has simply seen dominate 

another individual. 

As far as we are aware, however, there have been no experimental 

studies to show that animals can infer or act upon intransitivity. Such studies 

could confirm the findings of Lindquist and Chase (2009) and Chase and Rohwer 

(1987) mentioned above and extend our knowledge of the behavioral processes 

leading to the formation of linear hierarchies. 

VII. CONCLUSION 

We have pointed out that there are two types of approaches that researchers can 

use to explain the formation of dominance relationships and dominance hierarchies 

in small groups of animals. The first approach uses individuals as the unit 

of analysis—either concentrating on differences in their traits before hierarchy 

formation or differences in the states that they develop during group formation. 

The theoretical and experimental evidence that we have reviewed indicates that 

explanations based upon differences in the attributes and states of individuals 

often work quite well to predict the outcome of dominance encounters in 

isolated pairs of animals. But that evidence also demonstrates, surprisingly, 

that these same differences in individuals are less able to predict the outcomes 

of relationships in socially embedded pairs or the overall ranks of individuals in 

their groups. 

In order to resolve this problem, we have suggested that we need to ask a 

new research question—not what determines the ranks of individuals in hierarchies, 

but how linear hierarchies themselves develop. As the beginning of an 

answer to this question, we have discussed the support for a new approach that


uses behavioral processes to account for hierarchy structures. For some, such an 

approach may seem to be a kind of “cheating,” an avoidance of discovering 

things about individuals that really do explain their “successes” and “failures” in 

winning dominance contests within hierarchies. However, because the greater 

complexities of groups introduce an unavoidable chance element into the predictions 

about individuals within hierarchies, then perforce we need an approach 

that does not depend upon those individuals as units of analysis. A rough analogy 

is the way we look at the organization of tosses of a coin. Because of randomness, 

we do not try to predict the outcomes of individual coin tosses. Instead we move 

to a higher level of the phenomenon: we say something about the organization, 

or form of the distribution, of a great many coin flips. The behavioral process 

explanation of hierarchy structure is our attempt to get around the chance 

elements in what individuals do in hierarchies, and to say something about the 

organization of hierarchies in spite of that randomness. 

Recognizing when individual-based and process-based approaches are 

best applied in studies of dominance has fundamental importance in choosing 

the kinds of data we collect, how we analyze those data, the explanations that we 

develop for hierarchies, and for the cognitive capacities, for both humans and 

animals, that we envision as underlying dominance behavior. 


We thank Hronn Axelsdottir and Paul St. Denis for their help with the graphics in this chapter and 

Robert Huber for inviting us to participate in this volume. 

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5 

Neurogenomic Mechanisms of 

Aggression in Songbirds 

Donna L. Maney* and James L. Goodson † 

*Department of Psychology, Emory University, Atlanta, Georgia, USA 

† Department of Biology, Indiana University, Bloomington, Indiana, USA 

I. Aggression in Context 

II. Hormonal Mechanisms of Aggression 

A. Territoriality in the breeding season 

B. Hormones and territoriality 

C. Aggression outside the breeding season 

D. Evolution of aggression and life history strategies 

III. Transcriptional Activity and Neural Mechanisms 

of Aggression in Birds 

A. Transcriptional traces of aggression reveal ubiquitous 

vertebrate themes 

B. Neurochemistry and major modulators 

IV. A Natural Model Uniting Social Behavior, Hormones, and 

Genetics 

A. The white-throated sparrow 

B. Endocrine and neuroendocrine correlates of 

behavioral polymorphism 

C. Causality and “phenotypic engineering” 

D. Mapping the ZAL2 m 

V. Future Directions 


References 



DOI: 10.1016/B978-0-12-380858-5.00002-2

84 Maney and Goodson 

ABSTRACT 

Our understanding of the biological basis of aggression in all vertebrates, including 

humans, has been built largely upon discoveries first made in birds. 

A voluminous literature now indicates that hormonal mechanisms are shared 

between humans and a number of avian species. Research on genetics mechanisms 

in birds has lagged behind the more typical laboratory species because the 

necessary tools have been lacking until recently. Over the past 30 years, three 

major technical advances have propelled forward our understanding of the 

hormonal, neural, and genetic bases of aggression in birds: (1) the development 

of assays to measure plasma levels of hormones in free-living individuals, or “field 

endocrinology”; (2) the immunohistochemical labeling of immediate early gene 

products to map neural responses to social stimuli; and (3) the sequencing of the 

zebra finch genome, which makes available a tremendous set of genomic tools for 

studying gene sequences, expression, and chromosomal structure in species for 

which we already have large datasets on aggressive behavior. This combination 

of hormonal, neuroendocrine, and genetic tools has established songbirds as 

powerful models for understanding the neural basis and evolution of aggression 

in vertebrates. In this chapter, we discuss the contributions of field endocrinology 

toward a theoretical framework linking aggression with sex steroids, explore 

evidence that the neural substrates of aggression are conserved across vertebrate 

species, and describe a promising new songbird model for studying the molecular 

genetic mechanisms underlying aggression. ß 2011, Elsevier Inc. 

I. AGGRESSION IN CONTEXT 

Biomedical studies of aggression and its genetic basis are most often focused on 

pathology, yet aggressive behaviors and related agonistic displays are essential, 

adaptive components of social behavior that enable animals to secure and defend 

food, mates, and territories. For many species, aggression is also required to 

protect offspring from would-be predators. Thus, given that effective aggression 

is often essential for gene propagation, we can expect that it will be under strong 

selection to meet species-typical and population-specific demands. Further, for 

any given species, aggression will be adaptive in some contexts but not others, 

and it may therefore be the case that the neural and neurogenomic mechanisms 

of aggression vary in relation to the functional goals of the behavior. Numerous 

findings support this view, including evidence that parental aggression and male– 

male aggression are regulated by different suites of neuroendocrine mechanisms 

in rodents (Gammie, 2005; Trainor et al., 2008; Veenema et al., 2007) and that 

neuropeptides differentially influence territorial aggression and aggressive competition 

for mates in songbirds (Goodson and Kabelik, 2009). Indeed, the idea

5. Neurogenomic Mechanisms of Aggression in Songbirds 85 

that aggression is differentially regulated across distinct functional contexts, and 

distinct motivational states, has been around for more than 40 years (Moyer, 

1968). This functional perspective suggests that ethological approaches will be 

particularly useful for identifying integrated suites of neurogenomic mechanisms 

that regulate aggression in any given context and will provide a powerful 

framework for distinguishing pathology from normal, adaptive variation 

(Blanchard and Blanchard, 2003, 2005). 

In this review, we focus on aggression in the context of competition for 

resources, for example, defending a breeding territory or a position in a dominance 

hierarchy within a social group. This type of aggression, particularly in a 

reproductive context, is part of a suite of related behaviors that characterize a 

“life history strategy” maximizing short-term gains as opposed to longer term 

investments (Maynard-Smith, 1977; Trivers, 1972). Short-term relationships 

with mates, high aggression among same-sex individuals, and low parental care 

typify this strategy. At the other end of this continuum is a strategy characterized 

by commitment to one mate, avoidance of injury, and a high level of parental 

care. The two strategies are difficult to employ simultaneously, resulting in a 

trade-off between time spent on territorial aggression versus parenting. This 

trade-off has become a classic principle in ethology and is universal among 

vertebrates, including humans (Trivers, 1972). 

Disruptive selection that drives the sequestration of territorial and 

parental behavior into alternative strategies is most likely to act on genes with 

widespread effects—particularly those with multiple functions. Genes encoding 

the action or regulation of hormones are obvious examples of such genes (Finch 

and Rose, 1995; Hau, 2007; Ketterson and Nolan, 1992; McGlothlin and 

Ketterson, 2007; Miles et al., 2007; Moore, 1991; Nijhout, 2003; Rhen and 

Crews, 2002; Sinervo and Svensson, 2002). A growing literature suggests that 

trade-offs between parenting and territorial aggression are associated with gonadal 

steroids; in many species of fish, birds, rodents, and primates, including humans, 

high levels of circulating androgens are associated with increased intrasexual 

competition manifested as aggression or mating effort, whereas low levels are 

associated with increased parenting effort (e.g., Ketterson and Nolan, 1994; 

McGlothlin et al., 2007). In humans, paternal care and fatherhood have been 

repeatedly shown to correspond to low levels of testosterone (T) (Fleming et al., 

2002; Gray, 2003; Gray et al., 2002; Storey et al., 2000; Wynne-Edwards, 2001), 

whereas high T levels are associated with male–male aggression and competition 

(Bernhardt et al., 1998; Book et al., 2001; Booth et al., 1989). These opposing 

strategies can be generalized as a tendency to prioritize shorter term goals (mating) 

versus longer term goals (parental investment); at the former end of this 

continuum in humans, associations have been reported between T and antisocial 

activities such as alcoholism, drug use, reckless driving, failure to plan ahead, risktaking, 

and assaults (Aromaki et al., 1999; Dabbs and Morris, 1990; Udry, 1990).


Strategies to balance effort toward short-term versus long-term goals may therefore 

involve a limited number of hormones and genes. In this review, we attempt 

to bring together behavior, reproductive endocrinology, and genetics by focusing 

on species in which all three have been characterized in some detail. 

Since the scientific study of behavior began, birds have been the most 

commonly studied animals in relation to territoriality, dominance, and agonistic 

communication. Their popularity primarily reflects their unique accessibility— 

including location and use of vocal and visual communication channels—and 

the fact that territorial birds are readily captured using mist nets and playback of 

song. For the biomedical researcher attempting to model social behavior in 

humans, birds may seem to represent a rather distant taxonomic group. But in 

fact, birds have provided the test bed for some of the most influential theories in 

the history of aggression research, and it is no exaggeration to say that our 

understanding of the hormonal mechanisms of aggression in all vertebrates, 

including humans, has been built in large part upon discoveries that were 

first made in birds (Archer, 2006; Goodson et al., 2005a,b,c; Konishi et al., 

1989). For example, pioneering studies in birds established the theoretical 

framework currently used by researchers to understand how hormones mediate 

a trade-off between aggression and parenting in mammals (Wingfield et al., 

1990). This theoretical framework, which has been called the “challenge 

hypothesis,” is based on the idea that the role of gonadal steroids in aggression 

is modulated by social context. It predicts that when males are challenged in a 

reproductive context, T levels rise to facilitate territorial aggression and suppress 

parental behavior. Since it was first proposed by Wingfield et al. (1990), the 

challenge hypothesis has found support in a wide variety of nonavian vertebrate 

taxa including fish, reptiles, and primates, including humans (reviewed by 

Archer, 2006). The parallels between songbirds (particularly New World sparrows) 

and humans with regard to the social modulation of gonadal steroids and 

their effects on aggressive and parental behavior are voluminous and are summarized 

in Table 5.1. The underlying neuroendocrine mechanisms are nearly 

identical in birds and humans and are based on the function of the hypothalamopituitary-gonadal 

(HPG) axis, which is universally recognized as being highly 

conserved across all vertebrates (reviewed by Adkins-Regan, 2005). 

Despite the contributions of avian research to our understanding of 

human behavior, genomic resources in birds have lagged well behind those in 

mammals—although this situation is now rapidly changing. In the sections that 

follow, we first explore the neural and endocrine literature on songbird aggression, 

and then describe a relatively new research program that is focused on the neurogenomics 

of territorial aggression in white-throated sparrows (Zonotrichia albicollis), 

a species that exhibits morphological and behavioral polymorphisms associated 

with a chromosomal inversion (Thomas et al., 2008; Thorneycroft, 1975). Importantly, 

the morphs differ not only in their territorial aggression, but also in parental


Table 5.1. Evidence of Shared Mechanisms of Competitive Aggression in Birds and Humans 

Prediction Evidence in New World sparrows Evidence in humans 

Males respond to competition 

with increased plasma T 

The plasma T response to 

challenge increases 

aggression 

Plasma T levels are lower 

among paternal males 

Aggressive dominance is 

correlated with plasma 

T levels 

Plasma T is associated with 

alternative life history 

strategies regarding 

territoriality versus 

parenting 

Wingfield (1985), Wingfield and 

Hahn (1994), Wingfield and 

Wada (1989), Wingfield et al. 

(1990) 

Archawaranon et al. (1991), 

Wingfield (1984b, 1994b) 

Wingfield (1984a), Wingfield 

and Farner (1978), Wingfield 

and Goldsmith (1990), 

Wingfield et al. (1990) 

Archawaranon and Wiley 

(1988), Schlinger (1987), 

Wiley et al. (1993) 

Hau (2007), Ketterson and 

Nolan (1992), McGlothlin 

et al. (2007), Schoech et al. 

(1998), Spinney et al. (2006), 

Wingfield (1984a,b,c) 

Meta-analysis of 23 studies in 

Archer (2006) 


Archer (2006) 

Berg and Wynne-Edwards 

(2001), Fleming et al. 

(2002), Gray et al. (2002), 

Storey et al. (2000) 


Archer (2006) 

Dabbs and Morris (1990), 

Dabbs et al. (1997), 

Daitzman and Zuckerman 

(1980), Gray et al. (2002), 

Julian and McHenry (1989) 

The endocrine underpinnings of competitive aggression are broadly similar in New World 

sparrows (here limited to the Zonotrichia, Melospiza, and Junco genera) and humans (based primarily 

on Archer, 2006). Only a fraction of the relevant literature is cited here. 

behavior, and thus this species offers an extraordinary opportunity to examine 

neurogenomic mechanisms that integrate aggression with other aspects of social 

phenotype and context-specific behavior. 

II. HORMONAL MECHANISMS OF AGGRESSION 

A. Territoriality in the breeding season 

There are about 10,000 species of birds, almost half of which are songbirds. 

Territoriality runs the gamut, with members of some species nesting colonially or 

cooperatively, others defending territories of several hectares. Perhaps the beststudied 

territorial species are the seasonally breeding New World sparrows, 

which include song sparrows (Melospiza melodia), field sparrows (Spizella pusilla), 

white-crowned sparrows (Zonotrichia leucophrys), and dark-eyed juncos (Junco 

hyemalis; see Arcese et al., 2002; Chilton et al., 1995; Carey et al., 2008; Nolan 

et al., 2002 for reviews). In migratory populations, the males arrive at the


breeding grounds a week or so before the females and stake out territories 

containing food sources and nest sites. The females then arrive, basing their 

mate choices on the quality of the males as well as their territories. It is therefore 

important, in fact critical, for males to establish high-quality territories early in 

the breeding season. Once a male has attracted a mate, she will help defend the 

territory. 

The most ubiquitous and frequent behavior used for territory defense by 

songbirds is, not surprisingly, song. Each species’ song is distinct, and within a 

species there is enough variation that individuals can recognize each other’s 

songs (Krebs, 1971). Some species sing different types of song in different 

contexts; for example, the “complex song” of the field sparrow is considered 

more aggressive than the “simple song” (Carey et al., 2008; Nelson and Croner, 

1991), and the chestnut-sided warbler (Dendroica pensylvanica) sings a different 

song to an intruder than he does to a potential mate (Kroodsma et al., 1989; Lein, 

1978). Although most of the singing is done by males, females of some species do 

sing during agonistic encounters (e.g., Baptista et al., 1993; Falls and Kopachena, 

2010). Males typically choose a centrally located perch and sing loudly at regular 

intervals, making their presence known to would-be mates and intruders. In a 

now-classic study, Krebs (1976) showed that experimental removal of territorial 

male great tits (Parus major) resulted in rapid takeover of the vacated territories 

by other males; however, broadcasting a former resident’s song from a loudspeaker 

in his territory significantly delayed that takeover (see also Falls, 1988). 

Although most song is typically sung from a prominent perch in the center, it 

is also commonly used near territory boundaries, particularly directed at neighbors, 

as the territory is established. Males learn to recognize their neighbors’ 

songs and will tolerate them at a distance; however, hearing an unfamiliar song 

will generally trigger an investigation and aggressive response (Falls, 1969; 

Goldman, 1973, Krebs, 1971; Kroodsma, 1976). 

In addition to song, territorial sparrows are likely to exhibit a number of 

other displays during territory establishment and maintenance. Birds of both 

sexes may puff out their feathers, in particular raising those on the head to form a 

crest, or quiver their wings while pointing a closed bill at the intruder 

(Elekonich, 2000; Nice, 1943). They may peck furiously at nearby objects. If 

the intruder is unfazed, the resident then resorts to more direct physical threats, 

flying directly over the intruder, chasing him, and eventually attacking him. 

Opponents may fly at each other with feet stretched forward and may even fall to 

the ground as they engage and struggle. Physical fights are rare, however, and 

generally limited to the early breeding season before territory boundaries are 

firmly established. 

Territorial responses can be studied in the field by observing naturally 

occurring behavior or by staging a “simulated territorial intrusion” (STI). In this 

procedure, experimenters place a decoy “intruder,” often accompanied by song


played through a loudspeaker, onto a resident’s territory; the resident’s behavioral 

response is then quantified. Taxidermic or painted models may be used as decoys, 

or a live, unfamiliar male in cage may be presented. The most robust responses are 

obtained by presenting both decoy and recorded song so that the resident receives 

both visual and auditory cues (Wingfield and Wada, 1989). The behavioral data 

that are collected typically include latency to respond, songs, flights directed at 

the decoy threat displays (e.g., wing quivers), distance from the decoy at the 

closest approach, and the time spent within a certain distance, for example 5 m, 

of the decoy (Wingfield, 1984b, 1985; Wingfield and Hahn, 1994). 

B. Hormones and territoriality 

In the 1970s and 1980s, John Wingfield and Donald Farner revolutionized the 

study of behavior in songbirds by developing methods to measure gonadal 

hormones in small plasma samples collected from free-living individuals 

(Wingfield and Farner, 1976). The ensuing research in “field endocrinology” 

(Wingfield et al., 1990; Walker et al., 2005) elucidated patterns of gonadal 

hormone secretion over the reproductive cycle in a wide variety of avian species. 

In general, the stages of breeding associated with high levels of aggression 

coincide with high plasma levels of T. In song sparrows, for example T peaks 

during territory establishment when agonistic encounters are most frequent 

(reviewed by Wingfield et al., 2001), rises again during egg-laying, and slowly 

declines until the incubation phase when territory disputes are rare (Fig. 5.1A). 

In some multiple-brooded species, for example house sparrows (Passer domesticus), 

competition for nest holes appears to drive an increase in plasma T during 

each egg-laying period (Hegner and Wingfield, 1986; Fig. 5.1B). 

The temporal correlation between high plasma T and territorial behavior 

suggests that the two are related, and experimental manipulation of either T 

or the competitive environment shows that the relationship is bidirectional. 

Male song sparrows implanted subcutaneously with T-filled silastic capsules 

during territory establishment showed a more aggressive response to STI than 

males given empty capsules, and won territories that were twice the size 

(Wingfield, 1984b,c). Perhaps more interesting, however, was the effect on 

these males’ neighbors. The residents occupying territories adjacent to the 

treated males also showed increases in plasma T, suggesting that having to 

defend their territories against their more aggressive, T-treated neighbors stimulated 

HPG activity. In a separate study, male song sparrows were removed from 

their territories, allowing new residents to take over. In this case, both the new 

residents and their neighbors experienced high T levels compared with unmanipulated 

controls (Wingfield et al., 1987). Together, these studies show not only 

that T increases aggression, but also that engaging in agonistic encounters 

increases plasma T. The HPG response is rapid; plasma T rises significantly


A 

Song sparrow 

monogamous 

Prebreeding 

Sexual 

Parental 

Plasma level of testosterone 

B 

Prebreeding 

House sparrow 

monogamous 

Sexual 

Parental 

Sexual 

Parental 

Sexual 

Parental 

C 

Red-winged blackbird 

polygynous 

Prebreeding 

Breeding 

Figure 5.1. Plasma testosterone (T) profiles over the breeding season in males of three passerine 

species. (A) In song sparrows, T peaks during territory establishment (prebreeding) and 

again during laying of the first clutch when females are receptive (sexual), and then falls 

during incubation and feeding (parental). (B) In house sparrows, T peaks during periods 

of intense competition for nest sites, prior to each of multiple broods. (C) In red-winged 

blackbirds (Agelaius phoeniceus), males provide little parental care and spend more time 

on territorial defense; T remains relatively high until the end of the breeding season. 

Redrawn from data in Wingfield (1984a) and Hegner and Wingfield (1986). 

within 10 min of STI onset in male song sparrows (Wingfield et al., 1987) and 

can remain high for several days. This prolonged hormonal response probably 

heightens vigilance in anticipation of a sustained challenge (Wingfield, 1994a).

C. Aggression outside the breeding season 

In seasonally breeding birds, the gonads regress and become quiescent during the 

nonbreeding season. A testis that measures more than 10 mm across during 

breeding may shrink to less than 1 mm in the fall. Ovaries likewise regress such 

that follicles are barely visible. As a result, plasma levels of gonadal steroids fall 

to low or even nondetectable levels (Wingfield and Farner, 1993). The gonads 

remain in this state until the long days of spring stimulate photoreceptors in 

the mediobasal hypothalamus, triggering HPG hormone secretion and gonadal 

recrudescence (reviewed by Dawson et al., 2001). 

For many species, the fall in plasma gonadal steroid levels at the end of 

the breeding season coincides with abandonment of breeding territories and the 

onset of flocking behavior. For others, quiescence of the HPG axis does not seem 

to affect territorial behavior at all. Both of these scenarios are considered below. 

1. Aggression in flocks 


In species that do not defend territories year-round, the conclusion of territoriality 

each year may give rise to flocking behavior. In flocks, birds maximize foodfinding 

while minimizing predation risk (Hamilton, 1971). Competition for food, 

roosting sites, and other resources within flocks creates many opportunities for 

agonistic interactions, and some of the same behaviors used to defend territories, 

for example, song and threat displays, are also seen in this context. Other 

common aggressive displays in flocks include displacements, wherein one individual 

approaches another and causes it to move away, and hold-offs, wherein an 

individual refuses to be displaced. Each of these behaviors is easily observed in 

free-living groups, for example, in the vicinity of a popular food source (e.g., 

Ficken et al., 1978; Harrington, 1973; Rohwer and Rohwer, 1978), or in captivity 

(e.g., Schlinger, 1987; Watt, et al., 1984). 

In some species, winter flocks adopt a highly organized social structure. 

Many of us are familiar, for example, with the dominance hierarchies, or “pecking 

order,” established by chickens (Gallus gallus domesticus; Allee, 1936, 1942). 

Similar social arrangements have been observed in wild and captive groups of 

sparrows, for example, dark-eyed juncos (Junco hyemalis; Sabine, 1959), whitethroated 

sparrows (Schneider, 1984; Watt et al., 1984), Harris sparrows (Zonotrichia 

querula; Rohwer, 1975) and to a lesser extent, song sparrows (Nice, 1943). 

Within a group, each pair of individuals has a stable relationship such that one is 

dominant to the other. The subordinate will allow the dominant to displace it, 

deferring access to resources, and the dominant is unlikely to tolerate the close 

proximity of the subordinate. When all members of the group are considered 

together, there is in most cases a linear order of dominance; in other words, there 

is an alpha bird that dominates all others, a beta that dominates all but the alpha, 

and so on down to a bird that is subordinate to all. Exceptions, such as triangular


relationships, are fairly common. Reversals, in which the hierarchy is challenged 

and altered, do occur, but overall the arrangement is fixed and stable (Sabine, 

1959). In abiding by this social structure, the members of the group avoid the 

potential injuries and high energy expenditure that would result from constant 

aggressive encounters; when the hierarchy is stable, actual fighting is extremely 

rare. Only newcomers are subject to aggressive behavior, which subsides as they 

are assimilated into the group and assume a fixed rank (Tompkins, 1933). 

Whereas physical contact and escalated fights are not normally required 

for the maintenance of a stable hierarchy, its initial establishment is associated 

with frequent aggressive interactions. When unfamiliar birds are forming a 

group, or when newcomers arrive, rank is settled by the outcome of agonistic 

encounters. Age and sex can predict rank in some cases. For example in whitecrowned 

sparrows and related species, males tend to dominate females and older 

birds dominate younger ones such that the hierarchy within a group follows the 

general rule: adult males>adult females>immature males>immature females 

(Keys and Rothstein, 1991). In some species, such as house sparrows and Harris 

sparrows, plumage characteristics can predict rank; dominant individuals have 

dark “bibs” that appear to serve as status signals (Møller, 1987; Rohwer, 1975). 

Manipulation of bib coloration does not, however, alter status; rather, it results in 

heightened aggression toward the altered individuals, whose new plumage coloration 

is inconsistent with their behavior (Rohwer and Rohwer, 1978). 

The relationships between dominance rank and HPG function have 

been explored in many species of birds. This body of work, which spans almost 75 

years, collectively shows that dominance rank is predicted by plasma T levels 

only in groups that are newly forming. In other words, when unfamiliar birds 

come together to form a social group, their T levels during the establishment of 

the hierarchy contribute toward their eventual rank. Later, after the hierarchy is 

settled and stable, rank is unrelated to plasma T (Baptista et al., 1987; Buchanan 

et al., 2010; Chase, 1982; Ramenofsky, 1984; Schlinger, 1987; Wiley et al., 1999). 

Given that engaging in aggressive behavior causes T to rise (Wingfield 

et al., 1987), we must ask whether high T leads to the acquisition of a high rank, 

or vice versa. Some authors have reported that short-term treatment with 

exogenous T can alter stable hierarchies; the newly acquired ranks were maintained 

in white-crowned sparrows (Baptista et al., 1987) and domestic hens 

(Allee et al., 1939) but not Japanese quail (Coturnix coturnix japonica; Selinger 

and Bermant, 1967). In the majority of such studies, T treatment affects eventual 

rank when it is done early during hierarchy establishment. After rank is stable, 

however, rank is usually unaffected by T administration (Buchanan et al., 2010; 

Crook and Butterfield, 1968; Lumia, 1972; Mathewson, 1961; Rohwer and 

Rohwer, 1978; Wiley et al., 1999). The lack of an effect of T treatment on 

established, stable ranks has been attributed to learning, or “social inertia” 

(Guhl, 1968; Wiley et al., 1999), in groups of individuals that are familiar with


each other. In house sparrows, which do not defend large breeding territories, 

dominance rank during the nonbreeding season is determined largely by rank at 

the end of the breeding season when plasma T level is falling (Buchanan et al., 

2010). In other words, winners stay winners and losers stay losers (Chase, 1982). 

HPG activity during the breeding season may therefore contribute toward rank 

during the nonbreeding season. During both times of year, actual physical aggression 

is limited to periods of instability during which high-ranking positions up for 

grabs or otherwise in dispute. After the establishment of social relationships and 

boundaries, physical aggression is rare and plasma levels of T are much lower. 

2. Territoriality in the nonbreeding season 

Song sparrows in resident populations, despite being seasonal breeders that 

undergo gonadal regression in the fall, can maintain essentially the same 

territories year-round. Whereas the song sparrows studied by Wingfield in 

New York State (e.g., Wingfield, 1984a,b,c, 1985) abandon their territories 

and migrate at the conclusion of the breeding season, populations in Western 

Washington remain on the same territories, molt their feathers, and then, 

despite having completely regressed gonads and nondetectable levels of T, 

resume territorial defense (Wingfield and Hahn, 1994). Furthermore, young 

males just hatched the previous spring can establish new territories in the fall 

without an increase in T. STI during the fall induces the same behavioral 

responses as in spring, but without an accompanying HPG response (Soma and 

Wingfield, 2001; Wingfield and Hahn, 1994), and castration does not interfere 

with the ability to maintain a territory (Wingfield, 1994b). These results led to 

the hypothesis that territorial aggression and gonadal steroid secretion can 

become uncoupled in this and other species that defend territories outside 

the breeding season. 

To address this question, Soma et al. (1999, 2000a,b) tested whether T 

action is necessary for autumnal aggression in a population of song sparrows in 

Western Washington. To block the effects of T, they administered androgen 

receptor antagonists and, because T can also act via conversion to estradiol (E2), 

blockers of that conversion. They found that blocking the action of aromatase, 

an enzyme that converts T to E2, reduced territorial aggression even in the fall 

when plasma levels of gonadal steroids are naturally very low. This result 

suggested that autumnal aggression is not in fact independent of steroid hormones. 

This reduction was reversed by treatment with E2 (Soma et al., 2000a). 

Because gonads are not required for autumnal territorial defense 

(Wingfield, 1994b), the E2 that drives this behavior must come from a nongonadal 

source. One such source may be the brain itself, which contains high 

levels of aromatase. In song sparrows, aromatase mRNA is expressed in the brain 

at all times of year (Soma et al., 2003; Wacker et al., 2010) suggesting a possible


source of E2 available to brain tissue year-round. Aromatase activity in the 

ventral telencephalon, which contains the putative avian homologue of the 

amygdala, is reduced during molt, at which time aggression is also low (Soma 

et al., 2003). Brain-generated E2 may thus be an important regulator of territorial 

aggression in this species. To synthesize E2, the brain may make use of androgen 

precursors from regressed gonads or the adrenals (see Soma, 2006; Soma et al., 

2008 for reviews). Alternatively, some regions of the brain contain all of the 

enzymes necessary to synthesize E2 de novo from cholesterol substrate (reviewed 

by Soma et al., 2008; Remage-Healey et al., 2010), obviating the need for a 

peripheral steroid synthesis altogether. The regions of the brain important for 

aggressive behaviors, for example the nuclei that control singing behavior, are 

rich in these enzymes (Remage-Healey et al., 2010). Aromatase expression is 

high in the ventromedial nucleus of the hypothalamus (VMH) during all times of 

year except during molt, when aggression is virtually absent (Wacker et al., 

2010). In mice, distinct populations of VMH neurons contribute to fighting 

and mating behavior (Lin et al., 2011). In Section III, we will explore further 

the role of this region in aggression in songbirds. 

Like androgen release from the gonad, E2 synthesis by the brain appears to 

be behaviorally regulated. Remage-Healey et al. (2008)recently showed that in 

zebrafinches(Taeniopygia guttata), hearing conspecific song increases E2 concentrations 

in the auditory forebrain within minutes. Pradhan et al. (2010)showed 

subsequently that in nonbreeding, territorial song sparrows, exposure to STI rapidly 

increases activity of 3b-hydroxysteroid dehydrogenase, an enzyme necessary to 

synthesize E2 from androgen precursors. These findings demonstrate that the steroid 

environment within the brain is dynamic, sensitive to the social environment, and 

more independent of the gonad than previously thought. These discoveries of 

socially regulated, brain-generated steroid synthesis challenge the traditional view 

of hormone-mediated aggression and highlight the importance of songbird models 

to our understanding of how steroids regulate gene activity in the brain. 

Forty years of research on free-living sparrows has shown that aggression 

depends on steroid hormones. Even when at first glance it appears that aggression 

and steroid hormones have come “uncoupled,” for example, when resident song 

sparrows vigorously defend territories despite low plasma T, the evidence shows 

that low levels are necessary for the expression of territoriality and that the brain 

itself may produce sufficient amounts. The role of steroid hormones, particularly 

E2, in aggression seems very similar to their role in sexual receptivity (reviewed 

by Maney, 2010): plasma levels need not be high, and in fact seasonal peaks in 

plasma levels need not be associated in time with the behavior. A low level, 

however, is required for the behavior to be expressed. Because the frequency of 

aggressive behavior is clearly not always correlated directly with plasma levels of 

steroid hormones, it is possible that the hormones play a priming, or permissive, 

role and that other hormones or neurotransmitters are also important.


D. Evolution of aggression and life history strategies 

Research on wild songbirdshasdemonstrated a robust, two-wayrelationship between 

aggression and HPG activity. What does that finding tell us about the evolution and 

genetic control of these behaviors Because steroid hormones affect suites of behaviors, 

not just aggression, it is helpful to think about this issue in terms of behavioral 

strategies. As discussed in Section I above, investment in territory defense and matefinding 

defines a strategy at one end of a behavioral continuum, with investment in 

survival and parenting at the other (Trivers, 1972). This trade-off appears to be 

mediated, at least in part, by HPG activity (Ketterson and Nolan, 1994; McGlothlin 

et al., 2007; Wingfield et al.,1990).In specieswith maleparentalcare,Tis high during 

territory establishment but falls during the parental phase (Fig. 5.1A, B). Exogenous 

administration of T during the parental phase inhibits parental behavior and 

increases territorial behavior (Hegner and Wingfield, 1987; Schoech et al., 1998; 

Silverin, 1980). In species without male parental care, for example polygynous 

species in which females do the bulk of the care, T remains high in males for the 

duration of the season (Fig. 5.1C). In a study by Wingfield (1984c), T treatment of 

male song sparrows not only reduced parental care but also induced polygyny in this 

normally monogamous species. These males spent much of their time singing and 

acquired huge territories, attracting multiple females. Their failure to provision the 

young, however, likely reduced their overall reproductive success (Hegner and 

Wingfield, 1987; Silverin, 1980). Alterations in HPG function could therefore result 

in large, cascading effects and make an important contribution to variation in social 

behavior and social strategies (Ketterson and Nolan, 1992; Sinervo and Svensson, 

2002). When the effects of a hormone are antagonistic with respect to behavior, for 

example, in the case of T and parenting versus aggression, “antagonistic pleiotropy” 

can give rise to behavioral trade-offs (Finch and Rose, 1995). We hypothesize that 

suites of related genes, the expression of which is tightly governed by social cues, may 

act hierarchically to organize and regulate the hormonal and neural systems that 

promote territorial aggression and reduce parental behavior. In the next section, we 

explore the neural circuits that are involved and consider how evolution has shaped 

them in species with different behavioral strategies. 

III. TRANSCRIPTIONAL ACTIVITY AND NEURAL MECHANISMS 

OF AGGRESSION IN BIRDS 

A. Transcriptional traces of aggression reveal ubiquitous 

vertebrate themes 

Although it has long been known that all vertebrates share some basic features in 

the organization of the amygdala, hypothalamic nuclei, and associated (limbic) 

areas of the basal forebrain and midbrain, the extent of these similarities has


become much more clear in the past 10 years as investigators have combined 

genomic data with conventional neuroanatomical and functional approaches 

(e.g., using lesions and pharmacological manipulations). We now know that 

birds and rodents exhibit extraordinary similarities in the organization of limbic 

brain areas (Goodson, 2005; Newman, 1999), including distinct homologies at 

the subnuclear level (e.g., Goodson et al., 2004a; Kingsbury et al., 2011) and very 

specific similarities in the topographical patterns of transcriptional response to 

aggressive interactions (and other social interactions, as well), as established 

through the experimental induction of immediate early gene (IEG) transcripts 

and their protein products (Ball and Balthazart, 2001; Goodson, 2005). The IEGs 

most commonly used for such functional studies are c-fos and a gene variably 

known as zif-268, egr-1, NGFI-A, krox-24,orZenk (the latter being a name often 

used in birds as an acronym for the other four names; Mello et al., 1992). 

Experimentally induced increases in IEG mRNA can be detected by 

in situ hybridization (ISH) within 15–30 min. For detection of IEG proteins 

by immunocytochemistry (ICC), most investigators harvest brain tissue 

60–90 min after the experimental manipulation, such as an aggressive interaction. 

Because the induced IEG proteins are still elevated at 90 min and two halflives 

of the protein have passed (Herdegen and Leah, 1998), it is possible to 

determine whether the experimental manipulation may have decreased IEG 

activity from control levels (e.g., Bharati and Goodson, 2006; Goodson and 

Wang, 2006). Most behavioral neuroscientists are primarily interested in IEGs 

not because of what they do inside the cell, but rather because they provide a 

proxy marker to indicate that a cell has responded in some way to a stimulus. 

That response may or may not be associated with action potentials and release of 

neurochemicals (Herdegen and Leah, 1998), but by labeling for IEG transcripts 

and proteins, investigators can gain a good idea about the functional properties of 

different brain areas or cell groups. The actual molecular functions of IEGs are 

varied, but typically include the regulation of other genes involved in experience-dependent 

neuroplasticity (Herdegen and Leah, 1998; Mello and Ribeiro, 

1998), and thus IEGs probably have the ultimate effect of changing the way that 

cells function and behave during subsequent behavioral interactions. 

In rodents, resident–intruder encounters induce IEG activity in a characteristic 

pattern that includes the medial amygdala (MeA), medial bed nucleus 

of the stria terminalis (BSTm, a component of the medial extended amygdala 

that shares many anatomical and functional properties with the MeA), anterior 

hypothalamus (AH), ventrolateral lateral septum (LS), ventrolateral subdivision 

of the ventromedial nucleus of the hypothalamus (VMHvl; or lateral VMH in 

hamsters), dorsal premammillary nucleus, and the dorsal midbrain periaqueductal 

gray (Kollack-Walker et al., 1997; Motta et al., 2009). Notably, along with the 

medial preoptic area, these same brain areas are central to the regulation of most 

other social behaviors, including communication behaviors, parental care, pair


bonding, appetitive and consummatory sexual behavior, juvenile play, social 

recognition, and both same-sex and opposite-sex affiliation (Goodson, 2005; 

Newman, 1999). Despite the similarities, the relative amount of IEG activity 

across the different nodes of this “social behavior network” is distinctive for each 

social context, suggesting that functional relationships across the network nodes 

are dynamic and context-specific. Distinct patterns of correlated activity between 

network nodes in different social contexts have now been demonstrated in 

multiple vertebrate classes (Crews et al., 2006; Hoke et al., 2005; Yang and 

Wilczynski, 2007). 

The areas comprising the social behavior network are readily identified 

in birds and are anatomically and functionally conserved across amniote vertebrates, 

and in fact, the basic features of this network are present even in fish 

(Goodson, 2005; Goodson and Bass, 2002). Consistent with this conservation, 

territorial songbirds housed in captivity exhibit a pattern of IEG activity after 

STI that is virtually identical to the pattern described for rodents after a 

resident–intruder encounter (Goodson and Evans, 2004; Goodson et al., 

2005b). This work has been conducted in animals housed in their natural 

habitat, and data for catecholaminergic midbrain areas are even available from 

animals occupying natural territories (Maney and Ball, 2003). In addition, 

following exposure to same-sex conspecifics through a wire barrier in a quiet 

room (which elicits very little overt behavior), territorial finches exhibit relatively 

greater Fos and/or egr-1 responses than do gregarious species in a pattern 

similar to aggressive encounters (Goodson et al., 2005a). Hence, at least to an 

extent, the IEG activity of these brain areas reflects perceptual or motivational 

processes, not simply activation of aggression. 

Although it is intuitive to interpret IEG induction as reflecting a 

positive relationship between a brain area and behavior, negative correlations 

between IEG cell counts and aggressive behavior are observed for multiple brain 

areas. These include the AH, both pallial and subpallial subdivisions of the LS, 

and the paraventricular nucleus of the hypothalamus (PVN; Fig. 5.2; Goodson 

et al., 2005b). This pattern of results suggests that aggression is under inhibitory 

control, at least by some areas. Consistent with this idea, lesions of the LS 

increase resident–intruder aggression in male field sparrows and pigeons 

(Columba livia; Goodson et al., 1999; Ramirez et al., 1988). Note, however, that 

such effects are not observed in some contexts, such as aggressive competition for 

mates in male zebra finches, a highly gregarious species (Goodson et al., 1999). 

The PVN is heavily interconnected with the social behavior network 

and plays an important role in the regulation of autonomic and pituitary activity 

in relation to behavioral state. A subset of cells in the PVN produce arginine 

vasotocin (VT; homologue and evolutionary precursor of mammalian arginine 

vasopressin, VP), and the percentage of those cells that express Fos is also 

negatively correlated with aggressive response to an STI in male song sparrows


In contacts 

In contacts 

In contacts 

A 

B 

6 

6 

6 

LSc.v 

LSc.d 

5 

r = -0.571 LSc.vl 

5 

r = -0.688 5 

r = -0.534 

P = 0.020 

P = 0.003 

P = 0.033 

4 

3 

2 

1 

0 

-1 

4 

3 

2 

1 

0 

-1 

4 

3 

2 

1 

0 

-1 

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 

D 

Fos-ir nuclei/100 mm 2 Fos-ir nuclei/100 mm 2 Fos-ir nuclei/100 mm 2 

E 

F 

6 

6 

6 

PVN 

5 

r = -0.632 AH LSr 

5 

r = -0.478 5 

r = -0.530 

P = 0.008 

P = 0.060 

P = 0.034 

4 

4 

4 

3 

3 

3 

2 

2 

2 

1 

1 

1 

0 

0 

0 

-1 

-1 

-1 

0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 2 4 6 8 10 

Fos-ir nuclei/100 mm 2 Fos-ir nuclei/100 mm 2 Zenk-ir nuclei/100 mm 2 

G 

H 

I 

6 

6 

6 

LSc.vl 

5 

r = -0.693 LSc.l PVN 

5 

r = -0.551 5 

r = -0.573 

P = 0.002 

P = 0.026 

P = 0.020 

4 

4 

4 

3 

3 

3 

2 

2 

2 

1 

1 

1 

0 

0 

0 

-1 

-1 

-1 

0 2 4 6 8 10 0 2 4 6 8 10 0 2 4 6 8 10 

Zenk-ir nuclei/100 mm 2 Zenk-ir nuclei/100 mm 2 Zenk-ir nuclei/100 mm 2 

Figure 5.2. (A–E) Correlations between aggressive behavior and Fos-immunoreactive (-ir) cell 

counts in the subpallial (ventral, ventrolateral) and pallial (dorsal) zones of the caudal 

lateral septum (LSc.v, LSc.vl, and LSc.d; A–C, respectively), paraventricular hypothalamus 

(PVN; D), and anterior hypothalamus (AH; E) of male song sparrows exposed to 

STI (n¼16). The intruder’s cage and a speaker broadcasting song were placed adjacent 

to the subject’s cage. Subjects showed selective flights to the cage wall adjoining the 

intruder, providing a good measure of aggressive response. Data are shown as the natural 

log (ln) of the number of contacts with the wire barrier during a 10-min test. (F–I) 

Correlations between barrier contacts and Zenk-ir cell counts in the rostral LS (LSr; F), 

LS.vl (G), lateral zone of the LSc (LSc.l; H), and PVN (I). Cell counts are shown as the 

number of immunoreactive nuclei per 100 mm 2 . Modified from Goodson et al. (2005b). 

C


In contacts 

6 

5 

4 

3 

2 

1 

0 

-1 

0 

5 

r 2 = 0.305 

p = 0.026 

10 15 20 25 30 35 

%VT-ir neurons Fos-ir+ 

Figure 5.3. The percentage of arginine vasotocin (VT) neurons in the PVN that express Fos after a 

10-min STI is negatively correlated with aggression (ln, the number of contacts with the 

cage wall adjoining the intruder’s cage; see Fig. 5.2 caption; n¼16) in song sparrows. 

Modified from Goodson and Kabelik (2009). 

(Fig. 5.3; Goodson and Kabelik, 2009). VT and VP are secretagogues for adrenocorticotropic 

hormone, and thus the lower IEG activity of the PVN VT cells 

in more aggressive males likely reflects a lower stress response to the encounter. 

Virtually identical results for VP–Fos colocalization are obtained in lab mice (Ho 

et al., 2010). As addressed in Section III.B below, this negative relationship 

between aggression and VT–Fos colocalization in the PVN accurately predicts 

pharmacological effects that vary in relation to the subject’s dominance status 

(Goodson et al., 2009b). 

B. Neurochemistry and major modulators 

Although territorial aggression in birds has been the focus of hundreds of studies, 

including many that address proximate endocrine mechanisms (Goodson et al., 

2005c; Konishi et al.,1989), a surprisingly small number of experiments have been 

conducted with the goal of delineating relevant neurochemical circuits in the 

brain. An early study of whole-brain neurochemistry shows that dopamine, norepinephrine, 

and acetylcholine are all associated with aggressive behavior in male 

Japanese quail (Edens, 1987), and catecholaminergic midbrain nuclei show 

increased IEG activity in response to STI in song sparrows (Maney and Ball, 2003). 

Following aggressive competition for a potential mate, male zebra 

finches exhibit significant increases in the percentages of tyrosine hydroxylase-ir 

(TH-ir) cells expressing Fos within the “retrorubral” area (A8), substantial nigra 

(A9), ventral tegmental area (VTA; A10), and midbrain central gray (A11), but 

show a significant decrease in TH–Fos colocalization within the A12 neurons of 

the tuberal hypothalamus (Bharati and Goodson, 2006). TH is the rate-limiting


enzyme for catecholamine synthesis, and all of the cell groups just listed are 

known to be dopaminergic. Despite these results, treatments with quinpirole, a 

dopamine D2 receptor agonist, significantly decrease aggression during mate 

competition. D1 and D4 agonists are without effect, although a modest inhibition 

is observed with the D3 agonist 7-OH-DPAT, which may reflect weak 

binding to the D2 receptor (Kabelik et al., 2010). These seemingly contradictory 

results likely reflect the fact that courtship is displayed at a high rate during the 

competition tests, and given that TH–Fos colocalization in the central gray and 

caudal VTA correlates positively with courtship singing (Goodson et al., 2009a), 

the increased colocalization of TH and Fos following mate competition is likely 

attributable to directed singing and not the display of aggression. The number of 

TH-ir cells in the central gray also correlates positively with the average number 

of songs that male zebra finches sing to females during courtship tests. Notably, 

territorial finch species exhibit fewer TH-ir cells in the caudal VTA than do 

gregarious species such as the zebra finch, although this may reflect a lower level 

of affiliation rather than a negative relationship between this cell group and 

aggression (Goodson et al., 2009a). 

Dopaminergic mechanisms of song have also been examined in European 

starlings (Sturnus vulgaris), which sing in the context of breeding both to 

attract females and to repel other males. Antagonism of D1 receptors decreases 

song in breeding-condition males, whereas a dopamine reuptake inhibitor facilitates 

it (Schroeder and Riters, 2006), and aggressive song correlates negatively 

with D1 receptor density in numerous areas, including the LS, BSTm, medial 

preoptic area, and central gray (Heimovics et al., 2009). 

The handful of other neurochemical manipulations that have been 

conducted in studies of avian aggression have focused on neuromodulators 

such as VT, vasoactive intestinal polypeptide (VIP), and endogenous opioids. 

Of these, the endogenous opioids have received the least attention, but are 

known to inhibit aggression in Japanese quail, at least partially via the delta 

receptor subtype (Kotegawa et al., 1997). These neuropeptides are each produced 

in multiple brain areas, and as suggested for VT, it may be the case that the 

different cell groups have divergent effects on behavior (a possibility that should 

also be considered in relation to the major neurotransmitters just discussed; 

Goodson and Kabelik, 2009). 

Both VIP and VT exert complex effects on aggression that likely reflect 

the modulation of stress- and anxiety-related processes. For instance, in territorial 

male field sparrows housed in aviaries placed in their natural habitat, 

intraseptal infusions of VT decrease aggression in resident–intruder tests, but 

selectively facilitate the spontaneous use of an agonistic song type during the 

dawn song period (Goodson, 1998a). No effects are observed for the multipurpose 

song type that is used to attract females, and VIP tends to exert an opposite 

pattern of effects (Goodson, 1998a,b). Interestingly, the VT and VIP systems in


the LS are both sensitive to sex steroids. Castration causes down- and upregulation 

of VT and VIP immunoreactivity, respectively, and T or E2 replacement 

reverses these effects (Aste et al., 1997; Panzica et al., 2001; Voorhuis et al., 1988; 

but see Wacker et al., 2008). The VT/VIP systems therefore represent a possible 

mechanism whereby gonadal steroids may modulate aggression. 

In order to determine whether VT modulates stress-related processes, 

and whether it does so in a manner that is integrated with its effects on agonistic 

behavior, Goodson and Evans (2004) examined Zenk responses to nonsocial 

stress alone (capture in an outdoor flight cage and restraint for intraventricular 

infusions), or the same nonsocial stressors followed by STI. These manipulations 

were conducted in male song sparrows housed in flight cages placed in their 

natural habitat. Subjects were infused with either vehicle or a VT V 1a receptor 

antagonist and were sacrificed at the completion of testing for immunolabeling of 

Zenk and VT. In some brain areas, nonsocial and social stimuli induced Zenk 

within the same subset of cells, which was discernable because (1) in vehicletreated 

animals, the nonsocial stressor induced a significant increase in Zenk-ir 

cell numbers, and subsequent exposure to the social challenge produced no 

further increase, but (2) blocking the Zenk response to handling with the V 1a 

antagonist revealed a sensitivity to the social challenge (i.e., by eliminating the 

ceiling effect). This “integrated” pattern of Zenk response was observed for 

numerous areas, including the AH, POA, lateral VMH, lateral BST, and most 

zones of the LS. Notably, in all of these cases, the antagonist exerted more 

pronounced effects in the subjects that were exposed to the nonsocial stress 

alone. However, in the BSTm and ventrolateral LS, Zenk responses to the social 

challenge were significantly greater than to the nonsocial stressor, even in 

vehicle-treated subjects, indicating that at least some cells in these areas are 

more selectively activated by social challenge. The BSTm showed particularly 

selective responses to the social challenge, which were completely blocked by 

the V 1a antagonist (Goodson and Evans, 2004). 

Unfortunately, VT-ir cells of the BSTm were not detectable in this study 

(these neurons are weakly immunoreactive in most vertebrates and may store 

little peptide relative to the amount being released), but the VT-immunoreactive 

neurons of the PVN showed significant responses to social challenge and, most 

interestingly, the VT–Zenk colocalization was reduced by the V 1a antagonist only 

in the animals exposed to the STI (Goodson and Evans, 2004). As assessed in a 

later study with more robust immunolabeling of VT, VT–Fos colocalization in the 

BSTm of male song sparrows is not increased by social challenge, whereas 

colocalization in the PVN is negatively correlated with aggression (Fig. 5.2; 

Goodson and Kabelik, 2009). 

In territorial estrildid finches, exposure to a same-sex conspecific 

through a wire barrier actually decreases VT–Fos colocalization in the BSTm, 

but the same manipulation increases VT–Fos colocalization in gregarious finch


species, and the territorial birds do show large increases in VT–Fos colocalization 

if they are reunited with their pair-bond partner. Conversely, socially induced 

VT–Fos colocalization in the BSTm is blocked in the gregarious zebra finch if the 

subjects are intensely subjugated by a dominant bird (Goodson and Wang, 

2006). Thus, the VT neurons of the BSTm exhibit an exquisite sensitivity to 

the valence of social stimuli, and more recent findings suggest that this valence 

sensitivity is not extended to nonsocial stimuli (Goodson et al., 2009c). 

The differential response profiles of the VT neurons in the BSTm and 

PVN may account for at least a portion of the context-specificity that is observed 

following central infusions of VT or V 1 receptor antagonists. For instance, in 

zebra finches, VT promotes aggression in the context of mate competition and a 

V 1a antagonist inhibits aggression (Goodson et al., 2004b). These effects are 

consistent with the observation that VT–Fos colocalization is increased in the 

BSTm during mate competition, but not in the PVN. Conversely, resident– 

intruder aggression is inhibited by VT infusions in territorial species, consistent 

with the negative correlation between aggression and VT–Fos colocalization in 

the PVN (Goodson and Kabelik, 2009; Goodson and Wang, 2006). The different 

effects on mate competition and resident–intruder aggression (or nest defense in 

zebra finches) can be observed in the same species (Goodson et al., 2009b; 

Kabelik et al., 2009), as shown for the territorial violet-eared waxbill (Uraeginthus 

granatina) inFig. 5.4A–B. However, in the violet-eared waxbill, males that are 

typically dominant do not show a behavioral response to the V 1a antagonist in 

standard resident–intruder tests whereas aggression is facilitated in subordinates 

(Fig. 5.4C; Goodson et al., 2009b). Thus, perhaps only the subordinate males 

activate the PVN VT neurons during aggressive encounters and this activation 

inhibits aggression. 

Figure 5.4. (A) Peripheral injections of a novel V1a antagonist that crosses the blood–brain barrier 

have no effect on resident–intruder aggression in male violet-eared waxbills that are 

aggressive and typically dominant, but aggression in the context of mate competition is 

significantly reduced by the antagonist in the same males (B). (C) In males that are 

typically subordinate, resident–intruder aggression is disinhibited by the same treatments. 

Modified from Goodson et al. (2009b).


The ability to label IEG products has provided immeasurable insight 

into the neural basis of aggression, allowing the identification and mapping of 

specific circuits that respond rapidly to social stimuli. Lacking until recently were 

powerful genomic methods necessary for a more complete understanding of the 

complex protein interactions involved in social responses. The sequencing of the 

zebra finch genome (Warren et al., 2010) has provided unprecedented insight 

into what happens inside the songbird brain during agonistic encounters. Using 

tools such as high throughput sequencing and microarray analysis, investigators 

can now look at the regulation of many hundreds of genes simultaneously. In a 

recent gene profiling study, Mukai et al. (2009) compared the expression of more 

than 11,500 different gene transcripts in free-living song sparrows responding 

either to STI or a control intrusion by a heterospecific. For behavioral manipulations 

conducted during the breeding season, 67 gene transcripts were differentially 

expressed in the hypothalamus following exposure to an STI compared to 

control. During the fall, when territorial aggression seems to be independent of 

gonadal steroid production (reviewed by Soma, 2006; Soma et al., 2008; see also 

Section II), 173 transcripts were affected (Mukai et al., 2009). There were 

significant interactions between season and STI for 88 transcripts (Mukai et al., 

2009), which may in part reflect the differential regulation of the pituitary– 

gonadal axis across seasons. The expression of many of the gene transcripts was 

not, however, affected by season and therefore may be important for the regulation 

of aggressive behavior itself rather than endocrine responses to aggressive 

encounters. This study represents the early days of genomic analysis of social 

behavior in free-living, natural populations and sets the standard for many more 

sure to follow. In the next section, we consider a songbird species that because of 

a natural genetic anomaly is becoming a popular model for studying the genetic 

mechanisms underlying aggression. 

IV. A NATURAL MODEL UNITING SOCIAL BEHAVIOR, HORMONES, 

AND GENETICS 

A. The white-throated sparrow 

The underlying genetic basis of variation in social behavior is of intense interest, 

yet only a handful of genes have been linked to specific social behaviors in 

vertebrates (reviewed by Robinson et al., 2005). Thus, there is an obvious need to 

identify populations, human or otherwise, in which there is clear linkage between 

genes and social behavior. A common wild songbird, the white-throated 

sparrow, offers such an opportunity. This species, in which socially monogamous 

pairs defend breeding territories, provision the young with food, and form flocks 

with stable dominance hierarchies in the winter, is a typical New World sparrow


in nearly all respects. What sets it apart from other songbirds is that it exhibits 

alternative phenotypes, defined by a plumage polymorphism, that differ in their 

social behavior. Both males and females can be categorized into one of two 

plumage morphs that differ primarily in the color of the crown stripes (Lowther, 

1961; Piper and Wiley, 1989; Watt, 1986; see Fig. 5.5). Behavioral studies 

conducted in the animals’ natural habitat have established that individuals 

with a white medial stripe (WS) on the crown engage in a more aggressive 

strategy, whereas birds with a tan medial stripe (TS) are more parental. 

The species represents a promising model in which to study the genetic 

basis of aggression because the plumage pattern segregates with the presence or 

absence of a structural rearrangement of chromosome 2. WS individuals are 

heterozygous for the rearranged chromosome (ZAL2 m ), whereas those of the TS 

morph are homozygous for the wild-type chromosome (ZAL2; Thorneycroft, 

1975). Once they molt into adult plumage the phenotype is fixed for the lifetime 

of the individual. Within a population, approximately half of the birds are WS 

(ZAL2/2 m ), whereas the other half are TS (ZAL2/2; Lowther, 1961; 

Thorneycroft, 1975). This balanced polymorphism is maintained in the population 

by disassortative mating—WS and TS birds nearly always mate with individuals 

of the opposite morph (Knapton and Falls, 1983; Lowther, 1961; 

Thorneycroft, 1975; Tuttle, 1993). This mating pattern results in a virtual 

absence of birds homozygous for ZAL2 m , a genotype that Thorneycroft (1975) 

hypothesized may be less viable due to recessive deleterious mutations. Of more 

than 1000 individuals genotyped, only one was found to be homozygous for 

ZAL2 m (Maney et al. unpublished data; Romanov et al., 2009; Thorneycroft, 

1975). 

Figure 5.5. Plumage polymorphism in white-throated sparrows. (A) Individuals of the white-stripe 

(WS) morph have alternating black and white stripes on the crown, bright yellow lores, 

and a clear white throat patch. (B) Individuals of the tan-stripe (TS) morph have 

alternating brown and tan stripes on the crown, duller yellow lores, and dark bars within 

the white throat patch. Photos by Allison Reid. Reprinted from Maney (2008).


The behavioral differences that segregate with the ZAL2 m chromosome 

have been well documented in field studies. Males and females of the WS morph 

are more aggressive, both in territorial defense and in mate-seeking, than their 

TS counterparts. WS males sing more in response to STI than TS males (Collins 

and Houtman, 1999; Kopachena and Falls, 1993a; Horton and Maney, unpublished 

observations) and are more likely to trespass onto the territories of other 

males (Tuttle, 2003). Whereas WS females sing and engage in active territorial 

defense independently of their mates, TS females do so only rarely (Kopachena 

and Falls, 1993a; Horton and Maney, unpublished observations). TS birds of 

both sexes feed young more often during the parental phase of the breeding 

season than do WS birds (Knapton and Falls, 1983; Kopachena and Falls, 

1993b). The relative strategies employed by the different morphs of this species 

therefore fall onto different ends of the behavioral continuum between territoriality 

and parenting (Trivers, 1972). 

B. Endocrine and neuroendocrine correlates of 

behavioral polymorphism 

Because the behavioral trade-off between territorial defense and parenting is 

clearly mediated at least in part by HPG activity in songbirds (Ketterson and 

Nolan, 1994; McGlothlin et al., 2007; Wingfield et al., 1990), we should immediately 

suspect that, in white-throated sparrows, HPG function may vary according 

to morph. Spinney et al. (2006) found that in free-living birds in breeding 

condition, WS males do have larger testes and higher levels of circulating T than 

TS males. This phenomenon has also been demonstrated in captive populations 

(Maney, 2008; Swett and Breuner, 2009). In both the field and the lab, however, 

the difference in plasma T disappears when birds are not in breeding condition 

(Maney, 2008; Spinney et al., 2006). Interestingly, morph differences in aggression 

appear only during the breeding season, mirroring the morph difference in 

circulating T. In winter flocks and in laboratory-housed birds held on short days, 

morph is not related to dominance rank or to aggression (Dearborn and Wiley, 

1993; Harrington, 1973; Piper and Wiley, 1989; Schlinger, 1987; Schwabl et al., 

1988; Watt et al., 1984; Wiley et al., 1999). In contrast, when birds are held on 

long days and undergo gonadal recrudescence, WS birds engage in significantly 

more aggression than their TS cage-mates and tend to outrank them (Fig. 5.6; see 

also Watt et al., 1984). Morph differences in dominance and aggression may 

therefore depend on season and thus perhaps on differences in HPG function. 

Because levels of gonadal steroids differ between the morphs, the 

behavioral polymorphism may be driven by the effects of these steroids on the 

brain. To evaluate this hypothesis, Maney et al. (2005) compared the morphs 

with respect to the VT and VIP neuropeptide systems, which are highly steroid 

dependent (Aste et al., 1997; Panzica et al., 2001; Voorhuis et al., 1988). WS birds


Figure 5.6. Medians, IQR, and ranges for (A) aggression scores (number of aggressive acts initiated 

per hour) and (B) individual ranks (as percent opponents dominated) within social 

groups. Males were introduced in single-sex groups of six birds (three WS and three TS 

per group) in indoor aviaries. Aggression scores and ranks were determined 10–14 days 

later by observing interactions and constructing dominance matrices. During spring-like 

day lengths (16L:8D), WS males were (A) more aggressive and (B) outranked TS males. 

Rank was unrelated to morph on short days (8L:16D). The long- and short-day experiments 

were conducted on different individuals. Data from Horton and Maney, 

unpublished. 

had higher levels of VT-immunoreactivity in the BSTm and ventrolateral LS 

than TS birds. Since T is higher in WS males, this result is consistent with the 

idea that T may be engaging the VT system in the LS. Central administration of 

VT in the closely related white-throated sparrow induces agonistic song (Maney 

et al., 1997), suggesting that engagement of this system may be directly related to 

aggressive behaviors. Central administration of VIP, in contrast, reduces agonistic 

song in field sparrows (Goodson, 1998a); immunoreactivity for this peptide 

was higher in the ventrolateral LS of the TS (less aggressive) morph. VIP 

immunoreactivity in this region is inversely proportional to T levels (Aste 

et al., 1997) again supporting a possible role for gonadal sex steroids in the 

control of aggression in this species.


C. Causality and “phenotypic engineering” 

Looking for morph differences in endocrine variables in unmanipulated individuals 

is an important endeavor, in that significant correlations can help illuminate 

possible physiological causes of aggression. Such correlations alone, however, can 

provide only limited information on causal mechanisms. The morph difference in 

plasma T, for example, could be a consequence, rather than a cause, of polymorphic 

behavior. Either scenario would explain the observed correlations between T and 

social behavior (Spinney et al., 2006). As discussed in Section II above, experiments 

involving manipulation of T or of social contexts in songbirds have revealed causal 

effects in both directions. Recall that in other songbird species, free-living males 

treated with T defend larger territories, engage in more aggression, acquire more 

mates, and provide less parental care than untreated males (Hegner and Wingfield, 

1987; Schoech et al., 1998; Silverin, 1980; Wingfield, 1984b,c). Territorial intrusion 

or the presence of receptive females, however, cause release of endogenous T 

(Dufty and Wingfield, 1986; Moore, 1983; Wingfield and Hahn, 1994; Wingfield 

and Monk, 1994). A one-way causal effect of T on aggression and parenting may 

not completely explain polymorphic behavior in white-throated sparrows. 

Some authors have suggested that the role of hormones in alternative 

phenotypes is best studied by performing hormonal manipulations, or “phenotypic 

engineering” (Ketterson and Nolan, 1992; Miles et al., 2007; Zera and Harshman, 

2001). To test whether morph-dependent variation in territorial behavior in male 

white-throated sparrows is attributable entirely to variation in T, Maney et al. 

(2009) eliminated morph differences in T and then compared WS and TS 

responses to STI in the lab. Males in nonbreeding condition received silastic 

implants containing T, so that plasma levels in the WS and TS groups were 

high and equal. When presented with audio playback of conspecific male song, 

WS males sang significantly more often than TS males. This result suggests that 

WS males respond more aggressively to a territorial challenge than TS males, even 

when T levels are experimentally equalized between the morphs. 

If morph differences in social behavior are not caused simply by differences 

in plasma T, then our search for causal factors should turn to other aspects of HPG 

function, for example, steroid binding or metabolism. The list of such factors is long 

and includes a large number of receptors, enzymes, and binding globulins. Comparative 

genomic approaches are required to conduct large-scale comparisons of gene 

expression as well as detailed analysis of the genetic differences between the morphs. 

D. Mapping the ZAL2 m 

The early genetic work in the white-throated sparrow, done more than 35 years 

ago (Thorneycroft, 1975), showed definitively that morph differences are associated 

with a clear, tractable chromosomal rearrangement. The ZAL2 m


chromosome thus offers a powerful starting point for understanding the mechanisms 

underlying aggressive behavior in birds and other vertebrates. In essence, 

nature has created a genetic manipulation that allows us to identify genes that 

are affected by the rearrangement and therefore potentially causal for heightened 

aggression in the WS individuals. 

The identification of such genes first requires mapping of the ZAL2 m 

rearrangement; genes that map within it can then be evaluated as likely candidates. 

Using a comparative genomic approach, Thomas et al. (2008) (see also 

Davis et al., 2011; Huynh et al., 2010a,b) began the initial modern genomic 

characterization of the ZAL2 m rearrangement. By taking advantage of the 

genomic resources available for two other avian species, the chicken and the 

zebra finch, they established a comparative map of ZAL2 m and found that the 

chromosome contains a complex rearrangement involving not one but at least 

two inversions around the centromere (Fig. 5.7). The two inversions may have 

occurred in succession, with the second completely contained within the first. 

Alternatively, ZAL2 and ZAL2 m may each represent rearranged versions of an 

ancestral chromosome 2, having undergone rearrangement at different times. 

The rearrangement now spans the majority of the chromosome and could 

contain as many as 1000 protein-coding genes (Davis et al., 2011; Thomas 

et al., 2008). Thus, although the region containing the rearrangement is large, 

this work has delineated a finite set of genes linked to the behavioral and 

plumage polymorphisms in this species. 

2 

Presumed 

ancestral/intermediate 

2 m 

Figure 5.7. Model for the ZAL2 m rearrangement. A minimum of two pericentric inversions, 

represented by the pairs of dashed lines, are hypothesized to have led to the ZAL2/2 m 

polymorphism. ZAL2 (top) and ZAL2 m (bottom) are shown along with a hypothetical 

chromosomal arrangement (middle) that could be either ancestral to both the ZAL2 

and ZAL2 m or an intermediate arrangement. Centromeres are represented by filled 

circles. Dark and light boxes represent segments originating on the short and long arms 

of the presumed ancestral chromosome, respectively. Free recombination between the 

ZAL2 and ZAL2 m is limited to the tip of the short arm (hatched boxes).


Exactly how does the architecture of ZAL2 m affect the expression of the 

genes inside the rearrangement and the proteins they encode Inversions are 

hypothesized to affect gene and protein function in two main ways. First, genes at 

or near the breakpoints may be physically disrupted or otherwise directly affected 

by the breakage and subsequent change in position. So far, sequencing efforts 

have identified no genes physically disrupted by the ZAL2 m breakpoints (Davis 

et al., 2011); however, position effects may have led to functionally distinct 

alleles for those nearby. For example, a cluster of genes encoding bitter taste 

receptors has been separated by one of the breakpoints and now maps to different 

arms of the chromosome (Davis et al., 2010). This separation, which appears to 

have led to nonsynonymous variants detected between the ZAL2 and ZAL2 m , 

may have implications for diet and habitat selection but is unlikely to explain 

morph differences in aggression and parenting. 

The behavioral polymorphisms in social behavior in this species are more 

likely related to a second important consequence of pericentric inversions, which 

is the suppression of recombination and subsequent genetic differentiation of the 

inverted region. Thorneycroft (1975) observed that pairing in the ZAL2/2 m 

bivalent during meiosis was limited to one arm of each chromosome. Cytogenetic 

mapping efforts (Davis et al., 2011; Thomas et al., 2008) suggest that single 

recombination events elsewhere in the chromosome would give rise to gametes 

with large duplications and deletions, thereby effectively preventing the inheritance 

of the recombined chromosomes. ZAL2 m may therefore be largely isolated 

from ZAL2. Population genetics studies have confirmed differentiation between 

the ZAL2 and ZAL2 m over the entire rearranged region as a result of suppression of 

recombination (Huynh et al., 2010a; Thomas et al., 2008). Alleles are shared 

between the haplotypes only at the tip of the short arm of ZAL2/2 m ,whichis 

outside the rearrangement (Fig. 5.7). The rearrangement itself contains a unique 

set of alleles that are not shared with ZAL2—an estimated 3000 fixed differences 

(Davis et al., 2011), and this set is inherited together. Thus, the lack of gene flow 

between the ZAL2 and ZAL2 m has provided opportunity for the evolution of 

functionally distinct alleles that are restricted to one arrangement or the other. In 

the continuing analysis of the rearrangement, we should expect to find a series of 

genes, inherited together as a unit in WS birds, that are functionally distinct from 

the ZAL2 alleles with regard to either their protein products or patterns of 

expression. Given the important role of the HPG axis in aggression in this and 

other species, the strongest candidates will be closely related to HPG function. 

V. FUTURE DIRECTIONS 

Genetic research with comparative models will ultimately show how key genes, 

the molecular functions of which are conserved across evolutionary divergence, 

relate to complex and highly derived social behaviors such as aggression.


The mechanisms that underlie social behaviors in less accessible species, such as 

humans, are best studied in species that live in societies, particularly those that 

can be studied in their natural habitats or under naturalistic conditions (Insel 

and Fernald, 2004). The existing database on avian social behavior is unparalleled—for 

example, for over 4000 species, we know whether they are territorial 

or colonial, socially monogamous or polygynous, migratory, or sedentary. We 

have high-quality recordings of their vocalizations. No other group of animals, 

invertebrate or vertebrate, has been studied with such passion and intensity. 

This collective database, although it could provide profound insight into the 

neuroendocrine basis of diverse social behaviors, is underutilized by neuroscientists 

because the availability of genomic tools has, until recently, been limited. 

The recent sequencing of the zebra finch genome (Warren et al., 2010) now 

makes possible unprecedented advances in our understanding of social behavior 

because the resulting tools are applicable to all songbirds. 

Advances in genomic technology, together with conservation of underlying 

mechanisms, will make it more and more feasible to bridge from wellcharacterized 

data-rich lab organisms, such as mice, to phenomena-rich wild 

species. These species, which include fish, lizards, songbirds, and voles, are 

proving to be rich resources for the analysis of social behavior and for the 

development of general principles (Robinson et al., 2005). Studies with these 

model organisms have demonstrated the power of a comparative approach— 

looking for neural or genetic differences among individuals with known behavioral 

differences (Bullock, 1984; Robinson, et al., 2005). The songbird model is 

preferable to more typical laboratory species in the study of social behavior 

because of the greater parallels with humans regarding societal structures and 

hormonal bases of behavioral strategies, as well as the potential to study freeliving 

populations under natural conditions. Our work and that of others is 

making these natural and powerful models of vertebrate behavior feasible for 

genomic and neuroendocrine analysis. 


The authors thank Jim Thomas for his contributions to the work described in Section IV. The 

research from the authors’ labs was supported by NIH MH062656 to J. L. G., by NIH 

1R01MH082833-01, NIH 5R21MH082046-02, and NSF IOS-0723805 to D. L. M. and the Center 

for Behavioral Neuroscience. 

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6 

Genetics of Aggression in Voles 

Kyle L. Gobrogge 1 and Zuoxin W. Wang 

Department of Psychology and Program in Neuroscience, Florida State 

University, Tallahassee, Florida, USA 


II. The Prairie Vole Model 

III. Neural Correlates 

IV. Neural Circuitry 

V. Neurochemical Regulation of Selective Aggression 

A. Neuropeptides 

B. Dopamine 

C. Steroid hormones 

D. Classical neurotransmitters 

VI. Molecular Genetics of Selective Aggression 

VII. Drug-induced Aggression 

VIII. Conclusions and Future Directions 


References 

ABSTRACT 

Prairie voles (Microtus ochrogaster) are socially monogamous rodents that form 

pair bonds—a behavior composed of several social interactions including attachment 

with a familiar mate and aggression toward conspecific strangers. 

1 Present address: Department of Neurobiology, Harvard Medical School, Boston, 

Massachusetts, USA 



DOI: 10.1016/B978-0-12-380858-5.00003-4

122 Gobrogge and Wang 

Therefore, this species has provided an excellent opportunity for the study of pair 

bonding behavior and its underlying neural mechanisms. In this chapter, we 

discuss the utility of this unique animal model in the study of aggression and 

review recent findings illustrating the neurochemical mechanisms underlying 

pair bonding-induced aggression. Implications of this research for our understanding 

of the neurobiology of human violence are also discussed. ß 2011, Elsevier Inc. 


Mating induces aggression in several organisms throughout the animal kingdom. 

Within species, patterns of inter- and intrasexual aggression vary as a function of 

monogamy, parental investment, and group structure. In the wild, the appropriate 

coordination of social behavior is necessary for survival and reproductive 

success. How organisms make decisions about which behavior to display in the 

natural environment remains an important area of biological investigation. To 

address these questions, previous work has relied on using traditional laboratory 

rodents. However, these animals do not readily display certain types of social 

behaviors and thus are not appropriate for some investigations. For example, 

laboratory rats and mice do not exhibit strong social bonds between mates, and 

males typically do not display paternal behavior or female-directed aggression. 

Because mating naturally induces pair bonding, aggression, and biparental behavior 

in the socially monogamous prairie vole (Microtus ochrogaster), this 

species represents a unique animal model to study the underlying neural mechanisms 

regulating social behavior associated with a monogamous life strategy. 

In this chapter, we begin by describing the prairie vole model and 

reviewing the neural correlates of pair bonding behavior. We focus on the 

neuropeptides arginine vasopressin (AVP) and oxytocin; neurotransmitters dopamine 

(DA), gamma-aminobutyric acid (GABA), and glutamate; and steroid 

hormones testosterone and estrogen in the regulation of aggression. We highlight 

the molecular genetics underlying courtship and aggression associated with 

monogamous pair bonding in voles and humans. Finally, we speculate on the 

potential for translation, of aggression studies in prairie voles, for research 

examining the etiology of violence in human populations—with a particular 

emphasis on the interactions between drug abuse and social behavior. 

II. THE PRAIRIE VOLE MODEL 

Voles are microtine (Microtus) rodents that are taxonomically and genetically 

similar, yet show remarkable differences in their social behavior (Young and 

Wang, 2004; Young et al., 2008, 2011a). These animals have provided an

6. Genetics of Aggression in Voles 123 

excellent opportunity for comparative studies examining social behaviors associated 

with different life strategies. For example, prairie (M. ochrogaster) and pine 

(M. pinetorum) voles are highly social and monogamous, whereas meadow 

(M. pennsylvanicus) and montane (M. montanus) voles are asocial and promiscuous 

(Dewsbury, 1987; Insel and Hulihan, 1995; Jannett, 1982). In the laboratory, 

prairie and pine voles are biparental, with both parents equally caring for their 

young, while meadow and montane voles are primarily maternal and males do 

not stay in the natal nest after female parturition (McGuire and Novak, 1984, 

1986; Oliveras and Novak, 1986). Following mating, prairie voles develop pair 

bonds between mates (Fig. 6.1A; Young and Wang, 2004) and males even display 

aggression selectively toward conspecific strangers but not toward their familiar 

partner (Fig. 6.1B; Aragona et al., 2006; Gobrogge et al., 2007, 2009; Winslow 

et al., 1993)—behaviors that are not exhibited by promiscuous meadow or 

montane voles (Insel et al., 1995; Lim et al., 2004). Interestingly, these vole 

species do not differ in their nonsocial behavior (Tamarin, 1985), further 

indicating associations between species-specific social behavior and life strategy 

(Carter et al., 1995; Insel et al., 1998; Wang and Aragona, 2004; Young and 

Wang, 2004; Young et al., 1998). Therefore, prairie voles represent a unique 

model system to dissect the neural mechanisms underlying ethologically relevant 

social behavior. 

One behavioral index of pair bonding is selective aggression, which is 

more prominent in male than in female prairie voles. It has been suggested that 

selective aggression is a behavioral trait associated with mate guarding that is 

important for pair bonding (Carter et al., 1995). Selective aggression is studied 

using a resident–intruder test (RIT) (Fig. 6.1C; Gobrogge et al., 2007, 2009; 

Winslow et al., 1993; Wang et al., 1997a). A conspecific intruder is introduced 

into the male resident cage and their behavioral interactions are videotaped for 

5–10 min (Aragona et al., 2006; Gobrogge et al., 2007, 2009; Wang et al., 1997a; 

Winslow et al., 1993). Subject’s behavioral interactions with the intruder are 

recorded and the frequency of aggressive behaviors including attacks, bites, 

chases, defensive/offensive upright postures, offensive sniffs, threats, and retaliatory 

attacks are calculated as a composite score (Gobrogge et al., 2007, 2009) as 

well as the duration of affiliative side-by-side physical contact (Gobrogge et al., 

2007, 2009; Winslow et al., 1993). It is important to note that both offensive and 

defensive types of aggression are critical components of selective aggression in 

male prairie voles (Wang et al., 1997a; Winslow et al., 1993). 

Selective aggression is associated with mating, as cohabitation in the 

absence of mating does not induce this behavior in male prairie voles (Insel et al., 

1995; Wang et al., 1997a; Winslow et al., 1993). Selective aggression is also 

enduring (Aragona et al., 2006; Gobrogge et al., 2007, 2009; Insel et al., 1995) 

and lasts for at least 2 weeks after partner preference formation (Aragona et al., 

2006; Gobrogge et al., 2007, 2009), even in the absence of continuous exposure


A 

B 

C 

Contact time (min/3 h) 

D 

100 

80 

60 

40 

20 

0 

Partner 

Stranger 

6 h Cohab 

* 

24 h Mating 

Aggression (# attacks/10 min) 

E 

120 

80 

40 

0 

Naive 

a 

Stranger 

Paired 

a 

b 

Partner Stranger Stranger 

female male 

g 

Partner 

F 

Stranger 

Density Fos-ir (#/mm 3 ) 

2000 

1600 

1200 

800 

400 

0 

AH 

Partner 

Stranger 

* 

MeA 

* 

AH 

OT 

MeA 

AcA 

OT 

Figure 6.1. Neural correlates of selective aggression. (A) After 24 h, but not 6 h, of mating, male 

and female prairie voles display significantly more time in side-by-side physical contact 

with an opposite sex familiar partner than with a stranger. (B) Sexually naïve male 

prairie voles (Naïve) do not display aggression toward a stranger female, whereas 2 weeks 

of sexual and social experience (Paired) induces selective aggression toward both male 

and female strangers but not toward familiar female partners. (C) Photo depicts a pair 

bonded male prairie vole (left) preparing to attack a—sexually receptive—stranger 

female prairie vole (right). (D) Stereological estimates reveal a significantly higher 

density of Fos-ir cells in the anterior hypothalamus (AH) and medial amygdala 

(MeA) of pair bonded males displaying aggression toward a stranger female (Stranger) 

compared to males displaying affiliation toward their familiar female partner (Partner). 

(E) Photomicrographs showing Fos-ir (dark nuclear staining) in the AH and MeA from 

pair bonded males re-exposed to their familiar female partner (Partner) or to a stranger 

female (Stranger). F: fornix; OT: optic tract. Bars indicate meansstandard error of the 

mean. Bars with different Greek letters differ significantly from each other. *p


et al., 2007, 2009; Wang et al., 1997a). Together, these reliably expressed and 

measurable agonistic behaviors make the prairie vole an excellent model for 

investigation of the neural mechanisms underlying naturally occurring aggression 

associated with monogamy. It should be mentioned that although female 

aggression has been less studied in voles, female prairie voles exhibit similar 

aggressive behavior as males and this behavior is influenced by a female’s social 

and sexual experience (Bowler et al., 2002). 

III. NEURAL CORRELATES 

With considerable overlap of brain areas involved in several forms of social 

(Newman, 1999) and agonistic (Table 6.1) behaviors, there is a significant 

amount of ambiguity regarding which brain areas may be involved in the 

regulation of selective aggression. Using a neuronal activation marker of an 

immediate early gene, c-fos, previous studies in voles have examined neuronal 

Table 6.1. Summary of Brain Areas Implicated in Aggression 

Brain area Species References 

Anterior hypothalamus (AH) Human Sano et al. (1966), Ramamurthi (1988) 

Prairie vole Gobrogge et al. (2007, 2009), Gobrogge and 

Wang (2009) 

Rat 

Veening et al. (2005), Kruk (1991), Bermond 

et al. (1982), Kruk et al. (1984), Adams et al. 

(1993), Roeling et al. (1993), Haller et al. 

(1998), Veenema et al. (2006), Motta et al. 

(2009) 

Syrian hamster Delville et al. (2000), Ferris and Potegal (1988), 

Caldwell and Albers (2004), Ferris et al. (1997, 

1989), Albers et al. (2006), Harrison et al. 

(2000b), Jackson et al. (2005), Grimes et al. 

(2007), Ricci et al. (2009), Schwartzer et al. 

(2009), Schwartzer and Melloni (2010a,b) 

Lateral septum (LS) Rat Veenema et al. (2010) 

Medial amygdala (MeA) Human Ramamurthi (1988) 

Prairie vole Wang et al. (1997a), Gobrogge and Wang (2009) 

Rat Koolhaas et al. (1990) 

Nucleus accumbens (NAcc) Prairie vole Aragona et al. (2006) 

Ventromedial hypothalamus 

(VMH) 

Mouse Choi et al. (2005), Lin et al. (2011) 

Brain structures involved in aggression, across species, with corresponding references to ground 

brain area acronyms used throughout the chapter.


activity associated with aggression (Wang et al., 1997a), maternal (Katz et al., 

1999) and paternal behavior (Kirkpatrick et al., 1994), mating (Curtis and 

Wang, 2003; Lim and Young, 2004), anxiety (Stowe et al., 2005), spatial learning 

(Kuptsov et al., 2005), chemosensory processing (Hairston et al., 2003; Tubbiola 

and Wysocki, 1997), social experience (Cushing et al., 2003a; Kramer et al., 

2006), or pharmacological challenges (Curtis and Wang, 2005b; Cushing et al., 

2003b; Gingrich et al., 1997). Within these studies, however, typically only one 

type of behavior was investigated. Little focus was aimed at examining other 

forms of social behavior, including affiliation or general social olfactory processing. 

Consequently, there is considerable overlap in brain–behavior relationships 

among these studies leading to ambiguity as to which brain areas regulate 

selective aggression. Nevertheless, in an early study, male prairie voles displayed 

aggression toward a male intruder following 24 h of mating, but not following 

24 h of cohabitation with a female without mating (Wang et al., 1997a). 

However, despite their differences in sociosexual experience and in aggressive 

behavior, both types of male exposure led to equal levels of Fos-ir (immunoreactivity) 

expression in some brain areas, such as the bed nucleus of the stria 

terminalis (BNST). Males that mated for 24 h and displayed high levels of 

aggression toward either a male or a female intruder showed increased levels of 

Fos-ir expression in the medial amygdala (MeA; Wang et al., 1997a), compared 

to males that cohabitated with a female without mating, implicating the MeA as 

a brain area associated with the display of mating-induced selective aggression 

(Fig. 6.1D and E). 

In a more recent study, several brain areas including the BNST, medial 

preoptic area (MPOA), paraventricular nucleus (PVN), and lateral septum (LS) 

showed higher levels of Fos expression in pair bonded males that had experienced 

an RIT compared to pair bonded males not exposed to a social intruder 

(Gobrogge et al., 2007). However, no group differences in Fos expression across 

these brain areas were found among males that were exposed to different social 

stimuli or displaying different patterns of social behavior, including aggression or 

affiliation toward intruders. These data suggest that the increased neuronal 

activation in these brain regions is probably due to olfactory stimulation or 

general arousal associated with exposure to a conspecific, but such a response is 

nonselective. A unique pattern of Fos expression was found in the anterior 

hypothalamus (AH), in which exposure to a conspecific stranger, either male 

or female, induced a significant increase in AH-Fos over those reexposed to their 

familiar partner (Fig. 6.1D and E; Gobrogge et al., 2007). This increase in Fos 

staining may indicate a stimulus-specific response. The AH appears to be more 

responsive to chemosensory, tactile, and/or visual cues associated with conspecific 

strangers, but not familiar partners (Gobrogge et al., 2007). These data 

indicate that the increased neuronal activation in the AH may be involved in 

aggressive behavior displayed by pair bonded male prairie voles (Gobrogge et al.,


2007). This notion is corroborated by previous research documenting a critical 

role of the hypothalamus in regulating aggression across several mammalian 

species. For example, the ventromedial hypothalamus (VMH) in mice (Choi 

et al., 2005; Lin et al., 2011) and AH in rats (Veening et al., 2005) is responsive 

to conspecific chemosensory cues, which elicit aggressive behavior. Electrical 

stimulation applied directly to the AH induces attack toward conspecifics in rats 

(Kruk, 1991) and other animals (Albert and Walsh, 1984; Siegel et al., 1999). 

Interestingly, in humans, surgical lesioning of the AH reduces physical violence 

(Ramamurthi, 1988; Sano et al., 1966). In summary, data from vole studies 

demonstrate that activation of the MeA and AH is associated with the display 

of selective aggression (Gobrogge et al., 2007; Wang et al., 1997a). 

IV. NEURAL CIRCUITRY 

To directly evaluate the neural circuitry programming selective aggression, we 

performed a series of tract tracing experiments focusing on the AH and MeA. 

Intra-AH injections of an anterograde tracer, biotinylated dextran amine 

(BDA), resulted in BDA-ir staining in several brain regions. The AH projected 

to areas involved in processing chemosensory cues including the MeA; areas 

important for regulating social behavior including the LS, BNST, MPOA, VMH, 

and dorsal raphe (DR); and areas coordinating motor output, such as the 

periaqueductal gray (Gobrogge and Wang, 2009). The AH also projected to 

brain areas implicated in evaluating incentive salience including the medial 

prefrontal cortex (mPFC), nucleus accumbens (NAcc), and ventral pallidum 

(VP), as well as areas involved in memory formation and consolidation including 

hippocampal regions CA3 and the dentate gyrus (Gobrogge and Wang, 2009). 

Further, site-specific injections of a retrograde tracer, fluorogold (FG), into the 

LS, NAcc, or MeA resulted in FG-ir staining in the AH, indicating reciprocal 

connections between the AH and regions involved in motivation and chemosensory 

communication (Gobrogge and Wang, 2009). 

Fos-ir staining was also used to assess neuronal activation, in this circuit, 

associated with the display of pair bonding behavior. Males displaying aggression 

toward an unfamiliar female showed a significantly higher density of Fos-ir in the 

AH and MeA relative to males displaying affiliation toward their female partner 

(Fig. 6.1D and E), replicating our previous findings (Gobrogge et al., 2007; Wang 

et al., 1997a). Interestingly, we identified a MeA-AH-LS circuit that was activated 

when males were displaying aggression and a DR-AH circuit that was 

recruited when males were displaying affiliation (Gobrogge and Wang, 2009). 

The identification of these two neural circuits indicates a specific neuronal 

framework associated with the choice between affiliation (DR-AH circuit) and 

aggression (MeA-AH-LS circuit) in pair bonded male prairie voles.


V. NEUROCHEMICAL REGULATION OF SELECTIVE AGGRESSION 

Previous work has primarily focused on partner preference formation and documented 

a growing list of neurochemicals, including oxytocin (OT), AVP, corticotropin 

releasing hormone, DA, GABA, and glutamate, as well as their 

interactions in the regulation of pair bonding behavior (Aragona et al., 2003; 

Curtis and Wang, 2005a,b; Carter et al., 1995; DeVries et al., 1995; Gingrich 

et al., 2000; Lim and Young, 2004; Liu and Wang, 2003; Lim et al., 2004; Liu 

et al., 2001; Smeltzer et al., 2006; Wang et al., 1998, 1999; Williams et al., 1992, 

1994; Winslow et al., 1993). Importantly, data from several studies indicate a 

select subset of neurochemicals in the regulation of selective aggression. 

A. Neuropeptides 

Comparative approaches have been utilized in studies examining neuroendocrine 

mechanisms regulating social behavior in voles (Insel, 2010). Studies have 

focused on examining the central AVP system, a nine amino acid neuropeptide 

with diverse forebrain projections, across monogamous and promiscuous vole 

species. AVP is an antidiuretic hormone and has been shown to stimulate three 

structurally distinct receptors V1a, V1b, and V2, each activating very specific 

second messenger systems (Michell et al., 1979). Classically, AVP was first 

described as a primary homeostatic factor controlling kidney water reabsorption, 

blood volume/pressure, and vasodilatation in the peripheral nervous system. 

AVP and its receptors have been shown to be widely expressed in the central 

nervous system (Thibonnier, 1992), within specific brain regions (Johnson et al., 

1993). 

The V1a AVP receptor subtype (V1aR), in particular, has been extensively 

studied in the regulation of social behavior (Insel et al., 1994) including 

aggression (Albers et al., 2006; Cooper et al., 2005; Ferris et al., 2006; Winslow 

et al., 1993). V1aRs are directly coupled to stimulatory (s) Gq-11 proteins 

(Thibonnier et al., 1993). Stimulation of these G-proteins leads to activation 

of adenylate cyclase, cAMP, protein kinase C, and phospholipases C, A 2 , and D 

(Raggenbass et al., 1991; Thibonnier, 1992; Thibonnier et al., 1992, 1994) 

enhancing calcium influx through L-type calcium channels (Son and Brinton, 

2001). Such activation enhances learning and memory in the aging brain (Deyo 

et al., 1989; Yamada et al., 1996) via direct effects on gene expression (Murphy 

et al., 1991). 

Because AVP regulates species-specific social behaviors such as aggression 

(Ferris et al., 1984; Ryding et al., 2008), it was hypothesized that the 

organization of central AVP systems may differ between monogamous and 

promiscuous vole species (Bamshad et al., 1993b; Insel and Shapiro, 1992). To 

test this hypothesis, the distribution pattern of AVP cells, fibers, and receptors


were mapped in the vole brain. In all vole species examined, AVP-ir neurons 

were found in several brain regions, including the PVN and SON (supraoptic 

nucleus) of the hypothalamus, the BNST, MeA, AH, and MPOA (Bamshad 

et al., 1993b; Gobrogge et al., 2007; Wang, 1995; Wang et al., 1996). AVP-ir 

fibers were localized in the LS, lateral habenular nucleus, diagonal band, BNST, 

MPOA, and MeA (Bamshad et al., 1993b; Wang et al., 1996). Overall, AVP 

distribution patterns were highly conserved between monogamous and promiscuous 

vole species (Wang, 1995; Wang et al., 1996). Dramatic species differences 

in the distribution patterns and regional densities of V1aRs, however, were 

observed between vole species exhibiting different life strategies (Hammock 

and Young, 2002). For example, prairie voles have higher densities of V1aRs in 

the BNST, VP, central and basolateral nuclei of the amygdala, and accessory 

olfactory bulb, whereas montane voles exhibit a higher density of V1aRs in the 

LS and mPFC (Insel et al., 1994; Lim et al., 2004; Smeltzer et al., 2006; Wang 

et al., 1997c; Young et al., 1997). Further, prairie and pine voles exhibit similar 

patterns of V1aR binding, which differ from that of promiscuous meadow and 

montane voles (Insel et al., 1994; Lim et al., 2004). Species differences in V1aR 

distribution are stable across the lifespan (Wang et al., 1997b,c) and are receptorspecific, 

as no species differences are found in either the benzodiazepine or opiate 

receptor systems (Insel and Shapiro, 1992). In addition, monogamous prairie and 

promiscuous meadow voles differ in central AVP activity during mating and 

reproduction (Bamshad et al., 1993a; Wang et al., 1994). Because of these 

anatomical and functional differences, central AVP was thought to underlie 

selective aggression in male prairie voles (Winslow et al., 1993). 

Among the neuropeptides underlying aggression (Miczek et al., 2007; 

Siever, 2008), AVP, and its homolog vasotocin, have been found to regulate 

several forms of aggression across species (Caldwell et al., 2008; Riters and 

Panksepp, 1997) and diverse taxa (Backstrom and Winberg, 2009; Goodson, 

2008). In humans, central AVP correlates with aggressive behavior (Coccaro 

et al., 1998) and mediates anger (Thompson et al., 2004). Thus, the central AVP 

system may have evolved to be primed by a wide variety of experiences to induce 

aggression, when appropriate, in social animals (Donaldson and Young, 2008). 

Because central AVP underlies territorial aggression in other rodents (Ferris 

et al., 1984), AVP was proposed to regulate mating-induced aggression in prairie 

voles. In a pharmacological study, injections of a V1aR antagonist (V1aR Ant) 

into the lateral ventricle of male prairie voles blocked selective aggression 

induced by mating whereas injections of AVP-induced aggression toward an 

intruder in the absence of mating (Winslow et al., 1993). These effects were 

neuropeptide specific, as intracerebroventricular (ICV) infusion of an OT receptor 

antagonist had no effect on mating-induced aggression (Winslow et al., 

1993). Importantly, developmental exposure to either AVP in male prairie 

voles (Stribley and Carter, 1999) or OT in female prairie voles (Bales and


Carter, 2003) facilitates aggression in adulthood. Together, these data highlight 

a critical role of neuropeptide regulation of prairie vole aggression. However, the 

action site and release dynamics of neuropeptides in the regulation of selective 

aggression were unclear. 

In a more recent study, it was found that the display of selective aggression 

was associated with increased neuronal activation in the AH, specifically in 

neurons expressing AVP (Fig. 6.2A andB;Gobrogge et al., 2007). In a previous 

study in Syrian hamsters (Mesocricetus auratus), aggression has also been shown to 

be associated with an increase in AVP-ir/Fos-ir double-labeled cells in the nucleus 

circularis (NC), medial SON (mSON), and surrounding areas ventral to the fornix 

in the AH (Delville et al., 2000). Our data, combined with previous results from 

other species, suggest that the AH may be a brain area in which AVP regulates 

selective aggression. Indeed, AH-AVP has been implicated in various forms of 

aggressive behavior. In Syrian hamsters, for example, blockade of V1aRs in the 

AH diminished offensive aggression (Caldwell and Albers, 2004; Ferris and 

Potegal, 1988) whereas intra-AH administration of a V1aR agonist enhanced 

aggressive behavior (Caldwell and Albers, 2004; Ferris et al.,1997). More recently, 

the density of V1aRs in the AH has been found to increase significantly in Syrian 

hamsters after their display of offensive aggression (Albers et al., 2006). 

Because selective aggression was associated with neuronal activation in 

the AH, specifically in AVP-containing neurons (Fig. 6.2AandB;Gobrogge et al., 

2007), we tested the hypothesis that selective aggression is associated with AH- 

AVP release. In vivo brain microdialysis, with ELISA, was performed on male 

prairie voles that were pair bonded for 2 weeks. Pair bonded males displayed 

significantly higher levels of aggression toward novel females but more side-byside 

affiliation with their familiar female partner (Gobrogge et al., 2009). ELISA 

analysis indicated that exposure to a stranger female, compared to a familiar 

partner, increased AH-AVP release (Fig. 6.2C), which is further confirmed by 

correlation analyses indicating that AH-AVP release was coupled positively with 

aggression and negatively with affiliation (Gobrogge et al.,2009). Moreover, intra- 

AH administration of AVP at a high (500 ng/side), but not a low (5 ng/side), dose 

in sexually naïve males induced aggression toward a novel female, and this effect 

was mediated by V1aR as concurrent administration of a 10-fold higher dose of a 

V1aR Ant blocked AVP-induced aggression (Fig. 6.2D; Gobrogge et al., 2009). 

Further, intra-AH infusions of a V1aR Ant (5 mg/side), in pair bonded males, 

blocked aggression and facilitated social affiliation toward novel females 

(Fig. 6.2D; Gobrogge et al.,2009). Thus, AH-AVP is both necessary and sufficient 

to regulate mating-induced selective aggression in male prairie voles. 

Prior research has shown that the social environment has a significant 

impact on signaling and structural components of AVP systems in the brain. In 

marmoset monkeys, for example, prefrontal V1aR increases during fatherhood 

(Kozorovitskiy et al., 2006). In hamsters, several social and drug paradigms have


A B C 

10 

200 

b 

F 

AVP-ir/Fos-ir cells (density) 


8 

6 

4 

2 

0 

40 

30 

20 

10 

0 

Control Partner Stranger 

female 

Naive 

a 

a 

CSF 

a 

a 

AVP AVP+ 

V1aR Ant 

Paired 

b 

Stranger 

male 

D E F 

b 

* 

CSF V1aR Ant 

Naive 

AH 

OT 

AH 

Paired 

AVP release (% baseline) 


150 

100 

50 

0 

80 

60 

40 

20 

0 

Partner 

* 

Stranger 

female 

* 

Control AAV-V1aR 

Figure 6.2. Vasopressin (AVP) regulation of selective aggression. (A) Pair bonded male prairie voles 

that display aggression toward female or male strangers exhibit a significantly higher 

density of AVP-ir/Fos-ir double-labeled cells in the AH relative to pair bonded males 

re-exposed to their female partner or to males not exposed to any social stimulus 

(Control). (B) Photomicrograph of AVP-ir cell bodies and fibers (brown cytoplasmic 

staining), Fos-ir (dark nuclear staining), or AVP-ir/Fos-ir double labeled cells (insert) in 

the anterior hypothalamus (AH). (C) In vivo brain microdialysis reveals a significant 

increase in AH-AVP release in pair bonded male prairie voles displaying aggression 

toward a stranger female compared to males reexposed to their female partner. (D) Intra- 

AH AVP microinfusion, in sexually naïve males (Naïve), is sufficient to induce aggression 

toward a stranger female compared to control males infused with cerebral spinal 

fluid (CSF). AH-AVP-induced aggression is blocked with concurrent administration of 

AVP with a V1aR Ant. Pair bonded males (Paired) display aggression toward stranger 

females, which is blocked by intra-AH infusion of a V1aR Ant. (E) Pair bonded males 

(Paired) exhibit a significantly higher density of AVP-V1a receptor (V1aR) binding in 

the AH relative to sexually naïve males (Naïve). (F) Sexually naïve males infused with 

an adeno-associated virus expressing the V1aR gene (AAV-V1aR) in the AH exhibit 

enhanced aggression toward stranger females relative to males infused with the 

LacZ-gene (Control). F, fornix; OT, optic tract. Bars indicate means standard error 

of the mean. Bars with different Greek letters differ significantly from each other. 

*p


significantly increased the number of AVP mRNA labeled cells in the BNST 

(Wang et al., 1994). Because social isolation increases the density of V1aRs in 

the AH to regulate offensive aggression in golden hamsters (Albers et al., 2006), 

we tested the hypothesis that the density of AH-V1aR changes with pair bonding 

experience to engage selective aggression. Pair bonded males showed higher 

densities of V1aR binding, site specifically, in the AH (Fig. 6.2E), with no 

change in OT receptor binding, demonstrating that pair bonding experience 

induces a neural plastic reorganization of V1aRs in a region- and receptorspecific 

manner (Gobrogge et al., 2009). To determine whether this increase in 

V1aR density in the AH, following pair bonding, was directly related to the 

emergence of aggression toward novel females, we used viral vector mediated 

gene transfer to artificially elevate V1aR density in the AH. Males that received 

intra-AH infusions of the AAV-V1aR displayed higher levels of aggression 

toward a novel female compared to control males that received infusions of the 

LacZ-gene (Fig. 6.2F; Gobrogge et al., 2009). Similar viral vector mediated 

increases in V1aR expression in the VP in voles (Lim et al., 2004; Pitkow 

et al., 2001) and LS in mice (Bielsky et al., 2005) enhanced affiliation. In male 

rats, intermale aggression correlates with AVP release in the LS while AVP 

release in the BNST is inversely related to aggression levels (Veenema et al., 

2010). Together, these data support the notion that region-specific AVP functioning 

regulates specific types of social behaviors, and multiple brain regions 

serve as a circuit in which AVP coordinates a range of adaptive behaviors 

important for reproductive success. 

B. Dopamine 

Anatomically, central DA is divided into three distinct pathways: nigrostriatal, 

incertohypothalamic, and mesocorticolimbic. DA cell bodies projecting from 

the substantia nigra synapse in the dorsal striatum and comprise the nigrostriatal 

path (Swanson, 1982). Incertohypothalamic paths extend from DA cell bodies of 

the A12–14 cell groups and project to the MPOA and PVN (Cheung et al., 

1998). The mesocorticolimbic path represents DA cell bodies originating in the 

ventral tegmental area (VTA; Fig. 6.3C) projecting to the mPFC and NAcc 

(Fig. 6.3C; Carr and Sesack, 2000; Swanson, 1982). In addition, DA cells in the 

AH (Fig. 6.3B) project to forebrain areas including the striatum, LS, NAcc, and 

mPFC (Alcaro et al., 2007; Lindvall and Stenevi, 1978; Maeda and Mogenson, 

1980). 

DA preferentially binds to two families of receptors: D1-like and D2- 

like. Both types of DA receptors are found in the mPFC, NAcc, LS, and MeA 

(Boyson et al., 1986). D1-like receptors are directly coupled to both stimulatory 

(s) Ga and Ga olf proteins (Neve et al., 2004). Stimulation of these G-proteins 

leads to activation of adenylate cyclase, cAMP, and protein phosphatase-1


A B C 

TH-ir/Fos-ir cells (density) 

20 

15 

10 

5 

0 

a 

a 

b 


female 

b 

Stranger 

male 

D E F 

OT 

AH 

F 

TH-NAcc 

TH-VTA 

DAR binding (optical density) 

200 

160 

120 

80 

40 

0 

D1R 

* 

Naive 

Paired 

D2R 

Naive 

NAcc 

Paired 

Aggression (# attacks /10 min) 

40 

30 

20 

10 

0 

a 

b 

CSF CSF D2R Ant D1R Ant 

partner stranger stranger stranger 

b 

a 

Figure 6.3. Dopamine (DA) regulation of selective aggression. (A) Pair bonded male prairie voles 

that display aggression toward female or male strangers exhibit a significantly higher 

density of TH-ir/Fos-ir double-labeled cells in the AH relative to pair bonded males reexposed 

to their female partner or to males not exposed to any social stimulus (Control). 

(B) Photomicrograph of TH-ir cell bodies and fibers (brown cytoplasmic staining), Fos-ir 

(dark nuclear staining), or TH-ir/Fos-ir double labeled cells (insert) in the anterior 

hypothalamus (AH). (C) Photomicrograph of TH-ir fibers in the nucleus accumbens 

(NAcc) and neurons in the ventral tegmental area (VTA). (D, E) Pair bonded males 

(Paired) exhibit a significantly higher density of DA D1-like (D1R), but not D2-like 

(D2R), receptor binding in the NAcc compared to sexually naïve males (Naïve). (F) 

Pair bonded males, infused with CSF in the NAcc, display aggression toward a stranger 

female but not toward their female partner. Concurrent infusion of CSF with a DA D1R 

antagonist (D1R Ant), but not D2R antagonist (D2R Ant), in the NAcc is sufficient to 

attenuate pair bonding-induced aggression toward a stranger female. F, fornix; OT, optic 

tract. Bars indicate meansstandard error of the mean. Bars with different Greek letters 

differ significantly from each other. *p


Because mesocorticolimbic DA underlies partner preference formation 

(Aragona and Wang, 2009; Aragona et al., 2003; Gingrich et al., 2000; Gobrogge 

et al., 2008; Wang et al., 1999), studies focused on examining the potential role 

of central DA regulating selective aggression (Gobrogge et al., 2008). Pair 

bonded male prairie voles have significantly higher levels of DA D1-type receptors 

(D1Rs), but not D2-type receptors (D2Rs), in the NAcc (Fig. 6.3D and E; 

Aragona et al., 2006). Males that cohabitated with a female for 24 h, with or 

without mating, did not exhibit an increase in D1Rs in the NAcc, supporting the 

idea that upregulation of NAcc D1Rs, after pair bonding, may directly regulate 

selective aggression. To test this notion, pair bonded male prairie voles were 

injected with a D1R antagonist (D1R Ant) into the NAcc. NAcc-D1R, not D2R 

(D2R Ant), antagonism was sufficient to block selective aggression in pair 

bonded male prairie voles (Fig. 6.3F; Aragona et al., 2006). In other work, 

both brief and extended cohabitation with unfamiliar conspecifics in female 

prairie voles significantly increased the number of DA-ergic cells in the BNST 

and MeA (Cavanaugh and Lonstein, 2010) and blocking D2Rs, during development, 

decreased aggression-related behavior including infanticide in adult 

female, but not male, prairie voles (Hostetler et al., 2010). Further, pair bonded 

male prairie voles—displaying aggression toward either male or female intruders, 

had a significantly higher density of cells in the AH that were double-labeled for 

tyrosine hydroxylase-ir (TH—rate-limiting enzyme in DA biosynthesis) and Fosir 

than males not exposed to a social stimulus or males that were re-exposed to 

their familiar female partner (Fig. 6.3A and B), implicating AH-DA involvement 

in selective aggression (Gobrogge et al., 2007). 

C. Steroid hormones 

Physical aggression is significantly more common in males than females and 

these behavioral sex differences have been observed across many species 

(Gatewood et al., 2006). Research describing biological contributions underlying 

these sex differences has focused primarily on steroid hormones (Gatewood et al., 

2006). Several studies have examined the role of androgens in the development 

of aggressive behavior, both organizationally (e.g., treatment with prenatal 

testosterone) and activationally (e.g., treatment with postnatal testosterone). 

Previous research has found that prenatal androgen exposure increases the 

behavioral expression of adult aggression (Michard-Vanhee, 1988; Vale et al., 

1972). Although organizational and activational influences of androgen on 

aggression have been noted, some inconsistent results have been reported. For 

example, castration in male rats (Koolhaas et al., 1990) and male prairie voles 

(Demas et al., 1999) has no affect on aggression. Thus, circulating testosterone, 

alone, cannot solely contribute to the expression of aggressive behavior in all 

rodent species. However, these findings do not rule out the possible effects of


testosterone having organizational influences on other neurochemical systems in 

the brain—which, together, may regulate aggression in adulthood. Thus, 

neurochemical–steroid hormone interactions—underlying aggression—have 

also been examined. For example, AVP administered directly into the MeA 

facilitates territorial aggression in male rats and is sufficient to block the effects of 

castration on reducing aggression (Koolhaas et al., 1990). Further, castration 

(Bermond et al., 1982), but not ovariectomy (Kruk et al., 1984), decreases the 

excitability of neurons in the AH—blocking electrically induced aggression, 

which in castrates can be reversed by testosterone treatment (Bermond et al., 

1982). Therefore, circulating testosterone may be acting as a potent neuromodulator—interacting 

with neurochemicals, like AVP, to regulate aggression. 

Additional evidence demonstrating steroid hormone–neurotransmitter 

interactions exists in research investigating central DA. For example, 75% of 

TH-ir expressing cells in the hamster posterior MeA contain androgen receptors, 

are DA-ergic (i.e., they do not co-label with DA beta hydroxylase), and are 

highly influenced by gonadal hormones compared to TH-ir cells found in the 

anterior MeA (Asmus and Newman, 1993; Asmus et al., 1992). Interestingly, 

this same group of TH-ir cells is found in the posterior MeA and BNST in male 

prairie voles, which appears to be influenced by testosterone (Northcutt et al., 

2007) and activated after mating and social experience (Northcutt and Lonstein, 

2009). Together, these data suggest interactions between steroid hormones and 

central DA, in areas such as the MeA, in processing chemosensory cues related to 

social communication. 

D. Classical neurotransmitters 

In addition to the effects of neurotransmitters and hormones on aggression, 

neuromodulators such as GABA and glutamate have also been shown to be 

involved in the display of agonistic behavior. For example, microinjection of a 

GABA antagonist (Adams et al., 1993; Roeling et al., 1993) with concurrent 

treatment of a glutamate agonist (Haller et al., 1998) in the AH facilitates attack 

behavior in rodents—with higher doses having greater behavioral effects. Further, 

reverse microdialysis infusion with a glutamate agonist and a GABA-A 

antagonist into the AH of rats, recently having experienced an agonistic 

encounter, also facilitates aggression (Haller et al., 1998). Finally, it is worth 

mentioning that neuromodulators in the VTA, which provides the major 

source of DA projections to the NAcc (Fig. 6.3C) and mPFC, are also involved 

in pair bonding behavior. Glutamate and GABA receptor blockade in 

the VTA, which alters DA activity in the NAcc, induces partner preference 

formation in the absence of mating in male prairie voles (Curtis and Wang, 

2005b).


VI. MOLECULAR GENETICS OF SELECTIVE AGGRESSION 

Monogamous male prairie voles carry several repetitive microsatellite DNA 

sequences in the promoter region of the V1aR gene that are not found in 

promiscuous male voles (Hammock and Young, 2002, 2004; Young, 1999). 

These genetic differences directly contribute to species differences in social 

organization (Landgraf et al., 2003; Lim et al., 2004; Pitkow et al., 2001). Further, 

mice carrying a transgene coding for the prairie vole V1aR exhibit central V1aR 

patterns similar to prairie voles and, when injected with AVP, display enhanced 

social affiliation (Young et al., 1999). Male voles injected in the VP, with a virus 

expressing V1aR, display enhanced partner preference in the absence of mating 

(Lim et al., 2004; Pitkow et al., 2001). Interestingly, individual variability in the 

genetic sequences coding V1aRs has revealed remarkable within species differences 

in the strength of monogamous pair bonds in prairie voles (Hammock and 

Young, 2005; Ophir et al., 2008). 

Because prairie voles carry varying lengths of DNA to code V1aRs 

(Hammock and Young, 2005), this genomic predisposition enables their brain 

to dynamically express V1aRs after sociosexual experience. This genetic loading 

distinguishes prairie voles from traditional laboratory rodents that lack this 

genetic makeup. Future work would benefit from comparing aggression levels 

between male prairie voles carrying long versus short versions of the promoter 

region encoding the V1aR gene. In humans, polymorphisms in the promoter 

region encoding V1aR are associated with differences in sociosexual bonding 

behaviors (Prichard et al., 2007; Walum et al., 2008) including altruism (Israel 

et al., 2008) and deficits in social communication observed in individuals with 

autistic spectrum disorders (Israel et al., 2008; Kim et al., 2002; Meyer- 

Lindenberg et al., 2008). To date, no study has examined potential associations 

between the V1aR gene and patterns of aggression in humans. Thus, it would be 

interesting to examine polymorphisms in the V1aR gene in patients with a 

lifetime history of pathological violence, as the V1aR system may harbor susceptibility 

genes underlying extreme forms of aggression, increasing the prevalence 

of homicide and suicide in human populations. 

VII. DRUG-INDUCED AGGRESSION 

The prairie vole has been established as an animal model for depression related to 

social separation (Bosch et al., 2009; Grippo et al., 2007). Further, chronic metal 

ingestion—a potential model for autism—produces social avoidance in male, but 

not female, prairie voles exposed to unfamiliar same-sex conspecific strangers 

(Curtis et al., 2010), suggesting a developmental mechanism underlying the social


deficits associated with autistic spectrum disorders in humans. Recently, prairie 

voles have also been utilized to examine the effects of drugs of abuse on pair 

bonding behavior (Gobrogge et al., 2009; Liu et al., 2010; Young et al., 2011b). 

Drug addiction is a significant problem for many humans because drug 

abuse has such a powerful control over social behavior essential for survival 

(Kelley and Berridge, 2002; Nesse and Berridge, 1997; Panksepp et al., 2002). In 

humans, substance abuse has been associated with weapon-related violence and 

homicide (Hagelstam and Hakkanen, 2006; Madan et al., 2001; Spunt et al., 

1998), intimate partner aggression, including partner-directed physical and 

psychological aggression (Chermack et al., 2008; O’Farrell and Fals-Stewart, 

2000), sexual (El-Bassel et al., 2001), and child abuse (Haapasalo and 

Hamalainen, 1996; Mokuau, 2002; Walsh et al., 2003). Collectively, drugrelated 

violence leads to family system dysfunction and incarceration (Krug 

et al., 2002), creating significant societal concerns. While aggression research 

in humans has provided valuable information regarding relationships between 

drug abuse and violence, animal models have been used to examine neural 

mechanisms underlying drug-induced aggression. 

Drug use can override neurobiological programs to activate maladaptive 

forms of agonistic behavior, engaging inappropriate types of physical aggression 

(Swartz et al., 1998) such as domestic violence (Moore et al., 2008) and intimate 

partner homicide (Farooque et al., 2005). As a result, chronic drug abuse can 

cause permanent neural reorganization (Nestler and Aghajanian, 1997; White 

and Kalivas, 1998), impairing the adaptive—social brain (Panksepp et al., 2002), 

leading to the display of maladaptive social behavior (Wise, 2002). Multiple 

studies have demonstrated that aggression may be altered shortly after drug 

exposure and that the directionality of these effects depends on drug, dose, and 

individual differences between subjects. 

Repeated exposure to several drugs of abuse, during adolescence or 

adulthood, persistently enhances agonistic behaviors, specifically those associated 

with offensive aggression. For example, Syrian hamsters treated during 

adolescence with cocaine (DeLeon et al., 2002a; Harrison et al., 2000a; Jackson 

et al., 2005; Knyshevski et al., 2005a,b; Melloni et al., 2001) or anabolic-androgenic 

steroids (AASs) (DeLeon et al., 2002b; Harrison et al., 2000b; Melloni and 

Ferris, 1996; Melloni et al., 1997) display enhanced offensive aggression in 

adulthood. Interestingly, these drug experiences reorganize AVP (Grimes et al., 

2007; Harrison et al., 2000b; Jackson et al., 2005), DA (Ricci et al., 2009; 

Schwartzer et al., 2009), and GABA (Schwartzer et al., 2009) signaling in 

the AH. 

For example, when compared with nonaggressive sesame oil-treated 

control males, aggressive AAS-treated males exhibit significant neuroplastic 

changes in the AH including increased AVP-ir fiber density and AVP content 

(Harrison et al., 2000b), an increase in TH-ir cell and fiber density (Ricci et al.,


2009), enhanced DA-D2R expression (Schwartzer et al., 2009), a higher number 

of GAD 67 -ir cells (Schwartzer et al., 2009), and decreased GABA A receptor 

expression (Schwartzer et al., 2009). Further, pharmacological blockade of D2 

(Schwartzer and Melloni, 2010a,b), but not D5 (Schwartzer and Melloni, 

2010b), DA receptors in the AH abolishes these effects. Together, results from 

this work suggests that AVP and DA signaling facilitates aggression by GABA 

inhibition in the AH of AAS-treated male Syrian hamsters. 

As noted above, previous work has shown that exposure to drugs of 

abuse, such as cocaine, enhances male–male aggression by reorganizing the AH- 

AVP system in hamsters (Jackson et al., 2005). Therefore, we tested the hypothesis 

that amphetamine (AMPH), another commonly abused psychostimulant, 

would act in a similar fashion in affecting male-to-female aggression in prairie 

voles. Because our recent data revealed that repeated AMPH treatment—(1 mg/ 

kg) for 3 consecutive days—induces a conditioned place preference (Aragona 

et al., 2007) and blocks mating-induced partner preference (Fig. 6.4A; Liu et al., 

2010), this treatment regimen was used. To examine the selectivity of AMPHinduced 

aggression, males treated with saline or AMPH were tested for aggression 

toward an unfamiliar female or a familiar female (that cohabitated with a 

male across a wire mesh screen for 24 h without mating). Compared with salinetreated 

controls, AMPH-treated males displayed significantly higher levels of 

aggression toward either familiar or unfamiliar females (Fig. 6.4B), indicating 

that AMPH exposure induces generalized aggression, rather than being selective 

to novel females. This AMPH treatment also induced an increase in the density 

of AVP-V1aR binding in the AH, but not MPOA, relative to saline control 

males (Fig. 6.4C). Further, intra-AH infusions of CSF containing the V1aR Ant, 

but not CSF alone, diminished AMPH-induced aggression toward novel females 

(Fig. 6.4D). These data suggest that repeated exposure to AMPH can induce 

female-directed aggression and that this behavior is mediated by AH-AVP. 

Interestingly, these behavioral effects coincide with upregulation of D1Rs in 

the NAcc (Liu et al., 2010) and V1aRs in the AH (Gobrogge et al., 2009)— 

which both facilitate aggression toward novel females (Aragona et al., 2006; 

Gobrogge et al., 2009); indicating that drugs of abuse can hijack neuroplasticity 

evolved to maintain monogamous pair bonds. 

VIII. CONCLUSIONS AND FUTURE DIRECTIONS 

Prairie voles have provided an excellent model system to study the neurobiology 

of ethologically meaningful aggression associated with monogamous pair bonds. 

Aggression can be easily manipulated under laboratory conditions and reliably 

expressed following mating and social cohabitation. Several brain areas: MeA, 

AH, and NAcc, work in a neural circuit to regulate selective aggression via AVP


A 

B 

Side-by-Side contact (min/3 h) 

100 

80 

60 

40 

20 

** ** 

Partner 

Stranger 

Frequency of aggression 

40 

30 

20 

10 

Familiar 

Unfamiliar 

a 

b 

0 

Intact 

0.0 1.0 5.0 

AMPH (mg/kg) 

0 

Saline 

AMPH 

C 

V1aR binding (optical density) 

30 

25 

20 

15 

10 

5 

Saline 

AMPH 

* 

D 

Frequency of aggression 

30 

25 

20 

15 

10 

5 

* 

0 

MPOA 

AH 

0 

CSF 

V1aR Ant 

Figure 6.4. Drug experience impairs pair bonding behavior. (A) Pair bonded (Intact) and saline 

treated (0.0) male prairie voles, receiving 3-day—once daily; repeated injections, spend 

significantly more time in physical side-by-side contact with their familiar female 

partner than with an unfamiliar stranger female. Pair bonded males injected (i.p., 

intraperitoneal) with 1.0 or 5.0 mg/kg amphetamine (AMPH) spent equal amounts of 

time in physical side-by-side contact with their female partner as with a stranger female. 

(B, C) Repeated AMPH exposure, in sexually naïve males, increases aggression toward 

both familiar and unfamiliar females and enhances the density of vasopressin (AVP) 

receptor (V1aR) expression in the anterior hypothalamus (AH) but not in the medial 

preoptic area (MPOA). (D) Site-specific microinfusion of an AVP-V1aR antagonist 

(V1aR Ant) into the AH, of males receiving 3-day repeated AMPH exposure (i.p.), 

significantly decreases AMPH-induced aggression toward novel females relative to 

males receiving intra-AH infusions of cerebral spinal fluid (CSF). Bars indicate meansstandard 

error of the mean. Bars with different Greek letters differ significantly from 

each other. *p


Although male-to-male aggression has been studied in a variety of 

mammals, we know surprisingly little about male-to-female aggression and its 

underlying neuromechanisms. Interestingly, pair bonded male prairie voles naturally 

display aggression toward conspecific females but not toward their female 

partner and, therefore, selective aggression allows for investigation of the neurobiology 

of male-to-female aggression. Data have demonstrated that this form of 

selective aggression is mediated by elevated AVP release and increased V1aR 

expression in the AH—priming male prairie voles to respond aggressively to 

novel females. In addition, data have also shown that the same AH-AVP system 

mediates generalized, female-directed aggression induced by AMPH. Together 

with previous research from other animals (Ferris et al., 1989, 1997; Grimes et al., 

2007; Harrison et al., 2000b; Jackson et al., 2005; Veenema et al., 2006), these 

data demonstrate a unique point of convergence in the mammalian brain (Choi 

et al., 2005; Motta et al., 2009). The AH-AVP system is highly conserved and 

functions to control different forms of aggression to maintain a wide range of 

resources important for reproductive success. These highly evolved neuropeptide 

systems appear to be extremely vulnerable to drugs of abuse, as our data show that 

hypothalamic AVP controls both naturally occurring as well as drug-facilitated 

female-directed aggression, suggesting that psychostimulant drugs, like AMPH, 

are capable of switching adaptive (functional) forms of aggression (e.g., mate 

guarding) to aberrant (dysfunctional) forms of violent behavior (e.g., partnerdirected 

aggression). Together, these data demonstrate the utility of the prairie 

vole model for evaluation of the effects of drug abuse on neural systems 

controlling adaptive forms of aggression—such as mate guarding. 

Finally, because other neurochemicals, such as DA (Aragona et al., 

2006) and serotonin (Villalba et al., 1997), also regulate selective aggression in 

prairie voles, offensive aggression related to drug experience (Tidey and Miczek, 

1992) and AVP/5-HT interactions mediate aggression in other rodents (Ferris 

et al., 1997; Veenema et al., 2006), future studies should examine potential 

neurochemical interactions in the regulation of selective aggression. By understanding 

the basic neuroendocrinology of pair bonding in prairie voles, we may 

eventually be able to better clarify the neural chemistry of mental health deficits 

associated with aberrations in social behavior in patients suffering from drug 

addiction or pathological violence. 


The authors would like to thank Benjamin William Tyson for critically reading this manuscript. 

The work reviewed in this chapter was supported by National Institutes of Health grants MHF31- 

79600 to K. L. G., MHR01-58616, MHR01-89852, DAR01-19627, and DAK02-23048 to Z. X. W., 

and NIH Program Training Grant T32 NS-07437.


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7 

The Neurochemistry of Human 

Aggression 

Rachel Yanowitch and Emil F. Coccaro 

Clinical Neuroscience Research Unit, Department of Psychiatry, The University 

of Chicago Pritzker School of Medicine, Chicago, Illinois, USA 


II. Serotonin 

III. Dopamine 

IV. Norepinephrine (Noradrenaline) 

V. GABA 

VI. Peptides 

VII. Conclusion 

References 

ABSTRACT 

Various data from scientific research studies conducted over the past three decades 

suggest that central neurotransmitters play a key role in the modulation of 

aggression in all mammalian species, including humans. Specific neurotransmitter 

systems involved in mammalian aggression include serotonin, dopamine, norepinephrine, 

GABA, and neuropeptides such as vasopressin and oxytocin. Neurotransmitters 

not only help to execute basic behavioral components but also serve 

to modulate these preexisting behavioral states by amplifying or reducing their 

effects. This chapter reviews the currently available data to present a contemporary 

view of how central neurotransmitters influence the vulnerability for aggressive 

behavior and/or initiation of aggressive behavior in social situations. Data 

reviewed in this chapter include emoiric information from neurochemical, 

pharmaco-challenge, molecular genetic and neuroimaging studies. ß 2011, Elsevier Inc. 



DOI: 10.1016/B978-0-12-380858-5.00005-8

152 Yanowitch and Coccaro 


Since the late 1970s, data from scientific research studies have suggested that 

endogenous brain chemicals called neurotransmitters play a key role in the 

modulation of aggression. Human aggression is a multidimensional behavior 

that is determined by an amalgamation of biological, genetic, environmental, 

and psychological factors. Neurotransmitters not only help to execute these basic 

behavioral components but also serve to modulate these preexisting behavioral 

states by amplifying or reducing their effects. Genetic abnormalities in a number 

of neurotransmitter pathways have been implicated in aggression-related disorders. 

Current and future research aims to understand how these neurotransmitters 

function both normally and abnormally to mediate aggression and other 

human behaviors. With the evolution of genetic testing and continued development 

of neuroimaging technologies such as functional magnetic resonance 

imaging (fMRI) and positron emission tomography (PET) scanning, the ability 

of the scientific researcher to investigate the brain’s constellation of synapses and 

neurotransmitters is growing ever more proficient. While it is clear from these 

studies that neurotransmitters contribute significantly to the predisposition of an 

individual toward aggressiveness, whether neurotransmitter dysfunction alone is 

sufficient to cause violent aggression remains unclear. 

Aggression may be impulsive or premeditated in nature. In the former 

case, impulsivity defines, or describes, the aggression. That is, it is the aggression 

that is impulsive not that the person is aggressive and at other times impulsive, 

though that may be true as well. Diagnoses associated with impulsive aggression 

include Intermittent Explosive Disorder (IED) characterized by frequent and 

problematic impulsive aggressive outbursts, and Borderline Personality Disorder 

(BPD) characterized by instability in self-image, in interpersonal relationships as 

well as impulsivity and affect (including anger and aggression). In the latter case, 

the aggression is planned and carried out in order to achieve some tangible goal. 

Diagnoses associated with this type of aggression include Antisocial Personality 

Disorder (AsPD) which is characterized by a pattern of disregard for, and violation 

of, the rights of others. These types of aggression are not mutually exclusive, 

however, and some individuals display both types of aggression at different times. 

II. SEROTONIN 

Serotonin or 5-hydroxytryptamine (5-HT) is a multipurpose monoamine neurotransmitter 

derived from the amino acid, L-tryptophan, and has been implicated 

as an important regulator of mood (Kumar et al., 2010; Kunisato et al., 2010; 

Ruhé et al., 2007), appetite (Curzon, 1991; Dourish, 1995; Lam et al., 2010), 

gastrointestinal muscle contractility (Gershon, 2004; Xu et al., 2007), self-

7. The Neurochemistry of Human Aggression 153 

injurious behavior (Peddeer, 1992), and sleep (Monti, 2010; Monti and Jantos, 

2008; Monti and Monti, 2000). With respect to aggression and other behavioral 

disorders, serotonin action is highly complex and varies depending upon which 

receptor it is bound to, how much 5-HT is available in the synapse, how much 

enzymatic activity is present, and whether other agonists or antagonists are 

available for competitive binding. Both the clinical and molecular data on 

central 5-HT function in the mammalian brain overwhelmingly suggests that a 

reduction in 5-HT activity in emotion-modulating brain regions such as the 

prefrontal cortex and the anterior cingulate cortex leads to a predisposition for 

impulsive aggressiveness (New et al., 2002; Parsey et al., 2002; Seo et al., 2008; 

Siever et al., 1999). Research suggests that 5-HT significantly contributes to the 

genetically determined differences seen in individuals and that its primary 

mechanism of action is via the genes encoding major components of 5-HT 

viability in the brain such as the enzymes tryptophan hydroxylase-1 and monoamine 

oxidase A (MAOA) (Popova, 2008). Most of the literature discussing 5- 

HT regulation of aggression focuses on 5-HT metabolite levels and the functional 

state of 5-HT receptors. 

The first literature written on serotonin and impulsive aggressive behavior 

in human subjects came from two independent research groups (Asberg 

et al., 1976; Sheard et al., 1976) in 1976. Sheard et al. reported that administration 

of the putative 5-HT-enhancing agent, lithium carbonate, significantly 

reduced impulsive aggressive behavior in a prison inmate population. Asberg 

et al. found that lower concentrations of lumbar CSF 5-hydroxyindoleactic acid 

(5-HIAA), the most stable 5-HT metabolite in the brain, were correlated with 

violent and suicidal behavior. In 1979, Brown et al. studied 26 males with 

significant personality disorder traits (Brown et al., 1979). CSF amine metabolite 

levels of serotonin (5-HIAA), norepinephrine (3-methoxy-4-hydroxy-phenylglycol, 

MHPG), and dopamine (homovanillic acid, HVA), respectively, were 

studied. CSF 5-HIAA was significantly negatively correlated with aggression 

(r¼ 0.78), and MHPG was significantly positively correlated with aggression 

(r¼0.64). Brown et al. replicated this finding for CSF 5-HIAA and extended 

these findings to include other measures of aggression such as “psychopathic 

deviance” (i.e., defiance of authority and impulsivity) (Brown et al., 1982; 

Coccaro and Siever, 2002). Despite the fact that a number of subsequent studies 

supported the findings of an inverse relationship between aggression and CSF 

5-HIAA levels (Kruesi et al., 1990; Lidberg et al., 1985; Limson et al., 1991; 

Linnoila et al., 1983), additional reports also suggest a direct (Castellanos et al., 

1994; Moller et al., 1996; Prochazka and Agren, 2003) or no relationship 

(Coccaro et al., 1997c; Gardner et al., 1990) between the two. In a recent 

paper by Coccaro et al., the authors were able to reconcile the disputed data by 

reconsidering the CSF 5-HIAA levels in the context of (1) the severity of the 

aggression of the individual and (2) the CSF HVA levels present concomitantly


(Coccaro and Lee, 2010). Under this new paradigm, the results emerged against 

Brown’s preliminary findings: CSF 5-HIAA concentrations varied directly with 

aggression and CSF HVA concentrations varied inversely. In this model, a 

deficiency hypothesis of 5-HT for aggressiveness is only fulfilled if presynaptic 

release of 5-HT is being reduced and there is compensation of postsynaptic 5-HT 

receptor function (Coccaro, 1998). 

Evidence for a model in which postsynaptic 5-HT receptor function is 

altered by presynaptic reduction begins with Stanley et al.’s (1982) report 

demonstrating a reduced number of presynaptic 5-HT transporter sites in aggressive 

suicide victims as compared with accident victims (Stanley et al., 1982). The 

following year, Stanley and Mann published additional results showing increased 

postsynaptic 5-HT2A receptor sites in suicide subjects (Stanley and Mann, 

1983), suggesting that, in addition to modified responsiveness, there may be a 

change in receptor number as well. In response to these data, researchers 

designed psychopharmacologic challenge studies in order to further assess preand 

postsynaptic function in premortem subjects (Coccaro, 1998). These pharmacochallenge 

studies involve the activation of a specific neurotransmitter 

system through the administration and consequent ligand–receptor interaction 

of a pharmacologic agent. Subsequent signaling cascades result in physiological 

events that trigger homeostatic, behavioral, and hormonal alterations that can 

be measured as an index of the responsiveness of the neurotransmitter system in 

question (Coccaro and Kavoussi, 1994). 

The first report of a correlation between aggression and pharmacochallenge 

studies were published by Coccaro et al., 1989. In this study, prolactin 

responses to 60 mg of oral D,L-fenfluramine of 45 males with major affective 

(n¼25) and/or personality (n¼20) disorder were compared to those of 18 healthy 

male controls. D,L-fenfluramine was chosen as a challenge probe because of its 

properties as a serotonin-releasing agent. Its mechanism of action is the release of 

serotonin by disrupting vesicular storage of the neurotransmitter and reversing 

serotonin transporter function (Welch and Lim, 2007). Since prolactin secretion 

is directly dependent upon 5-HT transmission, recording prolactin levels can 

provide an indirect but effective measurement of 5-HT activity (Coccaro et al., 

1998a). Both groups of subjects demonstrated reduced prolactin responses to D,Lfenfluramine 

compared to controls. However, significant correlations appeared 

between reduced prolactin responses to D,L-fenfluramine and history of suicide 

attempts in all experimental subjects and impulsive aggression in males with 

personality disorder (Coccaro et al.,1989). These results suggest that altered 5-HT 

activity, specifically reduced receptor function, is apparent in subjects with aggression-related 

disorders. In a later study by Coccaro et al., the relationship between life 

history of aggression and prolactin response to D-fenfluramine and to CSF 5-HIAA 

concentration was evaluated (Coccaro et al., 1997a). The results were consistent 

with the altered postsynaptic 5-HT receptor function hypothesis: aggression was


significantly and inversely correlated with prolactin responses to D-fenfluramine but 

not with CSF 5-HIAA levels. Notably, prolactin response to fenfluramine appears 

to reflect activation of 5-HT2 receptors, likely of the 5-HT2c subtype (Coccaro 

et al.,2010a). Additional research has revealed that prolactin responses to fenfluramine 

are also positively correlated with prolactin responses to m-CPP challenge, 

which assesses 5-HT postsynaptic receptor activation (Coccaro et al., 1997b). 

Thus far, seven subtypes of 5-HT receptors have been identified, ranging 

from 5-HTR1 to 5-HTR7. These receptors have been found to mediate both 

excitatory and inhibitory inputs in a number of brain regions associated with 

aggression (Siever, 2008), emotion regulation, and cognition. Inhibition of 

offensive aggression via agonists of 5-HT1a attenuates various forms of aggression 

in animals (Ferris et al., 1999; Joppa et al., 1996; Miczek et al., 2004; 

Olivier et al., 1995; Ricci et al., 2006; White et al., 1991). According to one 

study by Popova et al., less aggressive rats had higher 5-HT1a receptor expression 

in the midbrain (Popova et al., 2005), whereas in the frontal cortex, lower 

aggression was associated with a decrease in 5-HT1a receptor mRNA (Popova 

et al., 2007). In support of this hypothesis, a recent study showed that high 5- 

HT1a receptor density corresponded to increased aggressiveness in male Golden 

hamsters (Cervantes and Delville, 2009). Additional confirmation came from a 

study in which PET imaging of healthy subjects revealed that aggression is 

positively correlated to 5-HT1a receptor distribution in the dorsolateral and 

ventromedial prefrontal cortex, in the orbitofrontal cortex, and in the anterior 

cingulate cortex (Witte et al., 2009). Support of 5-HT1a’s involvement in 

aggression also comes from animal studies showing that offensive aggression in 

hamsters is inhibited by 5-HT1a receptors and facilitated by 5-HT3 receptor 

activation (Cervantes et al., 2010). Agonists of the 5-HT1a and 5-HT1b (5- 

HT1d in the human) receptors in the medial prefrontal cortex or septal area can 

increase aggressive behavior under specific conditions (Takahashi et al., 2011). 

Activation of these two receptors, as well as the 5-HT2a and 5-HT2c receptors 

in mesocorticolimbic areas, reduces species-typical and other aggressive behaviors. 

Pathological aggression is reportedly reduced by activation of 5-HT transporters, 

whereas dysfunction of genes that affect the 5-HT system directly such as 

MAOA cause an escalation in pathological aggression (Alia-Klein et al., 2008). 

With respect to 5-HT2a distribution, PET imaging demonstrates that 

individuals with IED and current physical aggression have increased receptor 

density in the orbitofrontal cortex when compared to individuals with IED but 

no current physical aggression or when compared to individuals who served as 

healthy controls (Rosell et al., 2010). This is similar to 5-HT1a distribution in 

the orbitofrontal cortex with the respect to aggression, as noted above (Witte 

et al., 2009). In a separate study, 5-HT2a receptor-binding activity was investigated 

in a nearby brain region, the dorsolateral prefrontal cortex, and a pattern 

different to that seen in the orbitofrontal cortex emerged. The results found that


5-HT2a receptor-binding potentials were lower in the dorsolateral prefrontal 

cortex in individuals with more severe impulsivity and aggression than in healthy 

subjects (Meyer et al., 2008). Lower 5-HT2a binding potentials occur at younger 

ages, when violent behavior is more frequent and is more prominent when 

impulsivity and aggression are more severe. However, this has not been causally 

linked; a low binding potential indicates low ligand-receptor-binding interaction 

and therefore the cause of these reduced binding potentials require further 

investigation. In a novel study led by Soloff et al., gender differences were 

identified in 5-HT2a availability with respect to aggression, negativism, and 

suspiciousness, highlighting a potential for gender biases and a need to control 

for them when conducting research (Soloff et al., 2010). 

Advances in molecular biology and neuroimaging have allowed for 

experimental studies in which 5-HT activity can be altered by tryptophan 

manipulation and subsequent brain activity and behavior monitored. 

These studies have long noted that 5-HT in the central nervous system (CNS), 

as well as in the periphery (e.g., through assessment of 5-HT transporter binding 

sites on the blood platelet) is reduced in aggressive behavior (Coccaro et al., 

2010a). Platelet 5-HTT sites are structurally identical to corresponding sites on 

central 5-HT neurons (Lesch et al., 1993) and are therefore appropriate for further 

hypothesis testing. Preliminary studies by Stoff et al. found that lowered tryptophan 

levels and ingestion of alcohol were associated with increased aggression 

and lower 5-HTT binding (B)byH 3 -imipramine in normal adult males, suggesting 

that low 5-HT levels may be involved in the etiology of aggression and particularly, 

alcohol-induced violence (Pihl et al., 1995). Similarly, Birmaher et al., reported 

that a reduction in platelet H 3 -imipramine (B max ) was associated with aggression in 

children and adolescents (Birmaher et al.,1990). Two studies by Coccaro et al. have 

also demonstrated that the number of 5-HTT binding sites assessed by platelet H 3 - 

paroxetine is inversely related to aggression (Coccaro et al., 1996, 2010b). Individuals 

with IED also had fewer 5-HT transporter platelet binding sites than comparable 

personality disordered subjects without IED; measures of impulsivity did not 

correlate with 5-HTT binding in these studies. 

Animal and clinical studies have highlighted that impulsive aggression 

and its comorbid psychiatric disorders may result from a failure of the 5-HT 

system to communicate properly with other neurotransmitter systems, particularly 

that of dopamine (De Simoni et al., 1987). Specifically, failure of the 

dopamine and serotonin systems to successfully interact in the prefrontal cortex 

may underlie impulsive aggression (Seo et al., 2008). Van Erp and Miczek 

recently reported that increased aggressive behavior in male Long-Evans rats 

was related to both increased dopamine in the nucleus accumbens and reduced 

5-HT levels in the frontal cortex (Van Erp and Miczek, 2000). Previous studies 

have illustrated that serotonergic and dopaminergic systems are tightly linked 

(Daw et al., 2002; Kapur and Remington, 1996; Wong et al., 1995), and it is


thought that subnormal serotonergic function may lead to dopaminergic hyperactivity, 

which in turn leads to impulsive and aggressive behavior (Seo et al., 

2008). 

III. DOPAMINE 

Dopamine (DA) is a catecholamine neurotransmitter that acts both on the central 

and the sympathetic branch of the peripheral nervous systems. DA in the CNS has 

been linked to cognition (Browman et al., 2005; Heijtz et al., 2007), movement 

(Devos et al., 2003), sleep (Dzirasa et al., 2006; Lima et al., 2008), mood (Brown 

and Gershon, 1993; Diehl and Gershon, 1992), attention (Nieoullon, 2002), and 

learning and memory (Arias-Carrión andPöppel, 2007; Denenberg et al., 2004). 

Additionally, DA has developed a well-established and essential role as the 

neurotransmitter responsible for reward pathways involved in drug use (Pettit 

and Justice, 1991; Ranaldi et al., 1999; Weiss et al., 1992), eating (Hernandez 

and Hoebel, 1988), and sexual behavior (Hull et al., 1993; Pfaus et al., 1990). In 

patients with frontotemporal dementia, increased dopaminergic neurotransmission 

and serotonergic modulation of dopaminergic activity is, respectively, associated 

with agitated and aggressive behavior (Engelborghs et al.,2008), suggesting 

DA function contributes to the aggressive behavioral state. While much of what 

we know about dopamine and its biological effects remains to be determined, it is 

clear from the literature and data so far that dopamine is a neurotransmitter with a 

multitude of behavioral, physiological, and psychological capabilities. 

From a molecular perspective, research into DA function in aggressive 

individuals has revealed a spectrum of genetic variability that is linked to a 

number of polymorphisms in DA-specific genes. Led by Elena L. Grigorenko of 

Yale University’s Child Study Center, a coalition of scientists in 2010 found 

positive correlates between genetic polymorphisms in four genes involved in DA 

turnover and behavior pathology (Grigorenko et al., 2010). The four genes 

investigated included catechol-O-methyl-transferase (COMT), involved in catecholamine 

metabolism; dopamine beta hydroxylase (DbH), responsible for 

dopamine conversion; and MAOA and MAOB, both involved in the degradation 

of DA and/or other neurotransmitters. In this study, blood samples from 179 

adolescent offender males sentenced to a juvenile detention center in a large 

capital city in Northern Russia were compared for genetic analysis to those of 

two control groups of Russian male adolescents (n¼182; n¼60). While no 

single dopaminergic polymorphism revealed a definitive causal link to conduct 

disorder, criminality, aggression, or delinquency, combination of variants across 

two (COMT and DbH), three (COMT, DbH, and MAOB), or all four (COMT, 

DbH, MAOA, and MAOB) of the DA-specific genes investigated showed 

positive correlations with the behavioral traits in question. Nemoda et al.


found similar results among patients with borderline personality disorder in a 

separate study done in 2010 using young adults from low-to-moderate income 

households (n¼99) and major depressive or bipolar patients (n¼136) (Nemoda 

et al., 2010). The results of this study found that a promoter variant in the 

dopamine D4 receptor may be involved in the development of BPD traits, 

including aggression. The DA D4 receptor has been postulated as a candidate 

nexus for BPD because of its preferential expression in the prefrontal cortex (Oak 

et al., 2000), and its noted role in novelty-seeking and impulsivity (Munafò et al., 

2008). Data from both experimental groups showed polymorphisms in COMT 

and the DA transporter (DAT1) of the dopamine D2 receptor were directly 

related to self-injurious and impulsive behavior, both BPD traits. Other reports 

have confirmed genetic abnormalities with COMT in the presence of BPD, 

including a recent study citing an over-representation of the low activity Met/ 

Met genotype of the gene in BPD patients (n¼161) (Tadić et al., 2009). 

Interestingly, COMT and DAT1 are similarly implicated in bipolar and major 

depressive disorder (Joyce et al., 2006), suggesting DA dysfunction may encompass 

a much larger behavioral and physiological state. 

In 2008, Couppis and Kennedy published novel findings that found 

dopamine to be a reward for aggressive behavior in mice (Couppis and 

Kennedy, 2008). The authors had hypothesized that aggression could be linked 

to the dopaminergic receptors of the nucleus accumbens (NAc), citing their 

reputation as the most strongly implicated neurotransmitter in positive reinforcement 

(Wise, 2004) and reward behavior. The results of their studies showed 

that administration of a D1-like (D1 and D5) receptor antagonist (SCH-23390), 

or a D2-like (D2, D3, and D4) receptor antagonist (sulperide) into the NAc 

significantly reduced aggression responses when compared to administration 

outside of the NAc. In addition to the reductions in aggression, concomitant 

reductions in mobility were seen in these first studies. These results showing a 

simultaneous reduction in aggression and DA levels were consistent with previous 

reports that had suggested increased DA in the NAc led to increased 

aggression (Van Erp and Miczek, 2000). After Couppis and Kennedy’s initial 

publication, Schwartzer and Melloni reported similar findings that dopamine 

activity primarily mediated by D2 receptors was involved in modulating anabolic/androgenic 

steroid-induced offensive aggression in Syrian hamsters 

(Schwartzer and Melloni, 2010b). Interestingly, administration of the D2-like 

DA antagonist into the anterior hypothalamus (AH) rather than the NAc 

produced no side effects of reduced mobility: in a follow-up experiment, the 

authors reported that treatment of male Syrian hamsters with the D2-like 

receptor antagonist eticlopride in the AH results in dose-dependent suppression 

of aggression behaviors without causing mobility changes (Schwartzer and 

Melloni, 2010a). Conversely, injection of SCH-23390 into the AH reduced 

aggressiveness but showed simultaneous changes in sociability and mobility.


Postmortem studies revealed sparse population of GAD 67 (a GABA production 

marker) neurons distributed within the D5 receptors of the lateral AH. Based on 

these findings, the authors conclude that D5 receptors in the lateral AH modulate 

non-GABAergic pathways that may indirectly influence aggression behavior. 

Future aggression studies should aim to better understand the role of 

dopaminergic activity in the hypothalamus and other limbic structures that are 

in part physiologically responsible for emotion and behavior regulation. 

IV. NOREPINEPHRINE (NORADRENALINE) 

Synthesized from tyrosine-derived dopamine via dopamine decarboxylase and 

b-hydroxylase (Sofuoglu and Sewell, 2009), norepinephrine (NE) is both a 

catecholamine neurotransmitter and a stimulant stress hormone. As a stress 

hormone, NE primarily targets brain regions responsible for attention such as 

the amygdala and works in conjunction with epinephrine (adrenaline) to produce 

the “fight-or-flight” response (Tanaka et al., 2000). During times of high 

stress, this response increases heart rate, releases glucose from energy stores, and 

increases blood flow to skeletal muscle in an attempt to increase the oxygen 

supply to the brain. When released from the locus ceruleus, NE also works to 

actively suppress neuroinflammation that may potentially cause damage to the 

brain (Heneka et al., 2010). 

One of the earliest reports relating aggression to norepinephrine emerged 

in a 1972 publication by Thoa and colleagues in Science magazine (Thoa et al., 

1972). In this study, rats that received an intraventricular injection of 90 mg of 

6-hydroxydopamine (a neurotoxic agent used to selectively target dopaminergic or 

noradrenergic neurons) showed increased shock-induced aggression and reduced 

brain norepinephrine while dopamine levels remained unaltered. This inverse 

relationship between norepinephrine availability and shock-induced aggression 

suggests that the behavioral trait is partially modulated by noradrenergic function. 

In the mid-1980s, Pucilowski and colleagues launched a series of studies that 

confirmed NE was intimately related to aggression. The first paper, dating from 

1985, demonstrated that chemically induced muricide could be in part suppressed 

by norepinephrine (Pucilowski and Valzelli, 1985). A second study, published 

shortly thereafter, showed that bilateral microinjections of hydroxydopamine into 

the nuclei loci coerulei of male Wistar rats resulted in decreased mesencephalic 

and striatal norepinephrine levels as well as marked increased aggression 

(Pucilowski et al., 1986). In 1987, a similar study by the same group gave microinjections 

of the NE-depleting toxin N-(2-chloroethyl)-N-ethyl-2-bromobenzylamine 

(DSP-4) with or without apomorphine into the amygdala. Here, the results


clearly showed that NE was able to markedly reduce apomorphine-induced aggression 

(Pucilowski et al., 1987). The data also showed that norepinephrine significantly 

reduced locomotor activity and to a lesser degree, sensitivity to pain. 

In 1998, a novel research experiment authored by Spivak et al. reported 

that neuroleptic-resistant chronic schizophrenic patients maintained on clozapine 

for 1 year had significantly less aggression (p


schizophrenia (Kantrowitz et al., 2009; Wassef et al., 1999), epilepsy (Snodgrass, 

1992; Treiman, 2001), and pain and nociception (Enna and McCarson, 2006; 

Sawynok, 1984). 

In 2007, researchers at the Model Organism Research Center of the 

Shanghai Institutes for Biological Sciences found that GABA transporter subtype 

1-deficient (or GAT1 / ) mice exhibit lower behavioral aggressiveness compared 

to wild-type mice (Coccaro et al., 1998b). Deficiency in GABA transporter function, 

analogous to inhibition of GABA transporters, leads to an increase in synaptic 

GABA. Later, Takahashi et al. found that pharmacological activation of GABA 

(B), but not GABA(A), receptors in the dorsal raphé nucleus significantly increased 

aggression (Takahashi et al., 2010). The authors theorized that since the majority of 

forebrain 5-HT originates from the raphé nucleus, GABAergic control of this region 

could provide an indirect mechanism for escalations in behavioral aggression. A 

similar study by the same group showed that male CFW mice, treated with the 

GABA(A) receptor agonist muscimol, had increased aggressive tendencies following 

alcohol consumption compared to mice given water. These results demonstrate 

that GABA(A), but not GABA(B), receptors in the dorsal raphé nucleus are one of 

the neurobiological targets of alcohol-induced aggression (Coid et al., 1983), and 

illustrate a functional role for GABA in modulating aggressive behavior. 

In addition to its affiliations with serotonin, it has also been demonstrated 

that GABA is associated with the dopaminergic systems as well and that 

this relationship may influence displays of aggression. GABAergic interneurons 

in various brain regions including the AH are commonly found to express 

dopamine D2 receptors (Gerfen et al., 1990; Santana et al., 2009). Based on 

this observation and the known presence of DA D2 receptors in the AH (Ricci 

et al., 2009), Schwartzer et al. postulated that DA D2 receptor activity may be 

modulating behavioral aggression through direct inhibition of GABA in the AH 

(Schwartzer et al., 2009). The authors found that adolescent male Syrian hamsters 

exposed to anabolic-androgenic steroids had DA-stimulated increased aggression 

marked by the removal of GABAergic inhibition in the lateral AH. 

Human studies of GABA and aggression are limited but include two 

studies in personality disordered subjects from the laboratory of Coccaro et al. In 

the first study, Lee et al. demonstrated a direct relationship between CSF GABA 

and measures of impulsivity and history of suicide attempt (but not aggression) in 

personality disordered subjects (Lee et al., 2008). In the second study, the growth 

hormone (GH) response to the GABA(B) receptor agonist, baclofen, was found 

to be inversely correlated with measures of impulsivity (but not aggression) (Lee 

et al., in press). Taken together, these studies suggest that elevated central 

GABA may lead to, or be associated with, a reduction of GABA(B) receptors 

and that this reduction in downstream GABA(B) mediated activity is associated 

with increased liability to impulsive behavior. As such, these data are consistent 

with the work of Takahashi et al. (2010).


VI. PEPTIDES 

Limited published data suggest relationships between human aggression and 

central vasopressin, oxytocin, and opiates. (Coccaro et al., 1998b) first reported 

a positive correlation between CSF vasopressin concentration and life history of 

aggression in male and female subjects with personality disorders. This relationship 

was confined to males and remained even after the inverse correlation 

between CSF vasopressin and a collateral assessment of serotonin function 

(i.e., PRL response to FEN) was accounted for. Later, Lee et al. (2009) reported 

an inverse relationship between CSF oxytocin and life history of aggression in an 

overlapping group of subjects. CSF vasopressin and CSF oxytocin were inversely 

correlated, but CSF oxytocin continued to be related to aggression even after the 

influence of CSF vasopressin on aggression was controlled for. This lab has also 

noted a positive correlation between CSF Neuropeptide Y and CSF Substance P 

in these same subjects. In addition, circulating levels of metenkephalins have 

been associated with self-injurious behaviors in one study (Coid et al., 1983). 

Postmortem studies of violent suicide victims have found greater number of mu 

receptors in the brain. In healthy volunteers, administration of codeine (Spiga 

et al., 1990) or morphine (Berman et al., 1993) heightened aggression on 

laboratory measures. These studies suggest that increased opioid activity may 

increase the likelihood of aggressive behavior. In fact, naltrexone, an opioid 

antagonist, attenuates self-injurious behavior in autistic and retarded patients 

(Sandman et al., 1990, 2000). 

VII. CONCLUSION 

The neurobiology of aggression is clearly complex. However, we now know more 

about the biological underpinnings of this behavior than ever before and this 

knowledge points the way to possible strategies for treatment. Many agents appear 

to have therapeutic efficacy but many only work on the brain 5-HT system. In the 

upcoming years, we look to the development of agents that work on non-5-HT 

systems (e.g., vasopressin, oxytocin, etc.) so that we may have a more varied 

toolbox with which to treat individuals with problematic aggressive behavior. 

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8 

Human Aggression Across the 

Lifespan: Genetic Propensities 

and Environmental Moderators 

Catherine Tuvblad and Laura A. Baker 

University of Southern California, Los Angeles, California, USA 

I. Heritability of Aggression: Twin and Adoption Studies 

A. Does heritability vary depending on sex 

B. Does heritability change across age 

C. Do heritabilities vary across methods of assessment 

D. Do heritabilities vary across forms of aggression 

E. Does heritability vary depending on study design (twins vs. 

adopted siblings) 

F. Criticisms of twin and adoption studies: Assumptions and 

generalizability 

II. G E Interaction in Aggressive Behavior 

A. Potential moderators of genetic influence found in adoption 

and twin studies 

III. Specific Genes for Aggressive Behavior: Findings from Molecular 

Genetic Studies 

A. G E interaction involving specific genes for aggressive 

behavior 

IV. Conclusions 

References 

ABSTRACT 

This chapter reviews the recent evidence of genetic and environmental influences 

on human aggression. Findings from a large selection of the twin and adoption 

studies that have investigated the genetic and environmental architecture of 



DOI: 10.1016/B978-0-12-380858-5.00007-1

172 Tuvblad and Baker 

aggressive behavior are summarized. These studies together show that about half 

(50%) of the variance in aggressive behavior is explained by genetic influences in 

both males and females, with the remaining 50% of the variance being explained 

by environmental factors not shared by family members. Form of aggression 

(reactive, proactive, direct/physical, indirect/relational), method of assessment 

(laboratory observation, self-report, ratings by parents and teachers), and age of 

the subjects—all seem to be significant moderators of the magnitude of genetic 

and environmental influences on aggressive behavior. Neither study design (twin 

vs. sibling adoption design) nor sex (male vs. female) seems to impact the magnitude 

of the genetic and environmental influences on aggression. There is also some 

evidence of gene-environment interaction (G E) from both twin/adoption 

studies and molecular genetic studies. Various measures of family adversity and 

social disadvantage have been found to moderate genetic influences on aggressive 

behavior. Findings from these G E studies suggest that not all individuals will be 

affected to the same degree by experiences and exposures, and that genetic predispositions 

may have different effects depending on the environment. ß 2011, Elsevier Inc. 

Are all humans innately and equally capable of inflicting harm on others Do we 

learn by our various experiences to manipulate and even harm others for our own 

personal gain; or conversely, to be kind and benevolent, offering help even at 

costs to ourselves Although these fundamental questions pertaining to the 

nature of human aggression have plagued scientists and laypersons for centuries, 

some answers can be found in research spanning the last few decades. 

The early experiments of Milgram (1963) made it clear that, under 

certain circumstances, individuals can be coaxed into aggression and violence. 

The presence of a strict authority and removal of personal responsibility for one’s 

actions can result in aggressive behaviors that inflict harm on others. The 

infamous Stanford prison experiment (Haney et al., 1973) also demonstrated 

that the propensity toward violence and aggression can be elicited—extremely 

and unexpectedly—in situations, where a legitimized ideology and a powerful 

authority can lead to impressionability and obedience. 

Yet, while these powerful studies revealed the importance of social 

factors in inducing aggressive behaviors, not all individuals responded in an 

equally aggressive manner. In Milgram’s (1963) first set of experiments, while 

65% (26 of 40) of participants complied with the instruction to administer what 

they believed to be a final, massive 450-volt shock, the remaining 35% did not 

comply. Many of those who engaged in the aggressive behavior stated they were 

very uncomfortable doing so, and every participant reportedly questioned the 

experiment at some point or refused money promised for their study participation 

(Milgram, 1963). Although the studies by Milgram and Zimbardo provide clear 

evidence for the role of environment and social situations in affecting aggressive 

behavior, there are, nonetheless, large individual differences in the propensity for 

violence and aggression, even under these extreme circumstances.

8. Human Aggression Across the Lifespan 173 

What factors contribute to individual differences in aggression Behavioral 

genetic studies of family members’ resemblance for aggressive behavior help 

shed light on the matter. Twin and adoption studies agree with the experimental 

literature on aggression, which shows that a large effect of environmental factors 

is evident, particularly of the nonshared variety. Yet, there is also plenty of 

evidence, based on a variety of definitions of aggressive behavior from children 

to adults, for genetic propensity toward aggression (see reviews by Burt, 2009; 

Miles and Carey, 1997; Rhee and Waldman, 2002). Although few behavioral 

genetic studies have explicitly examined the question of gene by environment 

(GE) interactions, we contend that such interactions are likely to exist and 

that the genetic propensity for aggression should exert its effects more strongly in 

some situations than others. Consistent with the early findings of Milgram and 

Zimbardo, individual genetic predispositions should moderate the extent to 

which aggression can be elicited, even in extreme situations such as these 

infamous studies. Our view is that while many, if not most, humans may have 

the potential for aggression and violence under the right circumstances, not all 

individuals will succumb to these behaviors under the same circumstances. 

This chapter will review recent evidence of genetic and environmental 

influences on human aggression, with particular attention to several key 

questions and issues. We first consider how estimates of the relative importance 

of genetic effects (i.e., heritability) may vary across forms of aggression and 

the way in which it is measured. As detailed in other chapters of this volume, 

there are numerous definitions of aggression. Some definitions distinguish between 

reactive and proactive forms (Dodge et al., 1997; Raine et al., 2006), and 

others consider direct and indirect forms of aggression (e.g., physical vs. relational; 

Lahey et al., 2004; Tackett et al., 2009). Some definitions may include 

extreme criminal violence, such as assault, rape, and murder, although these 

extreme behaviors are relatively rare and have not been studied extensively in 

genetically informative designs. Measures of aggression can include self-reporting, 

teacher and parent reports (particularly for young children), and official 

records from schools or the justice system. This review focuses on twin and 

sibling adoption studies of aggressive behavior measured as a trait within the 

wider population. We compare effect sizes (heritability) across these various 

definitions and ways of measuring aggression. We also consider how heritability 

estimates may vary across both age and gender. Given higher levels of aggression 

in males across the lifespan, one obvious question concerns whether genetic 

propensities are of greater importance in one sex and how these differences might 

vary across age. We consider a variety of measurable environmental factors that 

might moderate these genetic influences and which may thus lead to GE 

interactions for aggressive behavior. Although direct tests of GE interactions 

have been relatively rare in the behavioral genetic literature on human aggression, 

it is likely that such interactions exist, given their robust effects in other forms of 

antisocial behavior (e.g., property criminal offending; Cloninger et al., 1982).


Finally, we briefly review evidence for specific genetic influences in aggression by 

summarizing some of the more recent findings from molecular genetic studies. 

These effects are reviewed in detail elsewhere in this volume, so our focus here is on 

how a few specific genes may be involved in GE interactions. 

I. HERITABILITY OF AGGRESSION: TWIN AND ADOPTION STUDIES 

Behavioral genetic research relies on the different levels of genetic relatedness 

between family members in order to estimate the relative contribution of heritable 

and environmental factors to individual differences in a phenotype of interest. 

Major research designs include: (a) studies of twins raised together and (b) studies of 

adopted individuals and their biological and adoptive family members. Although 

designs combining both approaches are the most powerful for separating genetic 

and environmental effects in human behavior, such studies of twins separated at 

birth and raised apart are rare and have not studied aggressive behavior extensively. 

Nonetheless, there are a handful of adoption studies and over two dozen studies of 

twins raised together which have specifically examined the genetic and environmental 

influence in aggression in nonselected samples from Northern America and 

Europe that are reasonably representative of the general population. 

In the classical twin design, monozygotic (identical) twins share their 

common environment and they are assumed to share 100% of their genes. 

Dizygotic (fraternal) twins also share their common environment and they are 

assumed to share on average 50% of their genes. By comparing the resemblance 

for aggressive behavior between monozygotic and dizygotic twins, the total 

phenotypic variance of aggression can be divided into additive genetic factors 

(or heritability, h 2 ), shared environmental factors (c 2 ), and nonshared environmental 

factors (e 2 ). Shared environmental factors refer to nongenetic influences 

that contribute to similarity within pairs of twins. Nonshared environmental 

factors are those individual experiences that cause siblings to differ in their levels 

of aggressive behavior. Heritability is the proportion of total phenotypic variance 

due to genetic variation (Neale and Cardon, 1992). Genetic influences may also 

be divided into those that are additive (i.e., allelic effects add up across loci) and 

those that are nonadditive (i.e., due to dominance or epistasis). In twin studies, 

however, it is not possible to estimate both additive and nonadditive genetic 

effects (d 2 ) simultaneously with shared twin environment effects. The twin 

correlations summarized in Table 8.2 can be used to estimate the genetic and 

environmental influences to aggressive behavior. Twice the difference between 

the MZ and DZ correlations provides an estimate of the relative contribution of 

additive genetic influences to aggressive behavior [h 2 ¼ 2(r MZ r DZ )]. The 

contribution of the nonadditive genetic effects due to dominance or epistasis 

(d 2 ) is obtained by subtracting four times the DZ correlation from twice the MZ


correlation (d 2 ¼ 2r MZ 4r DZ ). The proportion of the variance that is due to 

shared environmental influence is given by subtracting the MZ correlation from 

twice the DZ correlation (c 2 ¼ 2r DZ r MZ ). Finally, the contribution of the nonshared 

environmental influences can be obtained by subtracting the MZ correlation 

from unit correlation (e 2 ¼ 1 r MZ )(Posthuma et al., 2003). Many twin 

studies do not specifically examine or test for nonadditive genetic effects and 

instead report heritability estimates based on additive effects only. However, 

some twin studies compare models with additive effects and nonadditive effects 

versus models with additive genetic effects and shared environment. 

In sibling adoption studies, the correlation between adoptive siblings is 

compared with the correlation between biological siblings to estimate the influence 

of genetic and environmental factors on aggressive behavior (Plomin et al., 

2001). Resemblance between adoptive siblings for measures of aggression is 

indicative of shared (or common) family environment, while the extent to 

which biological sibling resemblance exceeds that of adoptive siblings is taken 

as evidence of heritable genetic influences for aggressive behavior. 

There have been a few meta-analyses of twin and adoption studies of 

aggressive behavior and the wider construct of antisocial behavior. In one early 

meta-analysis of 24 twin and adoption studies, heritable influences explained 

about half of the total variance in aggressive behavior and the nonshared environment 

explained the remaining 50% (Miles and Carey, 1997). Rhee and Waldman 

(2002) also summarized the results from 51 twin and adoption studies on criminal 

behavior, delinquency, psychopathy, conduct disorder, and antisocial personality 

disorder, as well as aggressive behavior, in children, adolescents, and adults. 

Genetic factors explained 41% of the variance in antisocial behavior, 16% was 

explained by shared environmental influences, and the remaining 43% of variance 

was explained by nonshared environmental factors. A more recent review focused 

on 19 twin and adoption studies using child and adolescent samples; studies 

including adult subjects were excluded. Heritability was found to explain 65%, 

shared environment explained 5%, and the nonshared environment explained the 

remaining 30% of the variance in aggressive behavior (Burt, 2009). Both Burt 

(2009) and Rhee and Waldman (2002) examined nonadditive genetic effects, but 

only Rhee and Waldman (2002) found significant nonadditive genetic effects for 

antisocial behavior. It is noteworthy that genetic influences are consistently found 

across these reviews, while shared environmental influences are comparatively 

small or nonexistent. Family similarity in aggressive and antisocial behavior, 

therefore, is primarily the result of shared genes, not environment. 

Tables 8.1 and 8.2, respectively, summarize a large selection of twin and 

sibling adoption studies which have specifically examined the genetic and 

environmental influences on aggressive behavior in child, adolescent, and 

adult samples. Several studies use prospective, longitudinal designs, and large 

samples, and three of the twin studies were designed, in particular, to study

Table 8.1. Effect Sizes for Aggressive Behavior from Adoption Studies 

Study 

(author, year) 

Aggression 

measure Informant Age in years Sex 

Biological 

siblings 

r(N) 

Adoptive 

siblings 

r(N) h 2 c 2 

Dutch adoptees 

(van den Oord et al., 1994) 

Dutch adoptees 

(van der Valk et al., 1998) 

Colorado adoptees 

(Deater-Deckard and 

Plomin, 1999) 

Unknown 

(Parker, 1989) a 

Aggression 

(CBCL) 

Aggression 

(CBCL) 

Aggression 

(CBCL) 

Aggression 

(TRF) 

Aggression 

(as reported in Rhee 

and Waldman, 

2002; Burt, 2009) 

Parent ratings 10–15 

Mean¼12.4 

M 

F 

MF 

0.40 (30) 

0.45 (35) 

0.38 (46) 

0.02 (44) 

0.21 (48) 

0.05 (129) 

0.52 

0.32 

0.00 

0.25 

Parent ratings 10–15 MþF 0.42 (111) 0.13 (221) 0.61 0.13 

13–18 MþF 0.36 (152) 0.26 (156) 0.52 0.12 

Parent ratings 7, 9, 10, 11, 12 MþF 0.39 (94) 0.26 (78) 0.24 0.27 

Mean¼9.5 

Teacher ratings MþF 0.25 (188) 0.06 (156) 0.49 0.00 

Parent ratings 4–7 MþF 0.44 (66) 0.47 (45) 

M, Male; F, Female; h 2 , heritability; c 2 , shared environment; CBCL, Child Behavior Checklist (Achenbach, 1991b); TRF, Teacher Report Form 

(Achenbach, 1991a). 

a Genetic and shared environmental estimates were not reported by the authors.

Table 8.2. Effect Sizes (Correlations) for Aggressive Behavior from Twin Studies 

Study sample 


Aggression measure 

Assessment 

method Age in years Sex 

MZ 

r(N) 

DZ 

r(N) h 2 c 2 Sex limitation effects 

Boston twins 

Aggression 

Parent ratings 6–10 F 0.35 (24) 0.08 (28) 0.40 a – N/A 

(Scarr, 1966) 

(ACL) 

Missouri twins 

Aggressive reaction Lab observation 6–14 M 0.09 (10) 0.24 (11) 0.44 a – Not tested 

(Owen and Sines, 

1970) 

(MCPS) 

F 0.58 (8) 0.22 (13) 

California twins Aggression 

Self-report 42–56 M 0.31 (93) 0.21 (97) 0.56 a – N/A 

(Rahe et al., 1978) (ACL) 

Mean¼48 

Colorado twins 

Aggression/bullying Parent ratings Mean¼7.6 M þF 0.72 (52) 0.42 (32) – – Not tested 

(O’Connor et al., 1980) (PSR) 

London twins, UK Aggression 

Self-report 19–60 MþF 0.40 (296) 0.04 (179) 0.72 a Not tested 

(Rushton et al., 1986) (IBS) 

Mean¼30 

California preschool Aggression 

Parent ratings Mean¼5.2 M þF 0.78 (21) 0.31 (17) 0.94 a – Not tested 

twins 

(CBCL) 

Ghodesian-Carpey and Aggression 

Mothers’ Mean¼5.2 M þF 0.65 (21) 0.35 (17) 0.60 a – 

Baker, 1987 

(MOCL) 

observations 

Philadelphia twins Impatience/aggression Teacher rating 6–11 M þF 0.67 (71) 0.11 (34) 1.12 a – Not tested 

(Meininger et al., 

1988) 

Competitive achievement 

striving 

0.63 (71) 0.13 (34) 1.00 a – 

Minnesota twins Aggression 

Self-report Mean¼19.8 M þF 0.61 (79) 0.09 (48) Not tested 

(McGue et al., 1993) c (MPQ) 

Aggression 

Self-report Mean¼29.6 M þF 0.58 (79) 0.14 (48) Not tested 

(MPQ) 

Midwest twins BDHI—assault Self-report Mean¼42.5 F 0.07 (77) 0.41 (21) 0.00 – N/A 

(Cates et al., 1993) BDHI—indirect Self-report Mean¼42.5 F 0.40 (77) 0.01 (21) 0.78 – N/A 

hostility 

BDHI—verbal Self-report Mean¼42.5 F 0.41 (77) 0.06 (21) 0.70 – N/A 

hostility 


(Schmitz et al., 1995) 

Aggression 

(CBCL) 

Parent rating 2–3 

4–11 

MþF 0.68 (77) 

0.79 (66) 

0.40 (183) 

0.41 (137) 

0.52 

0.55 

0.16 

0.19 

Not tested 

(Continues)

Table 8.2. (Continued) 

Study sample 


Ohio twins, Western 

Reserve Twin Project 

(Edelbrock et al., 1995) 

Dutch twins 

(van den Oord et al., 

1996) 

Minnesota twins 

(Finkel and McGue, 

1997) 


Aggression 

(CBCL) 

Aggression 

(CBCL) 

Aggression 

(MPQ) 

Assessment 


Parent rating 7–15 

Mean¼11.0 

Parent rating 3 M 

F 

MF 

Self-report 27–64 

Mean¼37.8 

MZ 

r(N) 

DZ 


MþF 0.75 (99) 0.45 (82) 0.60 0.15 Not tested 

M 

F 

MF 

0.81 (210) 

0.83 (265) 

0.37 (220) 

0.39 (406) 

0.49 (236) 

0.49 (238) 

0.45 (409) 

0.12 (165) 

0.14 (352) 

0.12 (114) 

0.69 0.12 Not tested 

VET twins BDHI—assault Self-report Mean¼44.1 M 0.50 (182) 0.19 (118) 0.47 0.00 N/A 

(Coccaro et al., 1997) BDHI—indirect Self-report M 0.42 (182) 0.02 (118) 0.40 0.00 N/A 

hostility 

BDHI—verbal Self-report M 0.28 (182) 0.07 (118) 0.28 0.00 N/A 

hostility 

Swedish twins (TCHAD; 

Eley et al., 1999) 

Aggression 

(CBCL) 

0.72 (176) 

0.82 (160) 

UK twins (sample 

obtained from Register 

of Child Twins; Eley 

et al., 1999) 

Virginia twins 

(Simonoff et al., 1998) 

Aggression 

(CBCL) 

Aggression 

(physical) 

Parent rating 8–9 M 

F 

MF 

Parent rating 12 M 

F 

MF 

0.68 (99) 

0.77 (124) 

0.41 (182) 

0.45 (194) 

0.41 (310) 

0.45 (93) 

0.44 (80) 

0.27 (95) 

0.35 

0.39 

0.00 

0.00 

NS quantitative sex 

differences 

0.70 0.07 NS quantitative sex 

differences, 

NS qualitative sex 

differences 


differences, 


differences 

Parent rating 8–16 MþF 0.76 (268) 0.46 (166) 0.58 0.18 Not tested 

Self-report 8–16 MþF 0.31 (268) 0.22 (166) 0.21 0.11 Not tested

Missouri twins 

(Hudziak et al., 2000) 

Dutch twins 

(Hudziak et al., 2003) 

Dutch twins 

(van Beijsterveldt 

et al., 2003) c 

Canadian twins 

(Dionne et al., 2003) 

UK (E-risk) twins 

(Taylor, 2004) 

South Wales twins 

(Button et al., 2004) 

Finnish twins 

(Vierikko et al., 2004) 

Aggression 

(CBCL) 

Aggression 

(TRF) 

Aggression 

(CBCL) 

Aggression 

(physical) 

Aggression 

(CBCL) 

Aggression 

(IAB) 

Aggression 

(MPNI) 


F 

0.77 (129) 

0.73 (91) 

0.50 (156) 

0.40 (115) 

0.77 

0.70 

0.00 Not tested 

Teacher rating 7 M 0.72 (181) 0.33 (160) 

F 0.71 (214) 0.33 (151) 

MF 

0.26 (330) 

10 M 0.73 (153) 0.41 (140) 0.72 0.00 

F 0.73 (202) 0.25 (125) 0.21 0.49 

MF 

0.17 (283) 

Parent rating 3 M 0.81 (1055) 0.55 (1066) 

F 0.82 (1226) 0.53 (997) 

MF 

0.48 (2144) 

7 M 0.83 (927) 0.48 (1069) 

F 0.84 (898) 0.53 (858) 

MF 

0.51 (1723) 

10 M 0.84 (526) 0.50 (621) 

F 0.79 (471) 0.55 (458) 

MF 

0.47 (907) 

12 M 0.86 (289) 0.45 (317) 

F 0.83 (237) 0.55 (233) 

MF 

0.57 (433) 

Parent rating 1.5 MþF 0.59 (107) 0.28 (174) 0.58 0.00 Not tested 


differences 

Parent rating 5 MþF 0.73 (602) 0.24 (514) 0.72 0.00 Not tested 

Significant quantitative 

sex differences 










Mean¼13.8 

MþF 0.64 (115) 0.40 (143) 0.68 0.00 Not tested 

Parent rating 12 M 0.72 (260) 0.59 (292) 0.14 0.75 Significant quantitative 

F 0.78 (300) 0.53 (278) 0.54 0.25 sex differences 

MF 

0.58 (517) 

(Continues)


Study sample 


Dutch twins 

(Polderman et al., 

2006) 


(Haberstick et al., 

2006a) 


Aggression 

(TRF) 

Aggression 

(CBCL) 

Aggression 

(TRF) 

Assessment 


MZ 

r(N) 

DZ 


Teacher rating 5 MþF 0.84 (67) 0.43 (59) 0.49 0.00 Not tested 

(same teacher) 

Teacher rating 

(different 

teachers) 

5 MþF 0.40 (45) 0.21 (44) 

Parent rating 7 b M 0.74 (69) 0.56 (76) 0.79 0.00 NS quantitative sex 

F 0.79 (91) 0.44 (62) 

differences 

9 M 

F 

10 M 

F 

11 M 

F 

12 M 

F 

Teacher rating 7 M 

F 

8 M 

F 

9 M 

F 

10 M 

F 

11 M 

F 

12 M 

F 

0.57 (73) 

0.76 (75) 

0.77 (58) 

0.70 (67) 

0.64 (58) 

0.86 (56) 

0.68 (69) 

0.83 (78) 

0.63 (71) 

0.56 (79) 

0.58 (66) 

0.70 (70) 

0.54 (63) 

0.67 (74) 

0.39 (63) 

0.49 (64) 

0.56 (68) 

0.50 (70) 

0.35 (55) 

0.48 (60) 

0.50 (63) 

0.55 (60) 

0.47 (52) 

0.56 (57) 

0.41 (55) 

0.59 (49) 

0.45 (61) 

0.45 (65) 

0.39 (70) 

0.34 (62) 

0.46 (62) 

0.41 (60) 

0.29 (59) 

0.37 (53) 

0.44 (56) 

0.18 (54) 

0.12 (54) 

0.45 (54) 

0.32 (39) 

0.24 (49) 


differences 


differences 


differences 


differences 


differences 


differences 


differences 


differences 


differences 


differences

Ad-Health 

(Cho et al., 2006) 


(Gelhorn et al., 2006) 

Finnish twins 

(von der Pahlen et al., 

2008) 

Norwegian twins 

(Czajkowski et al., 

2008) 

Tennessee twins 

(Tackett et al., 2009) 

California twins—RFAB 

cohort (Baker et al., 

2008) 

Aggression Self-report 12–19 M 

F 

MF 

Aggression 

Self-report 11–18 MþF 

(DISC items) 

Mean¼14.5 MF 

Aggression 

(BPAQ) 

Passive 

aggression 

(DSM-IV) 

Relational aggression 

(CAPS) 

Reactive aggression 

(RPQ) 

Self-report 18–33 M 

F 

MF 


Mean¼28.2 

M 

F 

MF 

Self- report 9–18 M 

F 

MF 


F 

MF 


F 

MF 


F 

MF 

Teacher rating 9–10 M 

F 

MF 

0.47 (141) 

0.47 (141) 

0.29 (131) 

0.27 (114) 

0.21 (197) 

0.47 (531) 0.27 (569) 

0.28 (212) 

0.45 (190) 

0.52 (608) 

0.35 (221) 

0.30 (448) 

0.54 (356) 

0.41 (376) 

0.66 (356) 

0.65 (376) 

0.48 (141) 

0.60 (142) 

0.38 (138) 

0.37 (139) 

0.59 (67) 

0.70 (68) 

0.22 (167 

þ321 sibs) 

0.18 (387 

þ1838 sibs) 

0.20 (508 

þ1559 sibs) 

0.45 (116) 

0.19 (261) 

0.21 (340) 

0.39 (328) 

0.36 (332) 

0.16 (589) 

0.61 (328) 

0.35 (332) 

0.48 (589) 

0.35 (87) 

0.46 (98) 

0.50 (151) 

0.28 (83) 

0.38 (96) 

0.08 (146) 

0.49 (45) 

0.43 (45) 

0.60 (62) 

0.50 

0.30 

0.00 

0.00 

Not tested 

0.49 0.00 Not tested 

0.70 

0.69 

0.00 

0.00 

Not tested 


differences, 


differences 


differences 

0.21 

0.42 

0.46 

0.22 




differences 

0.38 

0.00 

0.00 

0.36 




differences 

(Continues)


Study sample 



Assessment 


MZ 

r(N) 

DZ 


California twins—RFAB 

cohort (follow-up) 

(Tuvblad et al., 2009) 

Weighted average 

Proactive aggression 

(RPQ) 

Reactive aggression 

(RPQ) 

Proactive aggression 

(RPQ) 


F 

MF 


F 

MF 

Teacher rating 9–10 M 

F 

MF 


F 

MF 


F 

MF 

M 

F 

MF 

MþF 

0.61 (141) 

0.57 (142) 

0.60 (138) 

0.12 (139) 

0.56 (67) 

0.74 (68) 

0.49 (102) 

0.58 (98) 

0.55 (102) 

0.46 (98) 

0.66 

0.63 

0.59 

0.34 (87) 

0.48 (98) 

0.55 (151) 

0.34 (83) 

0.28 (96) 

0.14 (146) 

0.42 (45) 

0.38 (45) 

0.35 (62) 

0.33 (55) 

0.38 (77) 

0.42 (103) 

0.35 (55) 

0.27 (77) 

0.40 (103) 

0.42 

0.35 

0.38 

0.28 


differences 

0.50 

0.00 

0.00 

0.14 




differences 


differences 


differences 

MZ, monozygotic; DZ, dizygotic; M, male twin pairs; F, female twin pairs; MF, male–female twin pairs; MþF, male and female pairs combined; h 2 , heritability; c 2 , shared 

environment; CBCL, Child Behavior Checklist (Achenbach, 1991b) [20 items scored as 0 (not true), 1 (somewhat true), and 2 (very true), e.g., bragging and boasting, argues a 

lot, cruelty or meanness to other, disobedience (home and school)]; MOCL, Mothers’ Observational Checklist, including the following behaviors: rejection, destructiveness, 

negativism, noncompliance, teasing, physical negative, insult, verbal threat, yelling; ACL, Adjective Checklist (Gough, 1960) [consists of 300 adjectives that yields 26 scales]; 

MCPS, Missouri Children’s Picture Series (Sines et al., 1966) [consists of 238 line drawings, each portrays the figure of a child engaged in some activity or situation, the subject is 

required to sort the cards into two groups, those that look like fun and those that do not look like fun]; PSR, Parent Symptom Ratings (Conners, 1970) [includes six aggression 

items: bullying, hits or kicks other children, mean, sassy to grown-ups, fights constantly, picks on other children]; IBS, Interpersonal Behavior Survey (Mauger, 1980) [includes

items such as: “some people think I have a violent temper” or “I try not to give people a hard time”]; The Mathews Youth Test for Health (MYTH; Mathew and Angulo, 1980) 

[developed to measure Type A behavior in school-aged children. The instrument consists of 17 items characterized by overt type A behavior and yields two subscales: impatience/ 

aggression and competitive achievement striving]; BDHI, Buss-Durkee Hostility Inventory (Buss and Durkee, 1957) [contains of three subscales: the assault scale (10 items on 

physical aggression), the verbal hostility scale (13 items on verbal aggression), and the indirect hostility scale (nine items on indirect or undirected or displaced aggression)]; 

MPQ, Minnesota Personality Questionnaire (Tellegen, unpublished) [physically aggressive, vindictive, likes violent scenes, higher order factor, negative emotionality]; Physical 

Aggression scale, (Simonoff et al., 1998) [items on physical aggression, extortion, public fight, use of weapon in a fight, cruelty to animal, thrown objects at people, carried a 

weapon, sworn at teacher, based on Olweus, 1989]; Physical Aggression scale (Dionne et al., 2003) is a 37 item check list on which parents reported whether the child engaged, 

sometimes engaged, often engaged in a behavior. Based on factor analysis, 10 of the 37 behaviors were determined as direct physical aggression, for example, is cruel toward others, 

bullies other children, bites others, kicks, fights, takes things away from others, pushes, threatens to hit; IAB, instrument of aggressive behavior (Olweus, 1989) [contains two 

subscales: aggressive and nonaggressive antisocial behavior. The aggression scale contains 11 items of direct verbal and physical aggression, e.g., swearing at a teacher, bullying]; 

MPNI, Multidimensional Peer Nomination Inventory (Pulikkined et al., 1999) [contains of 38 items and the aggression subscale contains of six items, e.g., calls people names, 

may hurt other kids, bullying, goes around telling people’s secrets to others]; Ad-Health [aggression is based on four items, got into a serious physical fight, hurt someone badly 

enough they needed medical care, used to threaten to use a weapon to get something from someone, took part in a gang fight]; DISC, Diagnostic Interview Schedule for Children 

(Shaffer et al., 2000) [Gelhorn et al. (2006) only included aggression to people or animals, items 1–7]; BPAQ, Buss and Perry Aggression Questionnaire (Buss and Perry, 1992) 

[nine items on physical aggression and five items on verbal aggression, e.g., I cannot help getting into arguments when people disagree with me, I have threatened people I know, I 

get into fights a little bit more often than average people]; DSM-IV, the Norwegian version of the Structured Interview for DSM-IV personality (Pfohl et al., 1997) [the 

instrument is a semi-structured diagnostic interview for the assessment of all DSM axis II disorders, including passive-aggressive personality disorder]; CAPS, Child and 

Adolescent Psychopathology Scale (Lahey et al., 2004) [relational aggression was assessed via the CAPS, a structured interview assessing DSM-IV symptoms of common 

childhood disorders. Seven items measured relational aggression, for example, tried to keep kids he/she does not like outside his/her friend group, spread rumors to make others 

stop liking someone, stopped talking to people because he/she was mad at them, teased other people in a mean way]; RPQ, Reactive and Proactive Questionnaire (Raine et al., 

2006). [The RPQ is a validated 23-item questionnaire designed to measure reactive and proactive aggression in children and adolescents from the age of 8. The RPQ includes 11 

reactive items (e.g., “he/she damages things when he/she is mad”; “he/she gets mad or hits others when they tease him/her”) and 12 proactive items (e.g., “he/she threatens and 

bullies other kids”; “he/she damages or breaks things for fun”). The items in the RPQ have a three-point response format: 0¼never, 1 ¼sometimes, 2 ¼often.]; RFAB, USC twin 

study of Risk Factors for Antisocial Behavior; TCHAD: Twin Study of Child and Adolescent Development. 

a Heritability estimate is based on either Holzingers’ H or Falconer equation and did not report shared environmental influences. 

b Parent reported CBCL ratings were not collected at age 8. 

c Genetic and shared environmental estimates were not reported by the authors.


aggressive and antisocial outcomes. All three of these studies are ongoing. One of 

these is the University of Southern California Twin Study of Risk Factors for 

Antisocial Behavior (RFAB), which is a prospective study of the interplay of 

genetic, environmental, social, and biological (psychophysiological) factors on 

the development of antisocial and aggressive behavior from childhood to emerging 

adulthood. The project includes more than 750 twin pairs studied on several 

occasions, at ages 9–10, 11–13, 14–16, and 17–18 years (Baker et al., 2006). A 

second major twin study is the Environmental Risk Longitudinal Twin Study (Erisk 

study) in the United Kingdom. The E-risk study involves data on more than 

1000 twin pairs at ages 5, 7, and 12 with the special focus on what factors in the 

home, family, school, and neighborhood (i.e., environmental risks) promote children’s 

aggression (Moffitt, 2002). The Minnesota Study of Twins and Families 

(MFTS) is a third major longitudinal twin study that specifically investigates 

antisocial behavior and substance use across development. MTFS was established 

in 1989 using same-sexed twin pairs aged 11 or 17. Five hundred additional 11-yearold 

twin pairs were added in 2000. All twins of those ages, who were born in 

Minnesota, as identified by birth registry data, were invited to participate. Participants 

are asked about academic ability, personality, and interests; family and social 

relationships; mental and physical health; and physiological measurements. Of 

particular interest are prevalence of psychopathology, substance abuse, divorce, 

leadership, and other traits and behaviors related to mental and physical health, 

relationships, and religiosity (Iacono et al., 2006; Keyes et al.,2009). 

Before reviewing the twin and sibling adoption studies on aggressive 

behavior presented in Tables 8.1 and 8.2, it is important to consider the ways in 

which the phenotype of aggressive behavior is defined and measured. The various 

instruments utilized in the studies reviewed in this chapter are summarized in 

Tables 8.1 and 8.2, to provide a clear idea of the nature of the aggressive behavior 

phenotype being investigated. By and large, the Child Behavior Checklist 

(CBCL; Achenbach, 1991b) has been used more often than any other single 

instrument in behavioral genetic studies of aggression. Although self-report 

version of the CBCL is available for older adolescents and young adults (Youth 

Self Report (YSR); Achenbach, 1991c), studies more commonly rely on parent 

or teacher (Teacher’s Report Form (TRF); Achenbach, 1991a) rating versions. 

The aggressive behavior subscale of the CBCL includes 20 items on which the 

child is rated. These include defiance, argumentativeness, physical aggression, 

and cruelty toward others. Although there are a handful of other instruments 

that also yield single aggressive behavior scores, two instruments provide multiple 

scales: the Reactive and Proactive Aggression Questionnaire (RPQ; Raine 

et al., 2006), which provides separate scales for aggressive reactions to provocation 

and more planned or proactive forms of aggression; and the Buss-Durkee 

Hostility Inventory (BDHI; Buss and Durkee, 1957), which yields several subscales 

of aggression, including assault, verbal, and indirect hostility.


The studies summarized in Tables 8.1 and 8.2 vary on how aggressive 

behavior was defined (i.e., physical, verbal, relational, reactive, proactive, indirect, 

bullying) and measured (observation, self-report, parent/caregiver, teacher). A 

wide range of ages were included, from preschool children to adults; however, 

the vast majority of studies have used childhood samples (i.e., 12 years of age or 

younger) which explains why the CBCL is so frequently used to assess aggressive 

behavior. Correlations for biological and adoptive siblings (Table 8.1), and MZ 

and DZ twins (Table 8.2) are shown for each study. Most studies reported correlations 

separately for same-sex pairs of males (M), females (F), and opposite-sex pairs 

(MF); however, a few studies involve correlations for samples of male and female 

pairs combined. We review the key questions concerning the genetic influence 

(heritability) of human aggression based on the effect sizes reported for these 

studies. We also examine various potential moderators of these effects, including 

sex, age, method of assessment, form of aggression, study design (twin vs. sibling 

adoption design), and various social factors and circumstances that may exacerbate 

or ameliorate the genetic risk for aggression from one person to the next. 

A. Does heritability vary depending on sex 

Since it is well documented that males are much more likely than females to 

engage in most forms of aggressive behavior (Moffitt et al., 2001; Rutter et al., 

2003), it is also of interest to examine whether the same genetic and environmental 

influences are important in both sexes and whether the magnitude of 

these effects differs between males and females. 

In the classical twin design, genetic and environmental variance components 

for aggressive behavior can be estimated using data from same-sex MZ 

and DZ twins. Apart from estimating genetic and environmental effects on 

aggression, it is also possible to investigate whether sex-specific genetic or 

environmental influences are important. Such effects are referred to as sexlimitation 

or sex-limited effects. There are two primary questions about sex 

limitation in genetic research, one being whether there are qualitative differences 

between males and females, such that different genes and/or environmental 

influences operate in the two sexes, and whether quantitative differences exist 

in the relative magnitude of influences across sexes. To assess whether the 

magnitude of genetic and environmental effects in aggressive behavior differ 

between males and females (i.e., quantitative sex differences), only data from 

same-sex twin pairs are required. However, to determine whether or not it is the 

same set of genes or shared environmental experiences that influences aggressive 

behavior in males and females (i.e., qualitative sex differences), data from 

opposite-sex twin pairs are also needed. If qualitatively different genetic influences 

are important for aggressive behavior in males and females, then the 

opposite-sex twins will be less genetically similar for the trait than DZ twins.


Not all twin studies have examined sex-limited effects, either qualitative 

or quantitative, and several studies combined males and females when 

computing twin correlations, making it impossible to evaluate these effects 

based on published results shown in Table 8.2. Nonetheless, quantitative sex 

differences can be easily evaluated across at least 18 studies in Table 8.2, which 

present separate twin or sibling correlations by sex. Among these, there are a 

dozen studies that also include MF, which allow investigation of qualitative sex 

differences. The average twin correlations across these 18 studies, weighted by 

their respective sample sizes, shows quite similar twin correlations for both 

identical (r MZ Males ¼0.66; r MZ Females ¼0.63) and nonidentical same-sex pairs 

(r DZ Males ¼0.42; r DZ Females ¼0.35), indicating that there are no appreciable 

quantitative sex differences in aggressive behavior. This is consistent with the 

individual results across studies which formally tested for quantitative sex differences 

(e.g., Baker et al., 2008; Czajkowski et al., 2008; Eley et al., 1999; Finkel 

and McGue, 1997; Tackett et al., 2009; Tuvblad et al., 2009). As indicated in 

Table 8.2, only a small handful of studies have reported significant differences in 

heritability of aggression for males and females (and these are primarily for 

younger samples; e.g., Hudziak et al., 2003; van Beijsterveldt et al., 2003; 

Vierikko et al., 2004). The lack of quantitative sex differences is also well in 

line with what was reported in a recent meta-analysis summarizing 19 twin and 

family/adoption studies, whereby genetic influences were found to explain 54% 

of the variance in aggressive behavior in boys and 57% of the variance in girls 

(Burt, 2009). 

There is no evidence of qualitative sex differences either, given that the 

weighted twin correlation for MF (DZ Male Female ) is 0.38, which is quite similar 

to the same-sex DZ twin correlations (0.42 in males and 0.35 in females). 

In spite of the consistent sex difference in mean levels of aggression, the 

underlying etiologies of aggressive behavior appear to be remarkably similar for 

both sexes. There may still be biological and social differences between the sexes 

that might account for the greater mean levels of aggression observed in males, 

yet the same genes and the same environmental factors appear to explain 

individual differences in aggression within each sex to the same degree. One 

interesting question that has not been addressed, however, is to what extent 

there may be sex differences in moderators of genetic factors. In other words, 

there may be different circumstances or experiences in males and females that 

lead to greater expression of genetic predispositions for aggression. For example, 

sexual jealousy might trigger genetic propensity for aggression to a greater extent 

in males than females, while threats to resources might be a more important 

moderator of genetic influences in females compared to males, as discussed 

in Chapter 9. Other moderators are discussed later in II.A, although more 

research is clearly warranted to explore the degree to which they may be sex 

specific.


B. Does heritability change across age 

Although genetic studies of aggression have spanned from childhood to adulthood, 

most studies included in Tables 8.1 and 8.2 involved children 12 years of 

age or younger. This suggests that more studies examining the heritability of 

aggressive behavior in adolescents and adults are needed. Keeping this in mind, it 

is useful to examine the magnitude of twin correlations across age groups, which 

span from early childhood to middle-age adults. These correlations are summarized 

in Fig. 8.1, according to five age groups (early childhood, age 1.5–6 years; 

middle childhood, age 7–10; adolescence 11–15; late adolescence/young adulthood, 

age 16–26; and adulthood, age 27–48; Fig. 8.1). These results show that 

aggressive behavior is clearly influenced by genetic factors across the lifespan, 

given the fact that the MZ correlations exceed those for DZ pairs at all ages. (The 

Twin correlations across age groups (all studies) 

0.80 

Mean twin correlation 

0.60 

0.40 

0.20 

0.00 

Early 

childhood 

(1.5–6) 

Middle 

childhood 

(7–10) 

Adolescence 

(11–15) 

Late 

adolescence/ 

young adult 

(16–26) 

Adult 

(27–48) 

Age group 

Zygosity 

MZ DZ same–sex DZ male–female 

Figure 8.1. Twin correlations across age groups (all studies).


lack of qualitative sex differences is also evident across the life span, in that the 

DZ correlation is comparable for same-sex and MF pairs across ages.) However, 

both MZ and DZ correlations decline steadily across development, suggesting the 

waning importance of shared environmental effects from childhood to adolescence 

and then adulthood. The DZ correlation exceeds half the value of the MZ 

correlation (taken as evidence for shared environment) only in early childhood, 

but not in later age groups. The pattern shown in Fig. 8.1 is evident in individual 

studies as well. Aggressive behavior in childhood is influenced by genetic factors 

in all studies, and most of these studies also report shared environmental influences 

(Table 8.2; e.g., Baker et al., 2008; Eley et al., 1999; Hudziak et al., 2003; 

Schmitz et al., 1995; Simonoff et al., 1998; Tuvblad et al., 2009; van den Oord 

et al., 1996; Vierikko et al., 2004; but for an exception see Dionne et al., 2003; 

Taylor, 2004). Studies including adolescent twins (younger than 19 years of 

age) do not in most cases report finding any shared environmental influences 

(Table 8.2; e.g., Button et al., 2004; Cho et al., 2006; Gelhorn et al., 2006; 

Tackett et al., 2009). Similarly, studies including adult twins do not report 

finding any shared environmental influences (Table 8.2; e.g., Coccaro et al., 

1997; Finkel and McGue, 1997; von der Pahlen et al., 2008; but for an exception 

see Czajkowski et al., 2008). The overall pattern across the studies presented in 

Table 8.2 and Fig. 8.1 indicates that genetic influences for aggressive behavior 

become increasingly more important, while shared environmental effects become 

less so as children develop from childhood, through adolescence, and into 

adulthood. Similarly, findings from a recent meta-analysis reported that genetic 

influences increased from 55.2% at ages 1–5 years to 62.7% at ages 6–10 years 

and 62.9% at ages 11–18 years. At the same time, shared environmental influences 

were decreasing from 18.7% at ages 1–5 years to 13.9% at ages 6–10 years 

and 2.7% at ages 11–18 years (Burt, 2009). This pattern of decrease in shared 

environment, and a concomitant increase in heritability during development, is 

relatively common for personality traits and cognitive abilities (Bartels et al., 

2002; Loehlin, 1992; Plomin et al., 2001; Scarr and McCartney, 1983), and has 

also been found for other phenotypes including prosocial behavior (Knafo and 

Plomin, 2006). 

It should also be kept in mind, however, that methods of assessing 

aggression vary across age, such that studies of children tend to rely on ratings 

by teachers and parents, while studies of adults (and some older adolescents) rely 

more heavily on self-report methods. The confound between method of assessment 

and age of the subjects has made it difficult in prior studies and metaanalyses 

to disentangle age effects on heritability from differences that arise from 

different methods of assessment. Increasing heritability estimates from child to 

adulthood could therefore also be explained by different methods of assessment 

as well (e.g., parental bias may lead to overestimation of shared environmental 

effects and thus attenuate heritability estimates in childhood).


C. Do heritabilities vary across methods of assessment 

It is important to examine the magnitude of twin correlations across methods of 

assessment, as heritability estimates may vary depending on who is rating the 

subject. This is especially important given the age trends found for heritable 

influences in Fig. 8.1, since different methods of assessment tend to be employed 

for different age groups. As previously discussed, studies of younger subjects rely 

on parent or teacher ratings, while self-report methods are typically used in studies 

of adults and often adolescents. The twin correlations are summarized in Fig. 8.2, 

according to laboratory observation, self-reports, teacher ratings, and parent/ 

caregiver ratings. Indeed, twin correlations—and thus the estimates of genetic 

and environmental influences on aggressive behavior—do appear to vary across 

method of assessment. According to the twin correlations summarized in Fig. 8.2, 

the heritability of aggressive behavior based on laboratory observation is approximately 

32% [h 2 :2(r MZ r DZ )¼2(0.27 0.11)], dominant genetic effect accounts 

for approximately 10% [d 2 :2(r MZ r DZ )¼2(0.27)–4(0.11)], and the nonshared 

0.8 

Twin correlations across method of assessment (all studies) 

0.7 

0.6 

0.5 

0.4 

0.3 

0.2 

0.1 

0 

Observation Self-report Teacher Parent 

MZ DZ same-sex DZ male-female 

Figure 8.2. Twin correlations across method of assessment (all studies).


environment accounts for the remaining 58% of the variance. The heritability of 

aggressive behavior based on self-reports is 40% and the nonshared environment 

accounts for the remaining 60% of the variance. There is no evidence of shared 

environmental contribution, as the DZ correlation is approximately half the MZ 

correlation. The heritability of aggressive behavior based on teacher ratings is 

54%, shared environmental influences account for 6% [c 2 :2r DZ r MZ ¼2(0.33 

0.60)], and the nonshared environment accounts for the remaining 40% of the 

variance. The heritability of aggressive behavior based on parent/caregiver ratings 

is 54%, shared environmental influences account for 17%, and the nonshared 

environment accounts for the remaining 29% of the variance. Thus, parent/ 

caregiver ratings have the largest familial influence, explaining 71% of the 

variance (h 2 þc 2 ¼0.54%þ17%) in individual differences in aggressive behavior. 

It should be kept in mind that this is a descriptive approach and that formal 

modeling is required to determine how well these estimates describe the observed 

data. Also, this approach does not allow for actual testing of different hypotheses, 

for example, to test whether it is possible to set any of these effects to zero. It is 

difficult to discern whether the parent/caregiver rating patterns reflect true shared 

environment or are instead an artifact of rater bias whereby raters are less able to 

discriminate between the two twins’ aggressive behavior and thus inflate the 

similarities between them, regardless of zygosity. In fact, when the two co-twins 

are rated by different teachers (e.g., they are in different classrooms), twin 

correlations are lower for both MZ and DZ pairs for the wider construct of 

antisocial behavior (Baker et al., 2007). 

A few specific twin studies in Table 8.2, which utilize multiple raters in 

their design, also illustrate that genetic and environmental influences on aggressive 

behavior vary depending on method of assessment. For example, twin 

similarity for relational aggression was influenced only by genetic factors when 

using self-reported data, explaining 49% of the total variance. When using parent 

ratings (only biological mothers were used as raters) of relational aggression both 

genetic and shared environmental influences were important (boys: h 2 ¼21%, 

c 2 ¼46%, e 2 ¼33%; girls: h 2 ¼42%, c 2 ¼22%, e 2 ¼36%). However, when using 

youth self-reports, only genetic and nonshared environmental influences were 

significant (h 2 ¼49%, e 2 ¼51%; Tackett et al., 2009). A similar pattern was found 

for reactive and proactive aggression in 9–10-year-old boys, whereby only genetic 

influences were important for self-reports, but both genes and shared environment 

were important for teacher and parent ratings (Baker et al., 2008). Aggressive 

behavior in another sample of twins aged 7–12 years was found to be largely 

influenced by genetic (or familial) factors (76%–84%), as reported by parents. 

Data were collected from one or both parents; however, only mother-reported 

ratings were included in the analyses, as they accounted for the majority of the 

ratings collected (85.3%–90.1%). In contrast, when teacher ratings were used, 

aggressive behavior was found to be slightly less influenced by genetic (or familial)


factors (42%–61%; Haberstick et al., 2006a). Significant shared environmental 

effects were not found for either parent or teacher ratings, and were therefore 

dropped from the models, suggesting that any shared environmental influences 

are likely to be included in the genetic component. Apart from rater bias, which 

may result in inflated twin similarity across the board when using single raters for 

multiple children, the varying patterns of genetic and environmental influence 

across methods of assessment could be the result of different raters reporting 

different aspects of the child’s aggressive behavior. This could arise in part because 

individuals behave differently in different situations (e.g., school vs. home) or 

because some types of aggressive behaviors are more likely to be noticed (e.g., 

overt forms such as physical aggression) than other types of aggressive behaviors 

which may be more subtle or covert (e.g., relational aggression). Different raters 

provide important and unique pieces of information regarding behaviors. Selfreporters 

are aware of their own motives and behaviors, which may go undetected 

by their caregivers, teachers, or peers. On the other hand, caregivers or teachers 

may be able to understand difficult and complex constructs better than children. 

A teacher is also more likely to compare a child’s behavior to his or her peers, 

whereas a parent is likely to compare a child’s behavior to his or her siblings 

(Bartels et al., 2003). Regardless of the source of these discrepant results across 

methods of assessment, it is important to keep in mind that when it comes to 

studies of aggression, it matters who is doing the rating. 

D. Do heritabilities vary across forms of aggression 

Different types of aggressive behavior have been investigated across twin and 

adoption studies, with notable distinctions between reactive and proactive forms 

of aggression, as well as direct/physical and indirect/relational aggression 

(Table 8.3). It is likely that there are different etiologies for different forms of 

aggression; for example, defensive reactions to threatening stimuli may be more 

environmentally influenced, while more planned, proactive forms may be more 

genetically influenced (Tuvblad et al., 2009). Comparing heritability estimates 

collectively across the various measures employed is a reasonable way to address 

Table 8.3. Forms of Aggression 

Form of aggression 

Reactive/hostile/affective 

Proactive/instrumental 

Direct/physical 

Indirect/relational 

Description 

Angry or frustrated responses to a real or perceived threat 

Planning, the motive of the act extends beyond harming the victim 

Intentionally causing pain or harm to the victim 

Relational social manipulation such as gossip and peer exclusion


this question about whether some kinds of aggression are more heritable than 

others. When multiple forms of aggressive behavior are measured within the 

same study, it is also possible to investigate the extent to which the same genes 

and/or environmental factors are important to different manifestations of aggressive 

tendencies. 

Reactive aggression refers to angry or frustrated responses to a real or 

perceived threat. This specific type of aggression has been characterized to 

involve both high emotional arousal, impulsivity, and an inability to regulate 

or control affect. In contrast, proactive aggression is conceptualized as a more 

regulated, instrumental form of aggression, with more positive expectancies 

about the outcomes of aggression (Dodge, 1991; Dodge and Coie, 1987; 

Schwartz et al., 1998). Although reactive and proactive aggression have each 

been found to be mainly influenced by genetic and nonshared environmental 

factors, their genetic correlation is significantly less than 1.0, indicating some 

genetic specificity for the two forms of aggression. Reactive and proactive aggression 

each exhibit different developmental patterns in these influences (see Table 8.2; 

Baker et al., 2008; Tuvblad et al., 2009), that is, the genetic and environmental 

stability in reactive and proactive aggression has been found to differ. In one of the 

few longitudinal analyses of these constructs, the stability in reactive aggression 

from childhood to adolescence could be explained by genetic (48%), shared (11%), 

and nonshared (41%) environmental influences, whereas the continuity in proactive 

aggression was primarily genetically (85%) mediated (Tuvblad et al.,2009). 

Relational forms of aggression, which involve social manipulation such 

as gossip and peer exclusion, are often more indirect compared to other forms of 

aggression (Crick and Grotpeter, 1996). Like reactive and proactive forms, 

relational aggression appears to be influenced by genetic factors, both in 

self-report (49%) as well as parental reports (boys, 42%; girls, 21%). However, 

unlike the other more direct forms of aggression, relational aggression is also 

influenced by shared environmental influences, but only in parental reports 

(boys, 22%; girls, 46%) and not in self-report measures (Tackett et al., 2009). 

Together these findings—that is, the less than perfect genetic correlation between 

reactive and proactive forms, their different developmental etiologies, 

and the significant shared environmental effects in relational aggression only— 

provide support for at least some genetic and environmental etiological distinction 

among different forms of aggression. It should be noted, however, that no 

study to date has examined the genetic and environmental overlap between 

relational aggression and other forms such as proactive and reactive aggression. 

Other studies based on multifactorial measures of aggression, such as the 

BDHI, suggest some variability in the heritability estimates across subscales, 

although the patterns are not entirely consistent across studies. For example, 

“indirect hostility” showed the lowest heritability (28%) in one study of adult 

twins (Coccaro et al., 1997), compared to modest heritability for “verbal


hostility” (47%) and “assault” (40%). Yet, Cates et al. (1993) found no genetic 

influences for assault, but strong heritability for both verbal hostility (78%) and 

indirect hostility (70%). In multivariate genetic analyses, both studies found 

some support for genetic specificity for the various subscales, similar to what has 

been found for reactive and proactive aggression, in that genetic correlations 

(r G ) among the BDHI subscales were less than unity: r G ¼0.39 between indirect 

hostility and assault, r G ¼0.60 between indirect hostility and verbal hostility, 

r G ¼0.17 between verbal hostility and assault (Coccaro et al., 1997), r G ¼0.35 

between indirect hostility and assault, r G ¼0.39 between indirect hostility and 

verbal hostility, and r G ¼0.49 between verbal hostility and assault (Cates et al., 

1993). Overall, genetic influences are generally found for most, if not all forms of 

aggression, although somewhat different genetic factors may be operating across 

these different forms. The mechanisms that underlie more direct, planned, 

confrontational, and often physical forms of aggression may to some extent be 

different than those for reactive or indirect aggressive behaviors. 

E. Does heritability vary depending on study design (twins vs. 

adopted siblings) 

There were only a handful of studies identified examining the heritability of 

aggressive behavior using the sibling adoption design. Visual inspection of the 

results from these sibling adoption studies (see Table 8.1) compared to the results 

from studies including twin samples (Table 8.2) indicate that heritability estimates 

(i.e., h 2 ) and the shared environmental estimates (i.e., c 2 ) for aggressive behavior are 

very similar. This is also well in line with the results of a meta-analysis on antisocial 

and aggressive behavior that found no differences between twin and sibling adoption 

studies (h 2 ¼48%; c 2 ¼13%, e 2 ¼0.39%) (Rhee and Waldman, 2002). Thus, the 

heritability of aggressive behavior does not seem to vary depending on study design. 

F. Criticisms of twin and adoption studies: Assumptions and 

generalizability 

There are several assumptions in both twin and adoption studies that are important 

to consider when reviewing their findings. In adoption studies, the most important 

factors are (1) random placement of the adoptees into homes and (2) generalizability. 

Selective placement or matching (i.e., similarities between adoptive and 

biological parents) for certain characteristics can lead to inflated correlations 

between adoptive siblings (and thus overestimated effects of shared environment). 

Although such matching may occur for physical characteristics (including race), 

direct selective placement is unlikely to be made for aggressive behavior, per se. 

(Children with more aggressive or antisocial biological parents would not be placed 

into homes with more aggressive adoptive parents.) Thus, it is unlikely that the


genetic and environmental effects summarized in Table 8.1 are biased in any way as 

a result of selective placement. In terms of generalizability, it is often the case that 

adoptive parents tend to be in good health and from higher socioeconomic levels; 

thus, findings from adoption studies may not always be unquestionably generalized 

to the entire population (Rutter, 2006). Adopted children may also be at greater 

risk for aggression compared to nonadoptees, since birth parents giving up their 

children may have increased rates of disordered behaviors, including substance use, 

criminal offending, and aggression (Cloninger et al., 1985; Lewis et al.,2001). In the 

Deater-Deckard and Plomin (1999) study, the adopted children did in fact have 

higher aggression scores compared to the nonadopted children, consistent with the 

notion that adoptees may be at higher genetic risk for aggression compared to 

nonadopted individuals. The elevated levels of aggression in adoptees occurred in 

spite of the fact that background characteristics of the adoptive families were found 

to be representative of families with children in the larger Denver area, and that the 

demographic characteristics of the adoptive grandparents and the adopted children’s 

biological grandparents were similar, with regard to educational and occupational 

level. Similarly, van der Valk et al. (1998) reported mean differences 

between adoptees and nonadoptees, with adoptees showing higher mean levels in 

aggressive behavior. About 75% of the adoptees were adopted from Korea, India, 

Columbia, Indonesia, Bangladesh, or Lebanon and the remaining 25% were 

adopted from European or other non-European countries in both the van der 

Valk et al. (1998) and the van den Oord et al. (1994) studies, and the majority of 

the adoptive parents had a higher level of occupation. Given the higher aggression 

scores among adoptees compared to nonadoptees, as well as the somewhat greater 

affluence and ethnic heterogeneity in at least some of the adoption samples, the 

generalizability of adoption study results to the wider population could be 

questioned. 

To what extent are the twin study results generalizable to the wider 

population Twins and singletons have been found to experience similar rates of 

psychiatric disorders (e.g., attention-deficit hyperactivity disorder (ADHD), 

oppositional defiant disorder, conduct disorder) and behavioral and emotional 

problems (Gjone and Novik, 1995; Moilanen et al., 1999; Simonoff et al., 1997; 

van den Oord et al., 1995). Findings from the RFAB study show no differences in 

mean levels between MZ and DZ twins in reactive or proactive aggression (Baker 

et al., 2008; Tuvblad et al., 2009). It can, therefore, be assumed that twins and 

singletons display equal rates of aggressive behavior. 

There are, however, two ways in which twins differ from singletons: 

(i) lower birth weight, due to shorter length of gestation (Plomin et al.,2001)and 

(ii) delayed language development (Rutter and Redshaw, 1991). Birth weight has 

been found to have a minimal effect on academic performance; for twins this effect 

was judged relative to what is a normal birth weight for twins and not for singletons 

(Christensen et al., 2006). However, studies have shown that children with birth


complications are more likely to later develop antisocial and aggressive behavior 

(Raine, 2002), but birth complications may not by themselves predispose antisocial 

and aggressive behaviors, but will require the presence of an environmental risk 

factor (e.g., poor parenting, maternal rejection). In other words, the relationship 

between birth complications and antisocial and aggressive behavior is confounded 

by environmental risk factors (Hodgins et al.,2001;Raineet al.,1997). 

In addition to generalizability, there are several key assumptions of the 

classical twin design that need to be kept in mind when reviewing findings from 

these studies. These include (1) the equal environments assumption, (2) random 

mating, and (3) lack of correlation or interaction between genetic and environmental 

influences. We briefly review each of these assumptions here—both in 

general and as they pertain to aggressive behavior in particular—and consider 

their possible effects on the results summarized across studies. 

Perhaps the most important and commonly criticized assumption is the 

“equal environment assumption” (EEA). In the classical twin design, MZ twins, 

who are assumed to share 100% of their genes, are compared to DZ twins, who 

are assumed to on average share 50% of their genes. If MZ twins are more similar 

than DZ twins, it may be inferred that the difference is caused by genetic effects. 

To make this inference, however, it is necessary to rely on the EEA. It is assumed 

that environmentally caused similarity is roughly equal for both MZ and DZ 

twins. If this assumption is violated, higher correlations among MZ twins may be 

due to environmental factors, rather than genetic factors, and heritability estimate 

will be overestimated (Plomin et al., 2001). 

Several twin studies of various phenotypes have examined the EEA. 

One way to test the validity of the EEA is to examine whether a trait of interest is 

influenced by perceived versus assigned zygosity. The effect of perceived zygosity 

can be added as a “specified” familial environment in a univariate ACE twin 

model (Kendler et al., 1993) and if this parameter can be omitted without any 

significant loss in data fit, it can be assumed that the EEA holds for the 

phenotype under study. These studies generally report that the EEA assumption 

holds for numerous phenotypes such as physical activity, eating behavior, psychiatric 

disorders (e.g., major depression, generalized anxiety disorder, phobia, 

alcohol, and drug abuse; Eriksson et al., 2006; Hettema et al., 1995; Kendler et al., 

1993; Klump et al., 2000; Xian et al., 2000), including child and adolescent 

psychopathology such as anxiety disorder, ADHD, oppositional defiant disorder, 

conduct disorder, antisocial behavior (Cronk et al., 2002; Jacobson et al., 2002; 

Tuvblad et al., 2011) as well as aggressive behavior (Derks et al., 2006). 

The assumption of random mating for aggression in the parents of the 

twins is also important to consider, since nonrandom mating can lead to 

increased resemblance for DZ but not MZ twin pairs. Assortative mating in the 

parent generation acts to increase the resemblance between dizygotic twins and 

thereby bias shared environmental estimates upward and additive genetic effects


downward. A significant correlation between spouses for a particular trait is often 

interpreted as assortative mating (Maes et al., 1998). This assumption is probably 

violated when it comes to antisocial and aggressive behavior, as significant 

spouse correlations have been found suggesting that assortative mating exists 

in this behavioral domain (Krueger et al., 1998; Maes et al., 2007; Taylor et al., 

2000). Taylor et al. (2000) found that parents of twins were correlated for 

retrospectively reported delinquency (r¼0.23 in families of boys and r¼0.35 

in families of girls) and concluded that assortative mating is modest in degree. 

Another study using data from the Dunedin sample in New Zealand (Silva and 

Stanton, 1996) when the participants were 21-years-old found a correlation 

(r¼0.54) between couple members’ reports of antisocial behavior in their 

peers (i.e., participants were asked how many of their friends had aggression, 

personal, alcohol, or drug problems, or did things against the law), which was 

identical to the correlation for couple members’ reports of their own antisocial 

behavior as measured by a variety of offenses (e.g., theft, force, fraud, vice). They 

concluded that assortative mating for antisocial behavior is substantial and that 

antisocial individuals tend to cluster in peer groups with similar antisocial peers. 

As such, assortative mating should to be taken into account when modeling 

antisocial behavior (Krueger et al., 1998). It is interesting, however, that the 

shared environmental effects are fairly negligible in twin studies of aggressive 

behavior, both in the prior meta-analyses as well as in our summary in Table 8.2. 

Thus, any assortative mating for aggression does not appear to have resulted in 

severe overestimates of shared environment when considering these studies 

en masse. It is possible, on the other hand, that genetic influences themselves 

have been underestimated and could be larger than the 50% or so than these 

meta-analyses and our summary suggest. 

It is also assumed in the classical twin design that genetic and environmental 

influences combine additively (i.e., do not interact) and are uncorrelated. 

It is possible, however, that some genetic predispositions may be associated with 

certain kinds of social environments or experiences, leading to a correlation 

between genes and environments. (GE interactions are also discussed at 

length in a later section of this chapter.) Such GE correlations (r GE ) can 

arise in three different ways (Scarr and McCartney, 1983): (i) Passive r GE occurs 

when genes overlap between parents and their offspring. For example, a child 

with aggressive parents inherits genetic susceptibility for aggression as well as 

experiences an adverse rearing environment. An example of passive r GE was 

reported in a study comparing genetic and environmental influences on mothering. 

Passive r GE correlations were suggested for mother’s positivity and monitoring. 

For mother’s negativity and control, primarily nonpassive r GE correlations 

were suggested (Neiderhiser et al., 2004). (ii) Evocative/reactive r GE can arise 

when a specific child characteristic elicits a particular response from the environment. 

For example, aggressive children tend to elicit more negative affect and


harsh discipline from their parents (Ge et al., 1996; O’Connor et al., 1998). In a 

more recent study, using the classical twin design the association between 

parental criticism and adolescent antisocial behavior was found to be entirely 

genetically influenced. Approximately half of the genetic contribution to this 

association was explained by early adolescent aggression. Thus, child aggression 

seemed to elicit negative parenting followed by adolescent antisocial behavior, 

indicating an evocative r GE (Narusyte et al., 2006). (iii) Active r GE is defined as 

the process whereby an individual actively seeks out environmental situations 

that are more closely matched to the person’s genotype. Active r GE has been 

suggested in adolescent drinking behavior, specifically among girls (Loehlin, 

2010). If the assumption of no GE correlation is violated, heritability estimates 

for aggressive behavior in twin studies could include both additive genetic effects 

and the effects of GE correlation (i.e., heritability estimates are inflated). 

Apart from these specific examples cited here, few studies have examined the 

effects of r GE in aggressive behavior, making it difficult to know the extent of 

their effect on heritability estimates in twin studies. 

In conclusion, findings from adoption studies should probably be 

generalized cautiously to other populations as adoptees tend to show higher 

scores on aggressive behavior compared to controls. On the other hand, most 

of the assumptions of the classical twin design seem to hold for aggressive 

behavior. The EEA has been tested and found to hold for various phenotypes 

including aggressive behavior, and twins and singletons have been found to 

display similar scores on aggressive behavior, suggesting that findings from twin 

studies can be generalized to other populations. Most twin studies report finding 

little or no shared environmental influences on aggressive behavior, suggesting 

that random mating is of little importance for aggressive behavior. Only a few 

studies have examined the influence of GE correlation on aggressive behavior, 

suggesting that more research is needed on this topic before we can draw any firm 

conclusions. Last, in the classical twin design, it is assumed that genetic and 

environmental influences combine additively and do not interact. This assumption 

is probably violated to some extent when it comes to aggressive behavior, 

as several studies have reported finding significant interaction effects. GE 

interaction is discussed in detail in the next section of this chapter. 

II. G E INTERACTION IN AGGRESSIVE BEHAVIOR 

There is a general recognition that genes and environment work together—often 

in complex ways—to produce wide variations in behavior and psychological 

function. GE interaction, by definition, is a statistical term indicating that 

genetic effects on a given phenotype depend upon environmental factors or vice 

versa. Gene expression, for example, can be moderated by an individual’s


experiences or exposure to certain environments. Likewise, various individuals 

may respond differently to the same environmental exposure because they have 

different genotypes. Such genetic sensitivity to the environment has been 

demonstrated extensively in plant and animal species for a variety of traits. But 

even though the importance of GE interactions in human behavior has long 

been considered (Eaves, 1984; Mather and Jinks, 1982), GE interactions have 

been rarely reported in human traits until relatively recently. The failure to find 

GE interactions in studies of human characteristics may be due to a number of 

factors. One likely explanation is related to statistical power. In general, it is 

difficult to detect GE effects due to their low statistical power (Rowe, 2003). 

For example, behavioral genetic studies rely on genetic relatedness for groups of 

individuals, rather than on sharing of specific alleles between pairs of relatives. 

Studies relying on variance partitioning often do not find significant GE 

effects, or find that they explain a very small portion of the total variance, and 

are thus dropped from further analysis. When G E is not taken into account in 

behavioral genetic studies, heritability estimates will tend to be biased, although 

the direction of the bias depends on whether the moderating environmental 

influences are of the shared or nonshared variety. 

GE interactions can be tested or modeled in behavioral genetic studies 

using several different study designs (e.g., twin or adoption). The two most 

frequently used methods testing for GE interactions in twin and adoption studies 

include: (1) a mean levels approach, testing whether mean values of a phenotype 

differ across different combinations of genetic risk and environmental settings and 

(2) a moderated variance components approach, examining whether genetic and 

environmental variance for a trait varies across different measured environmental 

settings. These two different methods stem from the same conceptual idea, namely, 

that genetic effects vary across environments or vice versa. Their interpretations 

and meanings can be rather different, since one is based on means and the other is 

based on variances. The mean levels GE is perhaps a more traditional approach, 

is typically presented as a statistical interaction in an ANOVA, and indicates 

whether particular experiences, exposures, or other conditions may (on average) 

ameliorate or exacerbate specific genetic effects in groups of individuals with 

similar genetic and environmental risks. In comparison, the moderated effects 

approach does not address mean levels of risk, but instead evaluates whether 

variance in genes or environment differs across various measured conditions. 

Moderation can occur in either raw variances (V A , V C ,andV E )orinrelative 

effects (i.e., h 2 , c 2 , and e 2 ), and may not necessarily coincide with GE interactions 

found in mean levels. The latter point is important when evaluating GE 

interactions across studies using these different approaches, since different patterns 

can emerge from them. For example, it is possible that certain adverse environments 

(e.g., low socioeconomic status (SES)) may lead to some genes exerting 

stronger effects (mean levels), while overall, the relative variance explained by


genes (heritability) may be greater in other environments (e.g., high SES). The 

approach used for testing GE interactions can vary across study design, such that 

adoption designs or studies with measured genes are generally required for the 

mean levels approach, while the moderated variance components approach may be 

used in both twin and adoption studies in the absence of measured genes. 

In molecular genetic studies, both genes and environment are measured, 

rather than inferred from correlations among family members. GE interactions 

can therefore be tested in the general population, that is, without necessary 

reliance on a twin or adoption design. There are still advantages, nonetheless, 

to include measured genes and measured environments in the context of a familybased 

design, including twins and other siblings as well as parents and offspring. 

Evidence of GE interaction in aggressive behavior has been reported 

in twin and adoption studies, and more recently in molecular genetic studies. 

Below is a summary of some of the GE interaction findings in aggressive 

behavior from adoption, twin and molecular genetic studies. We also discuss 

two potential moderators of genetic and environmental influences on aggressive 

behavior, exposure to media violence, and alcohol use. 

A. Potential moderators of genetic influence found in adoption and 

twin studies 

1. Family adversity and social disadvantage 

GE interaction for aggressive behavior has been found in several of the early 

adoption studies, using a mean levels approach. What these early adoption study 

findings generally showed was that early adverse environments had a greater 

negative impact on genetically “higher risk” children. Adopted children with 

criminal biological parents reared by a family where there was adversity showed 

higher rates of antisocial and aggressive behavior than adopted children with 

antisocial biological parents not raised in a home with adversity, and than 

adopted children raised in adversity who are not at higher genetic risk. For 

example, the interaction of inherited and postnatal factors was examined in 

about 800 Swedish men adopted at an early age. When both inherited factors 

and environmental risk factors were present, 40% were found to be criminal; if 

only genetic factors were present, 12.1% were criminal; if only environmental 

factors were present, 6.7% were criminal; and with neither inherited nor environmental 

factors being present, 2.7% were criminal (Cloninger et al., 1982). 

The fact that 12.1% plus 6.7% is less than 40% would thus be an indication of 

GE interactions. This finding was later replicated in females (Cloninger and 

Gottesman, 1987). It should be pointed out, however, that in the adoption 

design, the genetic risk factors themselves are considered in a general way, 

such that the exact nature of the genes is left unspecified, both in terms of


which loci or alleles may be involved and what underlying mechanisms may be 

involved in the path from genes to phenotype. Similarly, the environmental risk 

factors as indexed by certain traits in the adoptive parents or characteristics of 

their home do not necessarily specify the exact nature of the child’s experiences 

or how these lead to various outcomes. 

Further, maltreatment places children at risk for psychiatric morbidity, 

especially conduct problems. However, not all maltreated children will develop 

conduct problems. A recent twin study tested whether the effect of physical 

maltreatment on risk for conduct problems was strongest among those who were 

at high genetic risk for these problems using data from the E-risk study, a representative 

cohort of 1116 5-year-old British twin pairs and their families. Maltreatment 

was found to be associated with a greater increase in the probability of developing 

conduct problems among children who had a high genetic liability for conduct 

disorder compared to children who had a low genetic liability (Jaffee et al.,2005). 

This finding is consistent with the GE interaction found in adoption studies of 

antisocial and aggressive behavior, in which genetic effects were more pronounced 

in adverse environments. This clearly suggests that children in risky environments 

would benefit from interventions. However, another view of this interaction is that 

favorable genotypes can play a protective role on children’s risk for conduct 

problems, especially under circumstances of maltreatment. 

There are also a few studies based on twin samples that have used the 

moderated variance components approach to examine whether measured environmental 

(risk) factors moderate the genetic and environmental variances for 

aggressive behavior. For example, the heritability of conduct problems was found 

to be lower in children growing up in dysfunctional families and higher in 

children growing up in families where dysfunction was absent (Button et al., 

2005). Another twin study used DeFries-Fulker regression analysis to examine 

whether genetic and environmental influences on aggressive behavior varied 

depending on levels of family warmth (DeFries and Fulker, 1985). Genetic 

influence on aggressive behavior was found to be higher in schools with higher 

average levels of family warmth. In contrast, environmental influences (both 

shared and nonshared) were more important in schools with lower average levels 

of family warmth (Rowe et al., 1999). These findings suggest that genetic effects 

are more likely to explain individual differences in aggression in more benign 

environments, whereas in more disadvantaged environments negative familyrelated 

factors and context-dependent risks may play a greater role than genetic 

predispositions in aggressive and antisocial outcomes. 

Many early theories about the causes of delinquency and crime assumed 

that delinquents come from socially disadvantaged backgrounds. For example, 

Merton postulated that antisocial behavior resulted from the strain caused by the 

gap between cultural goals and the means available for their achievement 

(Merton, 1957). Social disadvantage and poverty constitute a reasonable robust,


although not always a strong, indication of an increased risk for antisocial and 

aggressive behavior, assessed by self-reports and official convictions (Leventhal 

and Brooks-Gunn, 2000; Rutter et al., 1998). SES has also been found to moderate 

the relative influence of genetic factors on antisocial and aggressive behavior. In a 

sample of Swedish 16–17-year-old twins, heritability for antisocial and aggressive 

behavior was higher in the more affluent neighborhoods (boys, 37%; girls, 69%) 

compared to the less advantaged neighborhoods (boys, 1%, girls, 61%). Conversely, 

the shared environment was higher in the less advantaged neighborhoods 

(boys, 69%; girls, 16%) compared to better-off neighborhoods (boys, 13%; girls, 

6%). Following the “social push hypothesis,” Raine (2002) would suggest that the 

genetic factors on antisocial and aggressive behavior are more expressed in a 

socioeconomically advantaged environment where the environmental risk factors 

are absent. On the contrary, genetic factors for antisocial behavior will be 

weaker and the shared environment more important in a socioeconomically 

disadvantaged environment because the environmental risk factors will “camouflage” 

the genetic contribution (Tuvblad et al., 2006). 

These studies using the moderated variance components approach (e.g., 

Button et al., 2005; Rowe et al., 1999; Tuvblad et al., 2006), all examine whether 

an environmental (risk) factor moderates genetic and environmental variance 

on antisocial and aggressive behavior. Findings from these studies show that 

heritable influences on aggressive behavior vary depending on environmental 

context, indicating the importance of the environmental risk factors in the 

development of aggressive behavior as well as for gene expression. 

2. Violent media exposure 

There is an ongoing debate about whether exposure to violent video games 

increases aggressive behavior, and it is very possible that exposure to media 

violence could moderate the influences of genetic and environmental influences 

on aggressive behavior. One line of research argues that mass media exposures 

contribute to a child’s socialization. A primary process in such socialization is 

observational learning (Bandura, 1973). Children and adolescents mimic what 

they see and acquire complicated scripts for behaviors, beliefs about the world, 

and moral precepts about how to behave in the long run from what they observe 

(Huesmann, 2010). In contrast, another line of research argues that there is little 

empirical evidence for a link between media exposure and violence. This line of 

research argues that media violence cannot have any important psychological 

effect on the risk for aggressive behavior (Ferguson and Kilburn, 2010). 

A recent meta-analysis that included 136 studies examined the effects 

of violent video games on aggressive behaviors. The evidence suggested that 

exposure to violent video games is a risk factor for increased aggressive behavior,


aggressive cognition, and aggressive affect, and for decreased empathy and 

prosocial behavior. Moderator analyses showed significant research design 

effects, weak evidence of cultural differences in susceptibility and type of measurement 

effects, and no evidence of sex differences in susceptibility. Sensitivity 

analyses were also carried out and they revealed these effects to be robust, with 

little evidence of selection (publication) bias (Anderson et al., 2010). 

Others studies examining the relationship between violent video games 

and aggressive acts have found little evidence for a relationship. A recent review 

included a total of 25 studies comprising 27 independent observations. The 

corrected overall effect size for all included studies was only r¼0.08 (Ferguson 

and Kilburn, 2009). The mixed findings in the literature clearly suggest that more 

research is needed to resolve whether there is a link between exposure to violent 

video games and aggressive behavior. Also, some studies have found that exposure 

to violent video games only explains a small fraction of the variance. An explanation 

for this paradox could be that exposure to violent video games moderates 

the influence of genetic and environmental effects on aggressive behavior, rather 

than exerting direct effects. No genetically informative studies have examined 

violent video game exposure as a possible moderator of genetic influence on 

aggression, however, leaving this as an important area in need of study. 

3. Alcohol use 

It has long been known that some individuals become aggressive after consuming 

alcohol, and the relationship of violence and aggression with alcohol is well 

established (Bushman and Cooper, 1990; White et al., 2001). For example, a 

review including 130 independent studies found that alcohol was correlated with 

both criminal and domestic violence (Lipsey et al., 1997). Despite this, there is so 

far no behavioral genetic study that had examined whether alcohol use moderates 

the influence of genetic and environmental factors on aggressive behavior. 

However, the genetic and environmental relationship among alcohol 

use and aggressive behavior as well as other disruptive and problem behaviors 

within the disinhibitory spectrum such as antisocial behavior, ADHD, conduct 

disorder, impulsive and sensation seeking personality traits has been examined in 

several large population-based twin studies. On a phenotypic level, disruptive 

and problem behaviors within the disinhibitory spectrum can be united by a 

common higher order externalizing factor (Krueger et al., 2002, 2005, 2007). 

This higher order externalizing factor has been found to be largely influenced by 

genetic factors. For example, the genetic influences on a common externalizing 

factor describing conduct disorder, substance use, ADHD, and novelty seeking 

was found to account for more than 80% of the variation in an adolescent sample 

(Young et al., 2000). Strong heritable influences on an externalizing factor of


antisocial behavior, substance abuse, and conduct disorder has also been found 

among adults (Kendler et al., 2003). Together these studies provide important 

insight into our understanding of externalizing behaviors. It seems that behaviors 

and disorders within the externalizing spectrum, including aggressive behavior, 

share a common genetic liability. 

III. SPECIFIC GENES FOR AGGRESSIVE BEHAVIOR: FINDINGS FROM 

MOLECULAR GENETIC STUDIES 

Increasing evidence suggests the importance of heritable factors in the development 

of aggressive behavior (Burt, 2009; Miles and Carey, 1997; Rhee and 

Waldman, 2002). The first study that showed a link between a specific genotype 

and aggressive behavior examined the genetic material of members of a large 

Dutch family. This specific family had for decades been found to be prone to 

violent, aggressive, and impulsive behavior, including fighting, arson, attempted 

rape, and exhibitionism. Some of the male family members were also intellectually 

disabled. The aggressive males in this large family were shown to share a 

mutation in the gene that codes for the enzyme MAO (monoamine oxidase A). 

MAO breaks down brain chemicals (neurotransmitters) such as serotonin, noradrenaline, 

and dopamine, which transmit messages from one nerve cell to the 

next. In the afflicted males, however, a mistake in the coding sequence governing 

proper production of MAO was detected. As a result, abnormally large quantities 

of these neurotransmitters were found in the blood of the affected males 

(Brunner et al., 1993). Although this genetic defect remains the first such link 

to aggressive behavior in humans, exactly how the genetic defect causes aggressive, 

impulsive behavior, or mental retardation is not known. 

Apart from MAO, only a few candidate genes have been linked to 

aggressive behavior to date. The candidate genes that have been found to be 

associated with aggressive behavior in humans have, in many cases, been replicated 

in animal studies. The majority of these candidate genes are genes of the 

dopamine, serotonin, and norepinephrine neurotransmitter systems. The dopamine 

system is involved in mood, motivation and reward, arousal, as well as other 

behaviors. The serotonin system is involved in impulse control, affect regulation, 

sleep, and appetite, whereas the epinephrine and norepinephrine system facilitate 

fight-or-flight reactions and autonomic nervous system activity (Niv and Baker, 

2010). For example, dopaminergic candidates, including dopamine receptor 

DRD4, has been found to be involved in ADHD and externalizing behavior, 

and DRD2 has been found to be involved in substance abuse and disinhibition 

(Niv and Baker, 2010). The DRD3 polymorphism has been found to be associated 

with impulsivity. This association was significant in violent, but not in nonviolent 

individuals, and there were no association between DRD3 and violence per se


(Retz et al., 2003). Dopamine transporter gene DAT1 has also been linked to 

ADHD (Waldman et al., 1998), as well as with violent behavior and delinquency 

in adolescents and young adults (Guo et al., 2007). Cateocholamine-O-methyltransferase 

(COMT) has been examined primarily in children and adults with 

ADHD, and mixed evidence emerged for its association with conduct disorder 

and aggression (Caspi et al., 2008). Several studies have provided evidence that 

the low activity VNTR alleles of 5HTTLPR show associations with aggression, 

violence, aggressive symptoms of conduct disorder, and other forms of externalizing 

behavior (Haberstick et al., 2006b; Linnoila et al., 1983). Aggressive behavior 

has also shown associations with SNPs of epinephrine and norepinephrine. A 

recent study linked two SNPs of PNMT to cognitive and aggressive impulsivity in 

children and adolescents (Oades et al., 2008). 

A. G E interaction involving specific genes for aggressive behavior 

Advances in the field of molecular genetics have also made it possible for 

researchers to identify GE interactions much more specifically. One of the 

most influential studies examining GE in antisocial and aggressive behavior is 

Caspi et al. (2002), a famous study from 2002. The relationship between a 

functional polymorphism in the MAO-A gene encoding the neurotransmittermetabolizing 

enzyme and early childhood maltreatment was examined in the 

development of antisocial behavior in males. A significant G E interaction 

was detected, in that maltreated boys with a genotype conferring low levels of 

MAO-A were found to be more likely to later develop antisocial problems, 

including conduct disorder, adult violent crime, and antisocial personality disorder, 

than maltreated boys who had a genotype conferring high levels of MAO-A 

(Caspi et al., 2002). So far, there have only been a few replications of this 

important finding (Foley et al., 2004; Kim-Cohen et al., 2006; Nilsson et al., 

2006). For example, Kim-Cohen et al. (2006) found that the MAO-A polymorphism 

moderated the development of psychopathology after experiencing physical 

abuse in a sample of 975 seven-year-old boys. This finding was extended to 

the maltreatment exposure closer in time as the subjects were 7-years-old 

compared with previous work by Caspi et al. (2002) in which the subjects were 

26-years-old, and therefore the possibility of a spurious finding by accounting for 

passive and evocative GE correlation could be ruled out. Passive GE 

correlation, as discussed earlier, refers to the association between the genotype 

a child inherits from his/her parents and the environment in which the child is 

raised, and evocative GE correlation occurs when an individual’s (heritable) 

behavior evokes an environmental response. Further, the authors also conducted 

a meta-analysis including the following five studies: Caspi et al. (2002), Foley 

et al. (2004), Haberstick et al. (2005), Kim-Cohen et al. (2006), and Nilsson et al. 

(2006). The association between maltreatment and mental health problems


was significantly stronger in the group of males with a genotype conferring low 

versus high MAO-A activity. This provides strong evidence that the MAO-A 

gene influences vulnerability to environmental stress and that this biological 

process can be initiated early in life. However, there is at least one published 

failure to replicate (Haberstick et al., 2005), and this finding has been replicated 

neither in females (Sjöberg et al., 2007) nor in African Americans (Widom and 

Brzustowicz, 2006). 

AGE interaction between the DRD2 A1 allele and risk-level in family 

environments has been suggested in a sample of adolescents with criminal offenses, 

the National Longitudinal Study of Adolescent Health (Ad-Health). Polymorphisms 

in genes related to the neurotransmitter dopamine were associated with age of 

first police contact and arrests, but only for youth from low-risk family environments. 

More specifically, among those adolescents with a history of criminal 

offending, those at greatest risk for later onset were those with the A1 allelic 

form of the DRD2 gene, in combination with favorable home environments as 

defined by maternal attachment, involvement, and engagement (DeLisi et al., 

2008). It is important to emphasize that this finding involves the age of onset of 

first police contact and not the overall risk for offending versus not offending. 

There is also some evidence for a GE interaction in the 5HTTLPR 

genotype with adult violence, whereby home violence, familial economic difficulties, 

and educational or home-life disruptions during childhood were found to 

predict violent behavior later in life only in individuals with the short promoter 

alleles present (Reif et al., 2007). A similar GE interaction between the short 

allele of 5HTTLPR and childhood adversity has also been reported for ADHD 

(Retz et al., 2008). 

The ability to detect GE interactions in molecular genetic studies is 

both exciting and controversial. The identification of specific genetic markers 

and specific experiences provides the opportunity to evaluate genetic and 

environmental risk factors at the individual level. This significantly increases 

opportunities for developing effective treatments and preventions for antisocial 

and aggressive behavior as well as other forms of psychopathology, which is 

exciting. At the same time, increased understanding of individual risks has 

often been considered cautiously because of the potential for bias and discrimination 

of those individuals who are identified as being at highest risk for being 

afflicted with disorders. 

IV. CONCLUSIONS 

Studies (and meta-analyses) including both twin and adoption samples show 

that about half (50%) of the variance in aggressive behavior is explained by 

genetic influences in both males and females, with the remaining 50% of the


variance being explained by nonshared environmental factors. Form of aggression 

(reactive, proactive, direct/physical, indirect/relational), method of assessment 

(observation, self, teacher, parent/caregiver), and age of the subjects—all 

seem to be significant moderators of the magnitude of genetic and environmental 

influences on aggressive behavior. Neither study design (twin vs. 

sibling adoption design) nor sex, on the other hand, seems to impact the 

nature or magnitude of these genetic and environmental influences on 

aggression. 

Although we are unaware of any twin or adoption studies of aggression 

induced in authoritative situations such as in the Milgram or Stanford Prison 

studies, the vast evidence for genetic influences in most forms of aggression that 

have been studied could suggest that individual differences in those early 

studies might have stemmed in part from different genetic propensities in 

their subjects. Findings from GE studies on aggressive behavior suggest that 

not all individuals will be affected to the same degree by these environmental 

exposures, and also that not all individuals will be affected to the same degree 

by the genetic predispositions. Adoption and twin studies rely on relationships 

between family members when examining GE interaction effects, whereas 

molecular genetic studies are using both a measured environmental (risk) factor 

and a measured genetic factor. To date, there have only been a few twin/ 

adoption and molecular studies that report finding GE in aggressive behavior, 

either using the mean levels approach or the moderated effects approach. These 

studies have shown that various measures of family adversity and social disadvantage 

interact (or act as moderators) with genetic factors on aggressive 

behavior. 

Today, we have the potential to identify genetic risks at the level of 

specific genes, and identify aspects of the environment that make some individuals 

more vulnerable than others. Yet, there will always be groups of individuals 

with the same combination of genetic risk and environmental 

vulnerability who will not engage in aggressive behavior. So, it is still only an 

increased (probabilistic) risk and not a biological determinism. In spite of such 

strong support for a genetic basis to aggressive behavior, the importance of 

potential interventions which are environmentally based must not be ignored. 

Environmental interventions could be developed, for example, through family 

or school-based programs, to reduce aggressive behavior. In fact, a general view 

held by behavioral genetics researchers is that the best way to understand 

environment—and hence develop effect treatment interventions—is through 

genetically informative designs such as twin and family data. By using twin and 

family data, it is not only possible to estimate the influence of heritable factors 

on a trait or a phenotype, but also the influence of environmental factors. 

Modern methods for identifying and understanding GE interactions will 

provide a means for doing exactly this.


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9 

Perinatal Risk Factors in 

the Development of 

Aggression and Violence 

Jamie L. LaPrairie, Julia C. Schechter, Brittany A. Robinson, 

and Patricia A. Brennan 

Department of Psychology, Emory University, Atlanta, Georgia, USA 


II. The Neurobiological and Psychophysiological Systems Involved in 

the Regulation of Aggression and Violence 

A. Types of aggressive behavior 

B. Neurobiological bases of aggression and violence 

C. Neurochemical signals of aggression and violence 

D. Hormones 

E. Autonomic response measures 

F. Electro cortical response measures 

III. Perinatal Factors Related to the Development of Aggression 

A. Birth complications 

B. Preterm birth and low birth weight 

C. Prenatal drug and alcohol exposure 

D. Smoking 

E. Maternal psychological stress 

F. Environmental context 

IV. Genetic Contributions 

A. Genetic factors as explanatory 

B. Gene by environment (G E) interactions 

C. The role of epigenetics 

V. Conclusions 

References 



DOI: 10.1016/B978-0-12-380858-5.00004-6

216 LaPrairie et al. 

ABSTRACT 

Over the past several decades, the relative contribution of both environmental 

and genetic influences in the development of aggression and violence has been 

explored extensively. Only fairly recently, however, has it become increasingly 

evident that early perinatal life events may substantially increase the vulnerability 

toward the development of violent and aggressive behaviors in offspring 

across the lifespan. Early life risk factors, such as pregnancy and birth complications 

and intrauterine exposure to environmental toxins, appear to have a 

profound and enduring impact on the neuroregulatory systems mediating violence 

and aggression, yet the emergence of later adverse behavioral outcomes 

appears to be both complex and multidimensional. The present chapter reviews 

available experimental and clinical findings to provide a framework on perinatal 

risk factors that are associated with altered developmental trajectories leading to 

violence and aggression, and also highlights the genetic contributions in the 

expression of these behaviors. ß 2011, Elsevier Inc. 


Aggressive behavior and violent offending are significant burdens not only to the 

individual but also to society at large; incurring costs upward of 2.3 million dollars 

per individual in the most severe cases in the United States (Cohen et al., 2010). 

In contrast to popular belief, longitudinal epidemiological research indicates that 

the sudden onset of physical aggression in adolescence or adulthood is unusual 

(Tremblay, 2008). Rather, physically aggressive behaviors can already be detected 

by 12 months of age, and their frequency peaks by 2–4 years of age (Côté et al., 

2006; Tremblay, 2008). Indeed 85% of children exhibit aggression and tantrums 

by age 2 (Potegal and Davidson, 2003). In the majority of children, the frequency 

of physical aggression gradually decreases toward the end of the preschool period, 

reflecting an increase in cognitive control of behavior, the acquisition of alternate 

problem-solving strategies, and the influence of socialization (Nagin, and 

Tremblay, 1999; Tremblay, 2008). A 60-year longitudinal study of juvenile delinquents 

concluded that very few show a lifespan high frequency of violent offending 

(Sampson and Laub, 2003), and among those who do express chronic physical 

aggression, impaired executive functioning is evident in adolescence and early 

childhood, even after controlling other cognitive deficits (Barker et al., 2007). 

Longitudinal follow-up studies of elementary school children with continued high 

levels of physical aggression demonstrate that they are at greater risk for numerous 

adjustment problems throughout their lifetime, including substance abuse, academic 

failure, antisocial behavior, suicide, depression, spouse abuse, and neglectful 

parenting (Broidy et al., 2003; Tremblay et al., 2004).

9. Perinatal Factors in the Development of Aggression 217 

The neurobiological substrates underlying the individual variability in 

the development of aggression and violence are many (Loeber and Pardini, 2008), 

and current research suggests that some of the most relevant risk factors for a 

trajectory of consistently high aggression are predicted by perinatal life events 

including pregnancy and birth complications and intrauterine exposure to tobacco, 

drugs, and alcohol (Brennan and Mednick, 1997; Cannon et al., 2002). 

Genetic studies of aggressive behavior also indicate that childhood aggression is 

highly heritable (Brendgen et al., 2005; Hicks et al., 2004). Together, these 

congenital factors appear to produce neuropsychological deficits in the nervous 

system of offspring, manifesting as subtle neurocognitive difficulties, altered temperament, 

delayed motor development, and hyperactivity (Moffitt and Caspi, 

2001). The two most commonly characterized developmental trajectories for 

aggression and violence are: (1) an early-onset persistent offender and (2) a lateonset 

adolescent-limited offender (Moffitt, 1993; Patterson et al., 1989). In the 

early-onset offender, behavioral problems typically manifest early in life, develop 

into serious juvenile delinquency during adolescence, and ultimately evolve into a 

long-term adult history of criminal behavior. Alternatively, late-onset adolescentlimited 

individuals typically do not begin offending until middle to late adolescence 

and cease violent and criminal behavior by their mid-1920s (Moffitt, 1993). 

These two distinct trajectories are associated with substantial variation in severity, 

chronicity, etiology, and prognosis. In fact, adolescent-limited offending can be 

considered normative and functional, given the developmental demands on adolescents 

in modern society (Moffitt, 1993). Adolescent-limited offending may also 

be explained by normative changes in brain development in postpubertal children. 

Life-course-persistent offending, in contrast, is not socially sanctioned, functional, 

or reflective of normative changes in brain development. Instead, this type of 

offending is likely caused by genetic and perinatal factors which lead to deficits in 

neurocognitive and neurophysiological functioning throughout the life course. 

Prior to reviewing the current research on perinatal factors and violence, it is 

important to briefly describe the neurophysiological processes that are involved in 

the regulation of aggression and violence. Then we will describe how these factors 

may mediate that relationship between perinatal risk and aggressive outcomes. 

Finally, we will attempt to highlight what is known about the genetic contributions 

to this developmental process. 

II. THE NEUROBIOLOGICAL AND PSYCHOPHYSIOLOGICAL SYSTEMS 

INVOLVED IN THE REGULATION OF AGGRESSION AND VIOLENCE 

The central nervous system (CNS) and autonomic nervous system (ANS) 

maintain homeostasis and monitor physiological responses in humans from the 

perinatal period throughout the lifespan. These systems are also involved in the


mediation of aggressive, violent, and antisocial behavior. Although neurophysiological 

systems have been the focal point of studies on aggression for decades 

(Scarpa and Raine, 1997), significant technological advances over the past 

20 years have allowed researchers to advance their investigation of the biological 

basis underlying violent and aggressive behaviors. Indeed, researchers are now 

able to ask questions concerning the neural underpinnings of aggression and how 

the interactions between genes and environment may result in later violence; 

ultimately leading to a more complete picture of the development of aggression 

and violence throughout the lifespan. 

A. Types of aggressive behavior 

Two forms of aggression are present in both experimental animal and human 

models. Throughout the animal literature, predatory aggression has been differentiated 

from defensive aggression (Scarpa and Raine, 1997). Similarly, human 

studies often discriminate between instrumental/proactive aggression and hostile/reactive 

or impulsive aggression (Crick and Dodge, 1996; Nelson and 

Trainor, 2007). Reactive aggression is characterized as aggressive behavior occurring 

in the context of anger and high emotionality. It is often more impulsive, 

less controlled, and occurring in reaction to a provocation or frustration (Scarpa 

and Raine, 1997). Instrumental aggression is qualified as being more goal-oriented 

and relatively nonemotional. Studies suggest that this latter type of aggression 

is regulated by higher cortical systems rather than brain regions (i.e., limbic 

systems) associated with impulsiveness (Nelson and Trainor, 2007). 

Of note, instrumental aggression is characteristic of psychopathy, a 

subtype of aggression often associated with particularly low levels of physiological 

arousal (Raine, 2002a). While psychopathological disorders are outside the 

scope of this chapter, understanding that individuals may display different types 

of aggressive behavior is essential to conceptualizing physiological research 

findings and the development of violence, in general. 

B. Neurobiological bases of aggression and violence 

Recent technological advances have allowed scientists to observe parallel neurochemical 

and anatomical correlates that are activated during aggression in 

both human and nonhuman animals (Nelson and Trainor, 2007). Neurobiological 

literature regarding aggression appears to focus on substrates that are implicated 

in either the expression of aggressive behavior or inhibitory control of 

aggression (Siegel and Victoroff, 2009). Below is a brief synthesis of the animal 

and human literature that pertains to the neurobiological systems that have been 

implicated in the development and modulation of aggression and violence.

1. Amygdala 


The amygdala is part of the limbic system and is considered to play a central role in 

both emotional regulation (Joseph, 1999) and fear conditioning (Susman, 2006). 

Lesion studies in animals have been critical to the understanding of the relationship 

between the amygdala and aggression. Lesioning of the medial amygdala reduces 

aggression in rats (Kruk, 1992). Male rhesus monkeys with amygdalar lesions display 

significant increases in aggressive behavior in a group setting (Machado and 

Bachevalier, 2006), while decreases in aggressive behavior are observed when 

animals are tested within a dyad (Emery et al., 2001). An explanation for these 

divergent findings may be that reintroduction into a group is a more fearful situation, 

thus leading to increases in amygdalar responsiveness (Nelson and Trainor, 2007). 

Functional abnormalities in the amygdala have also been noted in human 

studies in childhood, adolescence (Marsh et al., 2008; Sterzer et al., 2005), and 

adulthood (Veit et al., 2002); however, these studies have provided mixed results. 

The posteroventral medial amygdala appears to be involved in the regulation of 

reactive aggression, as in defensive situations, while the posterodorsal medial amygdala 

appears to be associated with instrumental or offensive situations (Swanson, 

2000). Coccaro et al. (2007) found that amygdalar activation is positively associated 

with scores on the Lifetime History of Aggression scale for adults with intermittent 

explosive disorder and healthy controls. Notably, only individuals with intermittent 

explosive disorder display increased activation of the amygdala in response to angry 

faces (Coccaro et al., 2007). Conversely, Sterzer et al. (2005) found a negative 

correlation between aggression and the left amygdala in response to negative affective 

images in a group of boys diagnosed with conduct disorder (CD). However, the 

inverse relationship (i.e., positive correlation between amygdala activation and 

aggression) was found in youth with comorbid anxiety and depression, symptoms 

often found to be associated with CD (Loeber et al., 2000). Reduced responsiveness of 

the amygdala in response to fearful faces has been suggested to reflect impairment in 

the processing of distress cues (Marsh et al., 2008), which may result in a lack of 

empathy and increases in instrumental aggressive behavior (Blair, 2001). One 

explanation for these discrepant findings across samples is that aggressive individuals 

may appear hyporesponsive when faced with detecting threat or distress, but hyperresponsive 

to distressful situations that can lead to aggression (Decety et al., 2009). 

Further, these mixed findings highlight that the amygdala’s role in the mediation of 

aggression may be based largely on the type of aggression expressed. 

2. Anterior cingulate cortex 

The anterior cingulate cortex (ACC) is also a part of the brain’s limbic system 

and has been implicated in emotional and cognitive processing (Bush et al., 

2000). Lesions of the ACC have led to a range of outcomes, including


inattention, dysregulation of autonomic functions, and emotional instability 

(Kennard, 1954; Tow and Whitty, 1953). ACC lesions as a treatment for 

affective disorders in humans have produced decreased distress and emotional 

liability (Corkin, 1979). More recently, deactivation in the dorsal ACC, an area 

associated with cognitive monitoring and behavioral regulation (Bush et al., 

2000), has been noted in aggressive youth compared to controls (Sterzer et al., 

2005). Reduced activation in the ACC is also associated with “novelty seeking” 

(Cloninger, 1987), a dimension of temperament encompassing a quick-tempered 

personality and high impulsivity (Stadler et al., 2007). Thus, reduced activation 

of the ACC may be a connection between temperament, behavior, and emotion 

processing (Sterzer et al., 2005). 

3. Prefrontal cortex 

The prefrontal cortex (PFC) modulates subcortical behavior (Siever, 2008), 

specifically by inhibiting connections between the amygdala and hypothalamus, 

thereby resulting in increased aggression (Davidson, 2000). Prefrontal lesions in 

humans as a result of tumors, trauma, or metabolic disturbances have been 

instrumental in illustrating the role of the PFC in aggressive behavior (Siever, 

2008). The well-known case of Phineas Gage, a stable and dependable railroad 

worker who became irritable, angry, and showed poor judgment following an 

accident in which a rod entered his skull at the frontal cortex, is a prime example 

of the critical role of the PFC in monitoring aggression. 

Imaging studies exploring brain functioning have further elucidated the 

role of the frontal cortices in modulation of aggression. Individuals with lowerthan-average 

baseline activity in the frontal cortex demonstrate higher levels of 

reactive or impulsive aggression (Coccaro and Kavoussi, 1997; Soloff et al., 2003; 

Volkow et al., 1995). Moreover, the ventromedial prefrontal cortex (vmPFC) has 

been specifically implicated in the calculation of reward expectation (Elliott and 

Deakin, 2005), and increased activation is observed in the vmPFC when errors 

are made during a reversal learning task (Finger et al., 2008). Reversal learning 

tasks are designed to frustrate participants and measure their ability to adjust 

behavior in response to changing reinforcement (i.e., avoid frustration; Rolls 

et al., 1994), a deficit observed in individuals with psychopathic traits (Blair 

et al., 2001; Budhani and Blair, 2005). Violations of reward expectations (i.e., 

expecting but not receiving reinforcement) have been linked to frustration and 

reactive aggression (Berkowitz, 1989), which may be a result of not achieving an 

expected reward (Sterzer et al., 2005). Thus, increased vmPFC responses to 

violations of expectations may indeed be associated with an increased risk of 

frustration and subsequent aggressive or violent behaviors (Blair, 2010).


Experimental animal studies indicate a connection between the orbitofronal 

cortex (OFC) and aggressive behavior, particularly with regard to the 

interpretation of social cues and behavioral responses in social contexts (Nelson 

and Trainor, 2007). OFC lesions in male rhesus monkeys increase aggression in 

dominant but not in subordinate animals (Machado and Bachevalier, 2006). 

Butter and Snyder (1972) observed similar results, but these effects diminished 

over several months. In humans, structural abnormalities in the OFC, such as 

reduced levels of gray-matter volume in youth with CD (Huebner et al., 2008) 

and early brain damage in this region have also been associated with conduct 

problems (Anderson et al., 1999). Overall, dysfunction in the prefrontal regions 

of the brain appears to underlie impaired regulation of affective responses and 

reduced inhibition of aggression (Davidson, 2000). 

4. Hypothalamus 

The hypothalamus is another critical brain structure involved in the development 

of aggression. Research with nonhuman primates suggests that electrical 

stimulation of the ventromedial hypothalamus is linked to vocal threats and 

aggressive behaviors in marmosets (Lipp and Hunsperger, 1978), while lesions of 

the anterior hypothalamus reduce vocal threats toward a male intruder (Lloyd 

and Dixson, 1988). Electrical stimulation of the anterior hypothalamus increases 

vocalizations in rhesus monkeys (Robinson, 1967) and aggression toward insubordinate 

male rhesus monkeys (Alexander and Perachio, 1973). Similar findings 

have been found with electrical stimulation of the hypothalamus in male rats 

(Kruk, 1992) and cats (Siegel and Victoroff, 2009). In humans, the frontal cortex 

inhibits circuits in the hypothalamus that increase aggression (Davidson, 2000). 

During a period in the mid-twentieth century, electrolytic lesions of the hypothalamus 

were used as a treatment for “excessive aggression” (Heimburger et al., 

1966). Although conclusions from such studies should be interpreted cautiously 

for both methodological and ethical reasons (Scarpa and Raine, 1997), these 

lesions were found to inhibit aggression in humans. 

C. Neurochemical signals of aggression and violence 

Specific signaling molecules have provided additional information about neural 

circuits underlying aggression. As experimental research has turned to the brain 

for answers regarding the development of aggression and violence, the neurochemistry 

of aggressive behavior has also come to the forefront. In general, 

neurotransmitters in the brain either increase or inhibit aggressive behavior. 

Below is a brief review; a more extensive review of this area of research can be 

found in a separate chapter in this volume.


1. Neurotransmitters-serotonin 

Given the connection between emotion, cognition, and aggression, it seems 

fitting that many studies have focused their investigation on serotonergic neurotransmission, 

a system predominantly involved in the regulation of emotional 

states. Serotonin (5-HT) receptors in specific regions of the brain, such as the 

OFC and ACC, are involved in the modulation and suppression of aggressive 

behavior (Siever, 2008). Moreover, low levels of 5-HT are associated with 

increased aggression in humans (Chiavegatto et al., 2001) and nonhuman primates 

(Higley et al., 1992). Many studies have investigated the role of 5-HT in 

neuronal functioning and aggression. For example, Frankle et al. (2005) reported 

reduced 5-HT transporter distribution in the ACC of patients with aggressive 

personality disorder compared to healthy controls. Reduced prefrontal activation 

was observed in response to a serotonergic releasing agent (d, 1-fenfluramine) in 

individuals with impulsive aggression, such as those diagnosed with borderline 

personality disorder (Soloff et al., 2003), and in depressed patients with a history 

of suicidal behavior (Mann et al., 1992). Using positron emission tomography 

(PET) technology, Parsey et al. (2002) found a negative association between 

scores on the Lifetime History of Aggression scale and 5-HT receptor-binding in 

the PFC and amygdala. Further, individuals with high levels of impulsive aggression 

display reduced activation in the PFC (Coccaro and Kavoussi, 1997). 

Further, New et al. (2004) found that individuals with borderline personality 

disorder, who underwent 12 weeks of selective serotonin reuptake inhibitor 

(SSRI) treatment, increased baseline PFC activation, which was negatively 

correlated with ratings of aggression. 

2. Neurotransmitters-dopamine 

Dopamine (DA) has been implicated in the initiation and exhibition of aggression 

(de Almeida et al., 2005), yet its precise role remains unclear. Ferrari et al. 

(2003) found that rats can be conditioned to increase dopamine secretion and 

decrease levels of 5-HT in anticipation of aggressive interactions, whereby DA 

and 5-HT levels in the nucleus accumbens were measured during and following a 

confrontation with another rat using microdialysis. Heart rate (HR) also 

increased 1 h prior to the regularly scheduled interactions. Antagonists of both 

D 1 and D 2 receptors appear to reduce aggression in male mice (de Almeida et al., 

2005). Further, animal studies suggest that the activation of catecholaminergic 

brainstem neurons (e.g., ventral tegmental area) project to dopaminergic structures 

in the forebrain, such as the hypothalamus and the limbic system (e.g., 

amygdala, hippocampus, PFC, and ACC). In humans, both proactive and reactive 

aggressions are associated with dopamine (Siegel and Victoroff, 2009). In 

clinical populations, decreased D 1 receptors have been observed in depressed


individuals suffering from anger attacks (Dougherty et al., 2006). Psychopharmacological 

agents most frequently employ compounds that act on dopaminergic 

systems in the brain (McDougle et al., 1998). Risperdone, a D 2 antagonist, 

effectively reduces aggression in humans (Nelson and Trainor, 2007). Moreover, 

haloperidol, another D 2 antagonist, is used in the treatment of aggression in 

psychotic patients (Fitzgerald, 1999), of violent outbursts in adults with borderline 

personality disorder and dementia, and of aggression in children and adolescents 

(Beauchaine et al., 2000). 

3. Neurotransmitters-norepinephrine 

Norepinephrine (also known as noradrenaline) is a monoamine found in the 

ANS. It is associated with arousing situations and has been specifically cited in 

the development of both proactive and reactive aggression (Siegel and Victoroff, 

2009). Interestingly, a meta-analysis of central (cerebrospinal fluid) measures of 

norepinephrine found a negative association between norepinephrine and antisocial 

behavior (Raine, 1993). Plasma levels of norepinephrine are also associated 

with induced hostile behavior during experiments with healthy controls 

(Gerra et al., 1997). Pharmacological manipulation studies of noradrenaline 

levels and noradrenergic receptors suggest that this catecholamine facilitates 

the development of aggression (Miczek et al., 2002). Further evidence from the 

animal literature demonstrates that DA beta-hydroxylase knockout mice are 

unable to produce noradrenaline and display reduced levels of aggression, but 

normal levels of anxiety (Marino et al., 2005). 

D. Hormones 

Hormonal factors have long been studied in relation to aggressive behavior, 

particularly as scientists sought an explanation for the notable gender differences 

in the rates of violence. Androgens, and in particular testosterone, have received 

the most attention in this regard. Research on hormones and aggression has not 

demonstrated a one to one relationship between these factors. Instead, empirical 

findings suggest that the type of aggressive behavior and the structure and quality 

of the social environment are likely important moderators in the association 

between hormones and aggression. 

1. Testosterone 

A positive relationship between testosterone and aggression is well established in 

the animal literature, but less support for this association has emerged in humans 

(Archer, 1991). Injections of testosterone increase aggression in a variety of


animals (Monoghan and Glickman, 1992), and aggression has been positively 

associated with territorial behavior in birds (Wingfield and Hahn, 1994). Moreover, 

testosterone increases the display of dominance behaviors in rhesus 

monkeys (Rose et al., 1971). Further, the castration of lizards (Greenberg and 

Crews, 1983) and male mice (Vom Saal, 1983) leads to reduced aggression. 

While some research with humans indicates that testosterone is associated with 

anger and aggression (Olweus, 1986), evidence from the broader literature is 

mixed (Archer, 1991). Some studies have revealed positive relationships between 

testosterone and aggression, some report negative relationships, and no 

association is found in others (van Bokhoven et al., 2006). Specifically, testosterone 

measured in cerebrospinal fluid, serum, and saliva have been linked to 

chronic aggression (Ehrenkranz et al., 1974), violent crimes (Dabbs et al., 1987), 

antisocial personality disorder (Dabbs and Morris, 1990), and peer ratings of 

“toughness” (Dabbs et al., 1987). However, many studies have not replicated 

these results (Bain et al., 1987) and a metanalytic study of community and 

selected samples found only modest correlations (i.e., between 0.08 and 0.14) 

between testosterone and aggression (Archer et al., 2005). Mixed findings have 

similarly been observed in adolescents (Olweus et al., 1988; Susman et al., 1987). 

These inconsistent results may be partially attributable to social and developmental 

factors (Rowe et al., 2004), as well as other hormones, such as cortisol 

(Popma et al., 2007b). 

2. Cortisol 

Cortisol is the end product of the hypothalamic-pituitary-adrenal (HPA) axis, 

the human body’s stress response system, and is often used as a marker of stress 

responsiveness. Literature regarding the relationship between cortisol and aggression 

is mixed. Although numerous studies suggest that lower basal cortisol 

levels are associated with increased disruptive behaviors in males (Hawes et al., 

2009; Popma et al., 2007a), other studies report the opposite, with CD and 

aggression being associated with higher levels of cortisol (Alink et al., 2008; 

Van Bokhoven et al., 2005). Still other studies have not established any link 

between cortisol and aggressive behavior (Alink et al., 2008; Scerbo and Kolko, 

1994; van Goozen et al., 2000). A significant amount of research has focused on 

an association between an underreactive HPA axis and aggressive behaviors. 

Theoretically, this underreactivity may be associated with reduced comprehension 

of distress cues, which has been related to reduced empathy and behavioral 

inhibition (Marsh et al., 2008). Lower levels of cortisol are also linked with 

reductions in fear responsiveness (Cima et al., 2008), which may lead to persistent 

aggressive behavior (McBurnett et al., 2000). In reviewing the divergent 

findings linking cortisol levels and aggression, Hawes et al. (2009) proposed two


hormonal pathways to antisocial behavior—one which links stress exposure to 

high cortisol and aggression and the other which links low cortisol to aggression 

through callous-unemotional traits. In support of this proposal, a recent empirical 

study found that changes in cortisol levels in response to a stressor were 

positively associated with reactive (but not proactive) aggression in boys (Lopez- 

Duran et al., 2009). 

3. Oxytocin 

Recently, the hormone oxytocin has been investigated as a possible link in the 

development of aggression. Oxytocin is a hormone that is involved in trust and 

affiliative behaviors (Insel and Winslow, 1998; Young et al., 2001), thereby 

reduced oxytocin is thought to be associated with increased aggression. This 

hypothesis has been supported in the animal literature as oxytocin knockout 

mice exhibit increased aggressive behavior (Ragnauth et al., 2005). In humans, 

adults administered oxytocin intranasally are significantly better at identifying 

happy facial expressions compared to other expressions (Marsh et al., 2010). 

Oxytocin has also been found to reduce activation in the amygdala (Kirsch, 

2005). Taken together, data suggest that deficits in oxytocin may 

influence mistrust and hostility which can contribute to aggression and violence 

(Siever, 2008). 

E. Autonomic response measures 

Autonomic arousal is most commonly measured via HR and electrodermal 

activity (EDA). In general, research regarding autonomic arousal and aggressive 

and violent behavior has yielded findings suggesting a pattern of lower baseline 

levels of autonomic arousal and higher autonomic reactivity in children and 

adolescents (Patrick, 2008). Although less consistent, research on aggressive 

adults indicates an increase in autonomic activity in response to a stressor 

(Patrick, 2008). A met analysis by Lorber (2004) found a reliable but modest 

association between the autonomic measures of HR and EDA and aggression and 

conduct problems. Below is a brief review of the specific associations between 

HR and EDA and aggression and violence. 

1. Heart rate and electrodermal activity 

Low resting HR is a common phenomenon among aggressive children (Scarpa 

and Raine, 1997) and is associated with conduct problems throughout childhood, 

adolescence, and adulthood (Lorber, 2004). Evidence for HR reactivity is 

less consistent. It appears that aggressive children have increased HR in response


to a stressor (Lorber, 2004), and this finding is particularly robust in children 

displaying reactive aggression rather than proactive aggression (Hubbard et al., 

2002). HR reactivity and its association with aggression in adults are also mixed. 

EDA refers to small changes in electrical activity of the skin, usually 

occurring 1–3 s following the onset of a stimulus (Scarpa and Raine, 1997). 

Lorber (2004) found that conduct problems in childhood were associated with 

reduced EDA in the absence of stimulation, and reduced EDA during a task, but 

only in the presence of nonnegative stimuli. This met analysis also revealed a 

positive association between adult aggression and EDA reactivity. Scarpa and 

Raine (1997) suggested that EDA under arousal may be associated with specific 

forms of crime, such as crimes of evasion. Skin conductance levels have also been 

shown to interact with markers of the HPA axis to predict later externalizing 

behaviors in children (El-Sheikh et al., 2008). Results indicate that children with 

higher levels of EDA and higher levels of cortisol display increased levels of 

externalizing behaviors. 

F. Electro cortical response measures 

Electroencephalography (EEG) uses electrodes placed around the scalp at specified 

points to measure electrical activity of the brain. EEG evidence suggests that 

slow-wave activity during adolescence may predict later antisocial behavior 

(Raine et al., 1990). These findings have been interpreted to suggest that cortical 

immaturity leads to reduced inhibition (Volavka, 1999) and increased impulsive 

behavior. EEG abnormalities, specifically under arousal and cortical immaturity, 

have been reported in violent recidivistic offenders (Raine et al., 1990). 

Event-related potential (ERP) refers to the averaged changes in electrical 

brain activity in response to a stimulus. Literature on ERP and aggressive 

behavior is mixed. One consistent finding has been the association between 

reduced amplitude of the P300 wave response, an ERP elicited by infrequent 

stimuli, among aggressive and impulsive individuals (Gerstle et al., 1998). The 

P300 is thought to reflect online updating of cognitive representations (Donchin 

and Coles, 1988), thus the reduced amplitude may suggest impairment in higher 

cognitive functioning (e.g., working memory) in these individuals (Patrick, 

2008). Reduced P300 has been reported in antisocial personality disorder 

(Bauer et al., 1994), as well as other disorders that involve impaired impulsivity 

such as child CD and ADHD, drug dependence, and nicotine dependence 

(Iacono et al., 2002). Therefore, reduced P300 amplitude may be a reflection of 

impulse control, a characteristic of reactive aggression (Patrick, 2008). 

The physiological findings presented above illustrate the apparent 

biological underpinnings involved in the development of aggression and violence. 

Research from physiological and neurobiological studies has provided 

significant evidence for the biological basis of violent and aggressive behavior.


Taken together, the neurobiological and psychophysiological findings suggest a 

model in which aggression arises due to dysfunction in brain areas responsible for 

emotion processing, inhibition, and reactivity (Davidson, 2000). Repeated aggression 

may contribute to deficits in recognizing and processing of emotion, as 

well as the regulation and modulation of aggressive behavior in response to 

threat. Reduced activation and distribution of neurotransmitters in areas of the 

brain implicated in the development of violent behavior, in combination with 

dysregulation of the body’s hormonal responsiveness, may add to difficulties in 

controlling aggressive outbursts. Furthermore, reduced arousal to distressing 

stimuli, as evidenced by a diminished physiological response and electrical 

activity in the brain may contribute to further deficiencies in appropriate 

responses to increased arousal. Further research is necessary to provide additional 

evidence for this suggested model. 

As the field progresses, particular attention should be paid to the 

subtypes of aggressive behavior that may be characterized by unique physiological 

patterns. Future studies should focus on parsing the different types of aggression 

to elucidate the specific pathways underlying violent behaviors. A better 

understanding of these pathways allows for earlier intervention that may be able 

to reduce or prevent severe aggressive behavior later in life. With the knowledge 

of the psychophysiology associated with the development of violence throughout 

the lifetime, we now turn specifically to the perinatal period to better understand 

how these biological pathways can be altered to prevent or lead to later violence. 

III. PERINATAL FACTORS RELATED TO THE DEVELOPMENT 

OF AGGRESSION 

The notion of a mother’s health affecting that of her unborn infant is one that 

has pervaded common knowledge for centuries. Only recently, however, have 

scientists begun to empirically study the specific factors influencing fetal development. 

Preterm birth, delivery complications, maternal mental illness, gender, 

and exposure to drugs, alcohol, and tobacco are all topics that have been 

explored in relation to their impact on fetal development. These factors have 

been shown to have maladaptive effects on fetal brain development following 

prenatal exposure—a finding that makes pregnancy a critical window for the 

prevention of unfavorable outcomes throughout the lifespan of the offspring. 

One such risk that has been identified in relation to these perinatal factors is the 

development of aggression. It has been suggested that through disruptions in 

neural development, the fetus incurs neuropsychological deficits—namely neural 

impairments in executive and verbal functioning that may result in an irritable 

disposition, poor behavioral regulation, or aggression (Brennan et al., 2003). This 

tendency toward aggression tends to persist throughout adolescence and into


adulthood, manifesting itself through externalizing behaviors, internalizing problems 

(depression, loneliness, etc.), poor peer relationships, psychological disorders 

(CD, oppositional defiant disorder, etc.), recurring criminal behaviors, 

and violence. Because of the extensiveness of the risks associated with aggression, 

it has many potentially negative outcomes both in the developing infant, as 

well as in the significant economic and social burdens it places on society. In this 

section, the potential influences of the aforementioned perinatal factors will be 

explored in their relation to the development of aggression and violence. It is 

important to note that these risks do not necessitate the development of aggression 

in offspring but rather are important in understanding certain conditions in 

which aggressive traits may be more likely to arise. 

A. Birth complications 

Many studies have found associations between birth complications and negative 

behavioral outcomes in offspring. Specifically, irritable temperament in childhood, 

violent offending in adolescence and adulthood, and aggressive behaviors 

throughout the lifespan are among the offspring outcomes that have been 

associated with higher rates of birth complications. Birth complications typically 

refer to the following three factors: (1) prenatal complications, such as hypertension, 

mental illness, stress, drug and alcohol exposure, and viral infections 

experienced by the mother; (2) perinatal complications, which include difficult 

fetal delivery (e.g., breech birth), premature breaking of the membrane, assisted 

delivery (forceps and cesarean), fetal distress (i.e., difficulty breathing), preeclampsia, 

and umbilical cord prolapsed; and (3) postnatal complications as 

indicated by either cyanosis or treatment with oxygen (Liu et al., 2009). 

The mechanisms through which birth complications may influence the 

development of aggression are unknown, but they are hypothesized to involve 

damage to the PFC, hippocampus, and dopamine systems (Brennan et al., 1997; 

Cannon et al., 2002; Mednick and Kandel, 1988; Raine, 2002b). More specifically, 

preeclampsia, maternal bleeding, and maternal infection may cause an 

inadequate supply of blood to the placenta, fetal hypoxia or anoxia (lack of 

oxygen), and disrupted development of the hippocampus, dopamine systems, and 

other parts of the brain (Cannon et al., 2002; Liu, 2004; Mednick and Kandel, 

1988). Animal research has supported these findings by suggesting that perinatal 

complications surrounding anoxia in rats may reduce central dopamine transmission 

(Brake et al., 2000). Dopaminergic neurotransmission appears to be 

involved in impulse control, aggression, and violence (Chen et al., 2005; Retz 

et al., 2003). Animal research also suggests that perinatal complications may 

limit neurotransmitter functioning in the left PFC—an effect that has been one 

of the most frequently replicated indicators of violent offending in the brain 

imaging literature (Henry and Moffitt, 1997). It is important to note, however,


that birth complications alone are unlikely to predispose infants to externalizing 

behavior and aggression. Instead, these complications interact with various 

psychosocial risk factors (i.e., poverty, poor parenting, parental rejection, negative 

peer relationships, bad neighborhoods, etc.), and likely genetic factors, to 

influence aggressive tendencies (Raine et al., 1994). 

Prenatal, perinatal, and postnatal health care interventions aimed at 

reducing birth complications may help to decrease risks of later development of 

aggression and violence. If women who may be at risk for birth complications are 

identified and educated, these mothers may be in a better position to take steps 

toward keeping their pregnancies and their babies healthy. If, however, birth 

complications do occur, early enrichment programs, that improve cognitive 

ability or enhance the parent–child relationship, may be effective in preventing 

the emergence of aggressive and violent behavior in adolescence and adulthood. 

B. Preterm birth and low birth weight 

Research supporting the role of neuropsychological deficits in mediating birth 

complications and adverse outcomes is consistent with preterm and low birth 

weight literature. White et al. (1994) have shown that medical and congenital 

risk factors, such as low birth weight and preterm birth, may lead to neuropsychological 

deficits and CNS damage that result in an increased likelihood for 

criminal offending. Evidence also suggests that preterm birth may be involved in 

the development of externalizing behaviors and aggression, and that these 

negative behavioral outcomes worsen with age (Bhutta et al., 2002). 

Low birth weight and preterm birth serve as strong and consistent 

predictors of neuropsychological deficits that may result in subsequent aggression 

and antisocial behavior (McCormick, 1985). Low birth weight infants were three 

times more likely to experience neurological deficits than controls (McCormick, 

1985). Moreover, such CNS deficits (Moffitt, 1993) may manifest themselves in 

a variety of ways, including temperamental difficulties, cognitive deficits, inattention, 

antisocial behavior, subnormal growth, learning difficulties, hyperactivity, 

behavioral problems, poor academic achievement, CNS damage, and 

psychiatric disorders (Piquero and Tibbetts, 1999). 

Preterm birth and low birth weight have been found to be correlated 

with maternal tobacco use, lack of prenatal care, drug and alcohol use by the 

mother during pregnancy, low socioeconomic status, poor diet, psychotropic drug 

use during pregnancy, and low parental educational level (Piquero and Tibbetts, 

1999). Because of the range of factors that might cause preterm birth and low 

birth weight in an infant, preventative efforts are critical. 

It is important to note that the effects of preterm birth and low birth 

weight on psychological functioning and aggression may vary depending on the 

sex of the child. For example, low birth weight boys exhibit a significantly more


aggressive and delinquent acts in comparison to their female counterparts (Ross 

et al., 1990). There is also considerable evidence suggesting that disadvantaged 

home environments and maternal interactive style may moderate the relationship 

between these risks and aggressive behaviors (Piquero and Tibbetts, 1999). 

Therefore, a number of factors, such as sex, home environment, and maternal 

interactive style, are involved in the phenotypic expression of aggression in 

premature and low birth weight infants. 

Despite the decrease in infant mortality over the past 30 years, the 

prevalence of preterm birth and low birth weight has actually increased to 

approximately 12.5% of births in the United States. Given the prevalence of 

preterm birth and low birth weight in the United States, it is understandable why 

risk factors associated with this population are such a major public health 

concern (Berman and Butler, 2006). Preventative measures and public awareness 

campaigns focusing on the risks involved in preterm birth and low birth weight 

are a necessary next step in addressing these issues. 

C. Prenatal drug and alcohol exposure 

1. Alcohol 

Sixteen percent of children born in the United States are exposed prenatally to 

alcohol, making alcohol the most common neurobehavioral teratogen affecting 

fetal development (Sood et al., 2001). Overall, children who are prenatally 

exposed to alcohol are 3.2 times more likely to develop aggression and delinquent 

behavior than nonexposed children. Further, children exposed to low 

levels of alcohol prenatally show higher scores for aggressive and externalizing 

behaviors on the Child Behavior Checklist (CBCL) and children exposed to 

moderate levels have higher scores on delinquent and total problem behavior on 

the CBCL (Sood et al., 2001). This suggests a higher threshold for the development 

of delinquency in children, as opposed to aggressive and externalizing 

behaviors. However, it also negates claims that low levels of alcohol consumption 

during pregnancy are tolerable with evidence that suggests that even a small 

dose may have adverse effects on fetal development. More generally speaking, 

the literature supports a dose–response continuum where a more heavily exposed 

fetus shows a greater magnitude of these adverse effects (Driscoll et al., 1990). 

Fetal alcohol spectrum disorder (FASD) and fetal alcohol syndrome 

(FAS) are conditions that may arise when children are prenatally exposed to 

alcohol. These disorders are characterized by physical and mental birth defects 

that may result in impaired interpersonal skills and social deficits. Some of the 

behaviors that are commonly observed among populations of FAS individuals 

are tendencies to demand attention, interrupt others, lie, show impaired moral 

judgment (especially with regard to social relationships), overreact to situations


with excessively strong emotional responses, monopolize conversations, and 

demonstrate unawareness of the consequences of one’s actions. This population 

may also suffer major language and social communication deficits, which further 

hamper their social competence (Kelly et al., 2009). 

Animal studies have helped in linking prenatal alcohol exposure to the 

development of aggressive behaviors. Specifically, evidence suggests that alcohol 

exposure during prenatal development causes CNS damage. Rats provide an excellent 

model for understanding the development of aggression, because their social 

behavior has been shown to follow similar patterns to that of humans. Their social 

behavior results from a combination of influences including genetic makeup, teratogenic 

influences, early maternal–infant interactions, and later social learning. 

Primates, too, offer a suitable model for studying the effects of prenatal alcohol 

exposure, as their gestation characteristics and early developmental stages are 

similar to that of humans. In both animals and humans, prenatal alcohol exposure 

is not considered a singular cause of social deficits, but rather a probabilistic 

contributor serving as a risk factor for the developing child (Kelly et al.,2000). 

Because there are social–familial influences associated with prenatal 

exposure to alcohol, one might ask how it can be determined that alcohol 

exposure has any actual teratological effect. Animal models provide a means 

through which alcohol- and environment-related factors can be separated in an 

experimental fashion. For example, removing a newborn pup from its “alcoholusing” 

mother and transferring it to a foster-parent environment results in rates 

of aggression that are analogous to those remaining in the care of their “alcoholusing” 

mothers, suggesting that changes in aggressive behavior are initiated by 

the pup’s prenatal exposure to alcohol, rather than by its environment. This type 

of experiment, for obvious reasons, would be ethically impossible to conduct in 

human populations (Kelly et al., 2000). 

Animal models have contributed essential components to our understanding 

of the specific mechanisms through which prenatal ethanol (alcohol) 

exposure and aggression are linked. Rodent studies suggest that the behavioral 

deficits that result from ethanol exposure in utero are linked to ethanol-induced 

changes in the CNS. These changes in the CNS, however, are not uniform, and 

some brain regions (i.e., neocortex, hippocampus, cerebellum) are more affected 

than others. Notably, the HPA axis and beta-endorphin (b-EP) systems become 

dysregulated and hyperresponsive to social situations, which is demonstrated by 

heightened and prolonged concentrations of hormones, such as corticosterone 

(CORT) and adrenocorticotropin (ACTH), as well as elevated plasma levels and 

reduced pituitary content of b-EP compared to controls. Further, ethanol-exposed 

neonates show heightened sensitivity to stressors, significantly increased corticotrophin 

release factor (CRF) biosynthesis and expression, and more prolonged 

CORT and ACTH elevations during and after stress. These effects, which persist 

throughout the neonate’s lifespan, indicate deficits in pituitary–adrenal response


inhibition and in recovery from stress. It is through these mechanisms that 

prenatal alcohol exposure may manifest in aggressive tendencies and externalizing 

behaviors in the lives of effected offspring (Weinberg et al., 1996). 

2. Drugs 

Drug use by pregnant women has increased steadily. Despite general awareness of 

detrimental effects, drug use during pregnancy continues its upward trend with 

prevalence estimates ranging from 0.3% to 46%. Prenatal drug exposure is associated 

with behavioral abnormalities, such as excessive irritability, poor socialattachment 

behavior, and aggression (Johns et al., 1994). The neurobiological 

processes through which these deficits emerge primarily involve the effects of 

drugs on fetal organogenesis, especially fetal brain development (Mayes, 1994). 

Evidence suggests that an increase in aggressive or violent behaviors associated with 

prenatal drug use may arise from alterations in the CNS. More specifically, aggressive 

behaviors can be linked to changes in fetal neurotransmitter systems, particularly 

within the limbic system (Miller et al., 1991). Cocaine (including crack 

cocaine) is one of the most commonly studied CNS stimulants in the literature on 

prenatal drug exposure. Cocaine affects monoaminergic neurotransmitter (dopamine, 

norepinephrine, and 5-HT) systems in the CNS by blocking the reuptake of 

dopamine, norepinephrine, and 5-HT leaving more of these neurotransmitters 

within the synaptic space (and therefore the peripheral blood). An excess in the 

amount of these neurotransmitters results in psychological effects, such as pleasure 

and euphoria, as well as specific behaviors and physiological reactions. Physiologically, 

chronic cocaine use may lead to tolerance whereby increasing amounts of the 

drug are necessary to achieve a desired effect. 

In the developing fetus, monoaminergic neurotransmitters play a critical 

role in fetal brain development by influencing cell proliferation, neural 

outgrowth, and synaptogenesis (Lauder, 1988; Mattson, 1988). Cocaine and 

other drugs may affect these neural processes throughout gestation through 

their effects on the release and metabolism of monoamines. The importance of 

monoamine neurons in fetal brain development has been demonstrated in both 

human and animal models. For example, in the rats’ second week of gestation, 

norepinephrine neurons appear in the locus coeruleus, 5-HT neurons are found 

in the raphe nuclei, and dopaminergic neurons in the substantia nigra are 

functional (Lauder and Bloom, 1974). By the end of the second month of 

human gestation, 5-HT and norepinephrine neurons can be found. In both 

animals and humans, these monoamine neurons are rapidly generating axonal 

connections with the forebrain and actively influencing the production and 

differentiation of cell structure in these regions (Lidov and Molliver, 1982a,b; 

Wallace and Lauder, 1983).


Further evidence of these effects can be demonstrated by administering 

cocaine to rats during the early postnatal period when synaptogenesis begins in 

the forebrain. This early postnatal period in rats is functionally equivalent to the 

third trimester in human gestation during which axonal and dendritic growth 

take place. When brain glucose metabolism is used as an indicator of activity, 

animal models exhibit the greatest percentage change in brain regions with high 

dopaminergic activity in comparison to untreated controls (Dow-Edwards et al., 

1988, 1989). Several brain structures associated with the mesocortical and 

mesolimbic systems, including the cingulate cortex, PFC, nucleus accumbens, 

amygdala, septum, ventral tegmental area, and ventral thalamic nucleus, appear 

highly affected by dopamine activity (Goeders and Smith, 1983; Shepard, 1988). 

Each of these areas is thought to be involved in an organism’s arousal, attention, 

and ability to regulate anxiety and emotional responses (Mayes, 1994). 

The neural processes mentioned above may lead to the development of 

aggression when abnormalities in fetal brain development later manifest themselves 

in social and behavioral ways. Basic processes, like the regulation of 

attention, response to sensory stimuli, and the modulation of mood states may 

all be linked to prenatal drug exposure through the drug’s alterations of neurotransmitter 

activity. Several studies have found that infants exposed to drugs 

prenatally are often easily irritable and difficult to engage. Evidence also suggests 

that prenatal drug exposure results in crying patterns that indicate a general 

“excitable” tendency within affected infants. Human infants exposed prenatally 

to cocaine have also shown elevated HRs and norepinephrine levels at 2 months 

of age; lending further support to the influence cocaine has on monoaminergic 

systems (Mayes, 1994; Mirochnick et al., 1991). Rodent models have demonstrated 

an increased susceptibility to stressors, higher vulnerability to the environment, 

and increased rates of aggressive behaviors in response to social 

competition among offspring prenatally exposed to drugs (Spear et al., 1998). 

The influence of prenatal exposure to drugs and alcohol on social and 

aggressive behavior has serious implications for crime prevention. Early identification 

and intervention among infants and children who may be affected by 

prenatal drug or alcohol exposure is necessary to prevent delinquency and poor 

social relationships within these populations (Johns et al., 1994). Such steps are 

also necessary for gaining a better understanding of the behavioral differences 

that may exist within educational, occupational, and social settings due to 

prenatal exposure to drugs and alcohol. 

D. Smoking 

Smoking during pregnancy remains a critical public health concern. Nearly half of 

all women who smoke continue to do so even while pregnant, despite some women’s 

intentions to refrain from doing so. Despite common knowledge of the adverse


effects of maternal smoking during pregnancy among the American public, more 

than half a million infants per year in the United States are prenatally exposed to 

maternal smoking (Wakschlag et al., 2002). This is of even greater concern when 

one considers the failure of public health smoking cessation campaigns for the 

10.2% of women in the United States who continue to smoke through their 

pregnancies. Adverse outcomes, which include low birth weight, premature delivery, 

spontaneous abortion, and infant mortality, have been the primary focus of 

these campaigns (Weaver et al.,2007). In comparison, relatively little attention has 

been paid, from a public health standpoint, to the relationship between prenatal 

smoking and the development of aggression and violence in offspring. 

Prenatal smoking predicts children’s likelihood of displaying high aggression 

from as early as 1.5 years and throughout adulthood (Huijbregts et al., 

2008). Several externalizing behaviors, including impulsivity, truancy, hyperactivity, 

attentional difficulties, and delinquency, have all been found to be 

associated with maternal prenatal smoking through the fetus’ exposure in 

uterine. 

Potential neurobiological mechanisms through which prenatal nicotine 

exposure may increase the offspring’s risk for aggressive behaviors include the 

HPA axis and the CNS (Brennan et al., 1997). Substantial evidence suggests 

that nicotine crosses the placental barrier and causes neurotoxicity in the fetus. 

Neurotoxicity occurs via hypoxic effects on the fetal-placental unit (e.g., reduction 

of fetal blood flow) and teratological effects on the developing fetal brain. 

Two recent human studies support this contention, noting associations between 

maternal prenatal smoking and decreased frontal lobe volumes in infants (Ekblad 

et al., 2010), and a thinning of the cerebral cortex in adolescents (Toro et al., 

2008). Within the HPA axis, nicotine produces a heightened ACTH response to 

stress in adult rats (Poland et al., 1994). Other studies have found that elevated 

levels of ACTH increase aggressive and defensive behaviors in both rats and 

nonhuman primates, suggesting that this hormone may be related to the development 

of aggression (Higley et al., 1992; Veenema et al., 2007). However, lower 

levels of ACTH have also been found within human criminal and antisocial 

populations in comparison to controls, so these results are mixed and should be 

interpreted with caution (Coccaro and Siever, 2002; Virkkunen et al., 1994). 

Nicotinic acetylcholine receptors (nAChRs) are responsible for the 

regulation of many vital phases of brain maturation. These receptors are present 

in the brain early in gestation and develop throughout prenatal, postnatal, and 

adolescent periods, suggesting that nicotinic signaling plays a crucial role in neural 

development. During these developmental periods, NAChRs are particularly 

sensitive to environmental stimuli and, as specific nicotine-sensitive receptors, 

are especially vulnerable to exogenous nicotine. Nicotine affects fetal development 

primarily through its effect on nicotinic-binding sites in the cerebral cortex. 

More specifically, nicotine has been found to alter the neocortex, hippocampus,


and cerebellum during the early postnatal period within rats (the equivalent of the 

third trimester in humans; Dwyer et al., 2009). Evidence suggests that prenatal 

nicotine-induced defects within these particular brain regions may increase the 

likelihood of dopamine-mediated disorders like attention deficit hyperactivity 

disorder and substance abuse. Patterns of continuous maternal smoking (i.e., the 

tendency to smoke in a way that maintains plasma nicotine levels at a steady state) 

cause more negative effects than more periodic patterns of use, which allow the 

CNS to recover between episodes. The stimulation to nicotinic receptors interacts 

with the genes that influence differentiation of cells, causing permanent changes 

in cell functioning. It has been suggested that these processes disrupt the maturation 

of the fetal brain and produce adverse effects in fetal development that can 

later manifest themselves in aggression or violence (Wakschlag et al., 2002). 

Animal models demonstrate many of the biological effects of prenatal 

smoking on neonatal behavior. Rats exposed to nicotine prenatally show deficits 

in learning and memory, as well as in social behavior. Benowitz (1998) found 

that nicotine infusion in rats causes interference with neural cell replication and 

abnormal synaptic activity. These, in turn, produce neuroendocrine and behavioral 

abnormalities that could potentially lead to aggression. Rodent models have 

also shown similar adverse effects linked to second hand smoke, as well as 

maternal use of nicotine replacement therapy (NRT), a pharmacotherapy of 

smoking cessation thought to be less detrimental than smoking cigarettes during 

pregnancy (Dwyer et al., 2009). Findings of adverse effects related to maternal 

use of NRT are particularly disturbing, since (1) NRT does not seem to increase 

the likelihood of successful smoking cessation during pregnancy and (2) NRT 

has actually been recommended by a number of public health authorities, 

including the Food and Drug Administration (Bruin et al., 2010). NRT (as 

well as cognitive-behavioral therapy (CBT)) has been shown to be effective 

among nonpregnant smokers, so prevention rather than smoking cessation 

during pregnancy should be the aim for reducing adverse outcomes attributed 

to prenatal nicotine exposure. Further, interventionists should keep in mind that 

any prenatal nicotine exposure, even through modes of transmission not related 

to smoking, can be detrimental to fetal development. 

As with most toxins, the effects of prenatal smoking exposure are dosedependent 

and thus strongest among offspring of heavy smoking mothers (10 

cigarettes/day). Further, the effects of prenatal smoking are exacerbated when 

accompanied by low socioeconomic status, poor parenting, family dysfunction, 

paternal absence, and parental history of antisocial behavior. However, the 

relationship still exists even when these variables are controlled for (Huijbregts 

et al., 2008). Evidence suggests that gender might moderate the relationship 

between maternal prenatal smoking and externalizing behaviors in that the 

relationship is stronger among male offspring in predicting CD and stronger 

among female offspring when predicting substance abuse (Brennan et al., 2002).


E. Maternal psychological stress 

Prenatal stress is so common an occurrence that it seems unlikely that it could 

have any significant effects or unfavorable life-long outcomes on child development. 

However, it is, in fact, associated with low birth weight, preterm birth, 

preeclampsia, spontaneous abortion, growth-retardation (specifically reduced 

head circumference), developmental delays, heightened emotionality, externalizing 

behaviors, irritability, psychopathology, and deficits in attention, cognition, 

and neurodevelopment (Clarke et al., 1994, 1996; Gutteling et al., 2005; 

Mulder et al., 2002). Effects involving birth outcomes are relevant to the 

development of aggression in the ways previously described. However, prenatal 

stress, more broadly speaking, also affects fetal neurodevelopment in a different 

way. Prenatal stress may stem from a variety of sources including, but not limited 

to inadequate social support, low socioeconomic status, unwanted pregnancy, 

and sexual, physical, or verbal abuse. These stressors may take the form of one 

traumatic event, several recurrent ones, or more chronically on a daily basis 

(Mulder et al., 2002). When the stressor is experienced, the HPA axis and the 

sympathetic nervous system are activated, as the body’s response to a particular 

threat the individual perceives in her environment. This physiological response 

has evolutionary value in that it places us in “fight or flight” mode, increasing our 

awareness of problems that may exist and preparing us to find ways of solving 

them. This process becomes maladaptive, however, when our perception of a 

threat or stressor is inconsistent with its actual magnitude and relevance to our 

lives, and alternatively, when the physiological response following a stressor is 

prolonged (Clarke et al., 1994, 1996; Gutteling et al., 2005; Mulder et al., 2002). 

The connection between prenatal stress and HPA axis activity has been 

demonstrated in rodent, animal, and human studies, and in all of these, both 

prenatal stress and heightened HPA axis response have been found to be 

predictive of the development of aggression in offspring (Clarke et al., 1994, 

1996; Gutteling et al., 2005; Mulder et al., 2002). A number of rodent studies 

have introduced stress to a pregnant mother prenatally using electrical shock, 

immobilization, or randomly administered bursts of noise. These studies have 

demonstrated a dysregulation of the HPA axis in both mother and pup that 

eventually leads to heightened emotionality, hostility, and aggression in the 

offspring (Clarke and Schneider, 1993; Mulder et al., 2002; Sobrian et al., 

1997; Takahashi et al., 1990; Ward and Weisz, 2011). Similarly, studies of the 

offspring of rhesus monkey mothers exposed to stress from mid- to late-gestation 

demonstrated low birth weight, impaired neuromotor development, attention 

deficits, and disturbed behavior (Clarke et al., 1994, 1996; Schneider, 1992a,b). 

These effects were long-term and persisted even into the adolescent period of 

development (Clarke et al., 1996). In humans, similar effects of maternal prenatal 

stress have been reported (Gutteling et al., 2005; Mulder et al., 2002).


HPA axis regulation involves several hormones, including corticoreleasing 

hormone (CRH), cortisol, (nor)adrenaline, and ACTH, which are 

released into the bloodstream when a stressor is experienced. Small increases 

in these hormones within the pregnant mother may lead to disproportionately 

large increases in fetal hormonal levels. Excessive levels of these hormones may 

potentially inhibit the growth and development of the nervous system, cause 

damage to the brain, and produce programming effects on the fetal neuroendocrine 

system that lead to the developmental deficits mentioned above. This may 

be especially true when HPA axis activity is characterized by an exceptionally 

strong, sustained response to the stressor. Animal models have supported this 

explanation by demonstrating experimentally that levels of these hormones are 

higher in neonates prenatally exposed to stress in comparison to controls (Clarke 

et al., 1994, 1996; Gutteling et al., 2005; Mulder et al., 2002). 

It is important to note that there have been gender differences in the 

findings within this area, namely that hostility and aggressive behaviors appeared 

to be more prevalent in male offspring than in females. These findings, which are 

typically found in rodent studies, suggest that males may be more vulnerable to 

the effects of prenatal stress than their female counterparts (Clarke et al., 1996). 

However, in general, it seems that prenatal stress may be an important predisposing 

factor for a number of behavioral deficits among both male and female 

offspring, even if to different degrees. 

Because stress can be so pervasive in the life of a pregnant mother, it 

often manifests itself in a variety of ways. For example, stress might lead a mother 

to engage in smoking or alcohol and substance abuse, which, in turn, can 

produce fetal neurobehavioral deficits of the kind that have been described in 

previous sections. To prevent these types of detriments from occurring, it may be 

necessary to assess women’s stress levels in early pregnancy, identify those who 

are at risk, and provide stress reduction programs throughout their pregnancies. 

Educating women about the risks involved with prenatal stress, as well as training 

them in relaxation methods, may be helpful in alleviating these effects. Ensuring 

that women have the appropriate buffers needed to prevent stress is also essential. 

Adequate social support and financial resources are just a few factors that 

may be necessary to ensure a mother’s psychological well-being. 

F. Environmental context 

It is important to note that the prenatal factors discussed above may not 

necessarily operate in a unidirectional manner. It may often be the case that 

these factors result in child aggression in the form of coercion or manipulation of 

the parent in order to obtain something that is wanted. This coercion is likely to 

elicit a negative response from the parent in the form of either negative reinforcement 

(giving in to the child) or positive reinforcement (giving increased


attention to the child by chastising or yelling). This reinforcement indirectly 

encourages and exacerbates the child’s behavior, producing an ongoing cycle of 

reinforced aggressive behaviors throughout the child’s lifetime. Further, this 

cycle may be maintained by preexisting neuropsychological deficits and unintentionally 

harmful reinforcements from other figures in the child’s life, such as 

teachers, grandparents, and peers. 

Throughout this section, it has been continually noted that neither 

social nor biological elements operate alone in contributing to the development 

of aggression in offspring. One or the other may predispose a child to developing 

aggressive behaviors, but it is the “double hazard” of perinatal risk and social 

disadvantage that places a child at maximal risk for later aggression and externalizing 

behaviors (Brennan and Mednick, 1997). Understanding the interaction 

of biological and social risk factors in generating aggression is critical for 

preventing both personal costs (few positive social relationships, poor job performance, 

etc.), as well as social costs (crime rate, prison costs, etc.). Thus, 

researchers and policy makers should make it a goal to identify populations 

potentially affected by perinatal risk factors in order to more accurately predict 

who might benefit from interventions aimed at preventing later aggression, 

violence, and criminal offending. 

IV. GENETIC CONTRIBUTIONS 

As described in detail elsewhere in this volume, aggressive and violent behavior 

can in part be accounted for by genetic factors. Because prenatal stress and 

teratogenic exposures may be linked to genetic risk, it is important to consider 

potential genetic contributions to the association between perinatal factors and 

aggression. 

A. Genetic factors as explanatory 

One prenatal risk factor, that has received recent attention in terms of the 

potentially confound role of genetic factors, is maternal smoking during pregnancy. 

For example, twin studies have been utilized to assess whether the 

relationship between maternal prenatal smoking and offspring externalizing 

behavior remains significant when controlling for genetic influences. In one 

such study, the association between maternal smoking and offspring ADHD 

was found to persist after controlling for genetic influences (Thapar et al., 

2003). In a separate twin study, researchers found that genetic effects explained 

about half of the association between maternal prenatal smoking and child


conduct problems; in this study, controls for both genetic influences and parent 

psychopathology accounted for the initial association in its entirety (Maughan 

et al., 2004). 

Recent advances in infertility treatment (i.e., in vitro fertilization using 

donor eggs) have also allowed for the use of a prenatal cross fostering design to 

assess the moderating impact of genetic influences on the maternal prenatal 

smoking/child externalizing disorder association (Rice et al., 2009). In this novel 

study, maternal smoking during pregnancy was only associated with child antisocial 

outcomes in cases where the mother was implanted with her own egg, as 

opposed to an unrelated donor’s egg. These results suggest that genetic factors are 

a necessary component in the noted relationship between maternal smoking and 

child antisocial outcomes. 

Another novel design strategy has recently been used to evaluate outcomes 

for siblings discordant for maternal prenatal smoking (D’Onofrio et al., 

2010; Lindblad and Hjern, 2010). Results from studies using this design suggest 

that familial background factors, rather than environmental exposure effects, 

explain associations between maternal prenatal smoking and externalizing problems. 

However, as acknowledged by their authors, these sibling discordant 

design studies did not test for gene by environment interactions, leaving open 

the possibility that prenatal exposure to maternal smoking may result in externalizing 

behavior outcomes for offspring at particular genetic risk. 

B. Gene by environment (G E) interactions 

Gene by environment interactions have recently been examined in terms of 

their relevance to perinatal risks and child behavioral outcomes. These studies 

have primarily focused on polymorphisms linked to the neurotransmitter systems 

of dopamine, norepinephrine, and 5-HT, which have been described previously 

in terms of their relevance to both perinatal factors and aggressive outcomes. 

1. Monoamine oxidase genotype 

Monoamine oxidase (MAO) is a critical enzyme involved in the degradation of 

neurotransmitters, including norepinephrine, dopamine, and 5-HT. MAO exists 

in two forms, MAOa and MAOb. The gene that codes MAOa has functional 

variations that influence the level of MAOa (Sabol et al., 1998), which in turn 

affects central levels of dopamine and 5-HT and thus, directly regulates behavior. 

Therefore, this gene has been the focus of molecular genetics studies of 

aggressive behavior in both humans (Manuck et al., 2000) and rodents (Cases 

et al., 1995) and is the most well-established susceptibility variant for aggression 

in several species. MAOa genotype appears to influence the development of


violent behaviors by altering vulnerability to the effects of early adverse environments 

(Caspi et al., 2002; Kim-Cohen et al., 2006). Specifically, there is robust 

evidence that the interaction between MAOa and childhood maltreatment 

predicts child CD and adult antisocial behavior such that males with low 

expression of MAOa (L allele), but not males with high expression of MAOa 

(H allele) are at increased risk (Kim-Cohen et al., 2006; Nilsson et al., 2007). 

Recent evidence also links MAOa-L and low brain MAOa with trait aggression 

and neural hypersensitivity to social cues (Alia-Klein et al., 2008; Eisenberger 

et al., 2007). Interestingly, MAOa is an X-linked gene (with males carrying only 

one allele and females carrying two), which suggests the possibility of sex 

differences in genetic and epigenetic regulation and may explain the increased 

average aggressiveness in males in comparison to females. 

One recent study has noted an interaction between the MAOa uVNTR 

(untranslated region variable number of tandem repeats) genotype, gender, and 

maternal prenatal smoking in the prediction of CD symptoms (Wakschlag et al., 

2010). Specifically, boys with the low activity MAOa genotype whose mothers 

smoked during pregnancy were at an increased risk of CD symptoms, whereas 

girls with the high activity MAOa genotype whose mothers smoked during 

pregnancy were at increased risk for hostile attribution bias (a characteristic 

common to aggressive children) as well as CD symptoms. 

2. Genes related to dopaminergic function 

Kahn et al. (2003) noted an interaction between a DAT1 genotype and maternal 

prenatal smoking in the prediction of oppositional and hyperactive symptoms in 

young children. This finding was replicated in an adolescent sample; however, 

the GE effect was specific to hyperactive-impulsive symptoms in males 

(Becker et al., 2008). Other studies have failed to replicate this effect for 

DAT1 and other dopamine-related genotypes (e.g., Brookes et al., 2006; 

Langley et al., 2008); however, relatively few studies have been completed in 

this area. 

3. Catechol O-methyltransferase 

Catechol O-methyltransferase (COMT) is a key modulator of extracellular dopamine 

levels in the PFC. A common G/A polymorphism produces a valine-tomethionine 

amino acid substitution at codons 108 and 158 (Val108/158Met; 

rs4680), which results in a three- to fourfold variation in COMT activity, 

whereby the Val and Met alleles confer high and low activity, respectively 

(Lachman et al., 1996). This well-characterized, functional polymorphism has 

been associated with atypical neural processing and connectivity in healthy


individuals (Dennis et al., 2010), deficits in executive functioning abilities 

(Tunbridge et al., 2006), and with aggression and serious antisocial behavior in 

individuals with ADHD (Caspi et al., 2008). 

Prenatal exposure to nicotine also leads to persistent abnormalities in 

neurotransmitter functioning in the cerebrocortical areas of the rat brain 

(Slotkin et al., 2007). Further, both maternal prenatal smoking and COMT 

associations with CD appear to be specific to aggressive behavior, rather than 

covert antisocial behavior (Monuteaux et al., 2006, 2009). Taken together, these 

findings suggest that the combination of the Val/Val genotype and prenatal 

exposure to maternal smoking may lead to neural processing deficits that increase 

vulnerability for aggression. 

One study examining the interaction of prenatal risk and COMT 

variation in the prediction of antisocial outcomes found that birth weight 

interacted with Val108/158Met to predict antisocial behavior in an ADHD 

sample (Thapar et al., 2005); however, this finding has had at least one failure 

to replicate (Sengupta et al., 2006). Another recent study (Brennan et al., 2011) 

found that individuals with the COMT Val/Val genotype whose mothers also 

smoked during pregnancy were at an increased risk for aggressive behavior outcomes 

in adolescence and young adulthood. These GE interaction findings are 

preliminary but do suggest a potentially important role for genetics in noted 

relationships between perinatal risk factors and aggression. 

C. The role of epigenetics 

The analysis of a GE interaction is still focused on the “fixed” nature of the 

genome—the DNA sequence itself. The DNA sequence is the same in every cell 

of the body and does not change across the lifespan. But there are other 

characteristics of genetic makeup that are not as fixed, and that have been 

found to change in response to environmental influences over time. These are 

known as epigenetic phenomena. Several epigenetic processes have been discovered, 

but the most commonly studied today is the phenomenon of methylation, a 

measurable chemical modification to DNA that can directly alter the expression 

of genes. 

Methylation patterns change not only in response to toxins and stress 

encountered in the environment but also in response to nutritional supplements 

and parenting sensitivity. In a series of seminal studies in this area, Meaney and 

colleagues discovered that the quality of the parenting (licking and grooming) 

that a mother rat provided to her pups during early postnatal development 

changed the methylation patterns in the hippocampus of her offspring 

(Kappeler and Meaney, 2010). Specifically, higher levels of licking and grooming 

made the genes (and the offspring) less responsive to stress in the environment. 

In contrast, low levels of licking and grooming resulted in offspring whose


genetic profile enhanced the release of cortisol in response to stress. Importantly, 

either strategy might be considered “ideal” parenting, depending upon the 

environment in which the offspring will have to survive. 

Recent research suggests that prenatal factors may also influence DNA 

methylation patterns in offspring (Radtke et al., 2011). Specifically, maternal 

reports of abuse during pregnancy were found to be correlated with methylation 

of the glucocorticoid receptor (GR) gene in offspring ages 10–19. In contrast, 

maternal experiences of abuse prior to or after pregnancy were not associated 

with offspring DNA methylation patterns. Importantly, methylation of the GR 

gene directly impacts the functioning of the HPA axis, which (as noted previously) 

may, in turn, impact levels of aggression and antisocial behavior. 

In summary, preliminary evidence suggests that high versus low risk 

genotypes may moderate the effects of perinatal exposures by influencing an 

individual’s susceptibility or resistance to these environmental experiences. In 

addition, perinatal risk factors are associated with epigenetic changes that are 

evident in and may influence later development. Complex behaviors, like aggression, 

are likely based on interactions of numerous genes and numerous 

environmental factors. Future molecular genetics and epigenetic programming 

studies should attempt to unravel the interplay between genes and environment. 

Such knowledge will provide a clearer understanding of the role of early risk 

factors in the development of aggression and how they can be used as intervention 

targets to alter developmental trajectories that lead to a lifetime of violence. 

V. CONCLUSIONS 

It is highly evident based on experimental and clinical studies that deleterious 

perinatal exposures can have a profound and enduring impact on the neuroregulatory 

systems that mediate violence and aggression. Early adverse perinatal 

experiences, in combination with predisposing genetic factors, combine with 

unstable family environments to substantially increase the vulnerability for a 

trajectory of delinquent and aggressive behavior throughout the lifespan; however, 

these outcomes are both complex and multidimensional. Future studies 

should focus on genetic risk factors, as well as novel interventions that may 

mitigate or prevent the deleterious effects of an adverse perinatal environment 

on the development of aggression. Effective interventions should target prenatal 

maternal mental and physical health-related behaviors, address parenting behaviors 

during critical stages of child development (i.e., infancy, early childhood, 

and adolescence), as well as focus on child cognitive and social enrichment 

during pre- and elementary-school years. As we are just beginning to understand 

the complexity of the intergenerational transmission of these problems during


pregnancy and early childhood, it is important as a field to focus on the origin, 

early development, and prevention of aggression and violence to prevent vulnerable 

families and at-risk children from a lifetime of adversity. 

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10 

Neurocriminology 

Benjamin R. Nordstrom,* Yu Gao, † Andrea L. Glenn, ‡ 

Melissa Peskin, } Anna S. Rudo-Hutt, } Robert A. Schug, 

Yaling Yang, k and Adrian Raine* ,},# 

*Department of Psychiatry, University of Pennsylvania, Philadelphia, USA 

† Department of Psychology, Brooklyn College, New York, USA 

‡ Department of Child and Adolescent Psychiatry, Institute of Mental Health, 

Singapore, Singapore 

} Department of Psychology, University of Pennsylvania, Philadelphia, USA 

Department of Criminal Justice, California State University, Long Branch, 

USA 

k Laboratory of Neuro Imaging, University of California, Los Angeles, USA 

# Department of Criminology, University of Pennsylvania, Philadelphia, USA 


II. Psychodynamic Theories 

III. Neuroimaging 

A. Structural imaging studies 

B. Functional imaging studies 

IV. Neuropsychological Testing 

V. Psychophysiological Evidence 

A. Electrocortical measures 

VI. Genetics 

A. Twin studies 

B. Adoption studies 

C. Molecular genetics 

D. ACE model 

E. Gene–environment interaction 

VII. Nongenetic Risk Factors 

A. Prenatal 



DOI: 10.1016/B978-0-12-380858-5.00006-X

256 Nordstrom et al. 

B. Perinatal risk factors 

C. Postnatal 

VIII. The Limitations and Potential of Neurocriminology 

IX. Modifiable Risk Factor Interventions 

X. Conclusion 

References 

ABSTRACT 

In the past several decades there has been an explosion of research into the 

biological correlates to antisocial behavior. This chapter reviews the state of 

current research on the topic, including a review of the genetics, neuroimaging, 

neuropsychological, and electrophysiological studies in delinquent and antisocial 

populations. Special attention is paid to the biopsychosocial model and 

gene–environment interactions in producing antisocial behavior. ß 2011, Elsevier Inc. 


In 1977, George Engel wrote an essay in Science to advocate for a new model in 

medicine that would serve as a corrective to the biomedical reductionism that he 

noted in the field and in psychiatry in particular (Engel, 1977). The model he 

suggested was called the biopsychosocial model and, in understanding the disease 

in question, took into account the biological aspect of the individual, their 

psychological state, and the social context in which they exist. This model has 

since become the dominant paradigm in psychiatric treatment. 

In recent years, a tremendous amount of research has been done to 

elucidate the biological correlates and causes of antisocial behavior. This work 

has been conducted in an environment that has been, at times, hostile to this 

kind of research, as the dominant paradigm in criminology research has focused 

on social theories of crime. What we hope to accomplish in this chapter is to 

present the evidence for a biopsychosocial model of crime. 

We will present the data that argues that there is an inherited propensity 

for criminal behavior. The behavioral phenotype of those who criminally 

offend is demonstrably and obviously different from those who do not; we will 

show that their biological phenotypes are also different. We will marshal the data 

that suggest that the various brain areas that perform cognitive processes relevant 

to criminal offending are structurally and functionally different in antisocial 

people compared to others. We will discuss how these brain differences are also

10. Neurocriminology 257 

evident in techniques that elucidate the mind–body connection. We will also 

discuss how various social, or environmental, events can have multiplicative 

interactions with the biological risk factors to produce criminal offending. 

That there is not one standard diagnosis to identify the behavioral 

phenotype of interest to criminologists is a limitation of any review of this 

literature. Some research teams studying children use the diagnosis of oppositional 

defiant disorder or conduct disorder. Others use a broader category of 

disruptive behavior, attention deficit hyperactivity disorder. Researchers interested 

in adults may use the diagnosis of antisocial personality disorder to identify 

participants, while others might use the more stringent diagnosis of psychopathy. 

Other teams use self-reports of violence or aggression, a history of arrests, or 

various scores on personality inventories to identify the population of interest. 

Our stance on this is that although these differences make it difficult to directly 

compare the results of studies using different identifying criteria, all add the 

potential to better understand the biological correlates of problematic behaviors. 

II. PSYCHODYNAMIC THEORIES 

For the first part of the twentieth century, psychoanalytic models of crime and/or 

criminality (Holmes and Holmes, 1998; Wittels, 1937), cases of murder 

(Abrahamsen, 1973; Arieti and Schreiber, 1981; Bromberg, 1951; Cassity, 

1941; Evseef and Wisniewski, 1972; Karpman, 1951a,b; Lehrman, 1939; 

Morrison, 1979; Revitch and Schlesinger, 1981, 1989; Wertham, 1949, 1950; 

Wittels, 1937), and even homicide wound patterns (DeRiver, 1951) appeared in 

the psychiatric literature. A common feature of psychoanalytic criminological 

theory centers on unconscious processes (i.e., drives, instincts, and motivations, 

and the defense mechanisms used to control them which operate outside of a 

person’s conscious awareness) which are maladaptive and lead to antisocial and 

criminal behavior (Alexander and Staub, 1931). 

A number of psychodynamic theorists have posited that early problems 

of attachment to parents (especially mothers) can predispose individuals to 

unstable personality structure and later criminal offending (Bowlby, 1944, 

1969, 1973, 1980). Some theorists have posited that early experiences with 

rejecting mothers can lead children to mentally internalize fragments of this 

“bad mother,” which can then be externalized onto later female victims (Liebert, 

1972). More recent authors have posited that such malformed attachments 

might be at work in cases of serial homicide (Whitman and Akutagawa, 2004). 

Although some of these notions of psychodynamic theories may appear 

quaint compared to the astonishing technological achievements used in the 

studies described later, it is worth noting that the psychodynamic theorists may 

be using a different language to describe phenomena other researchers frame in


more exacting biological terms. For example, we will later turn to discussions of 

how biology and environment can interact in ways that increase the likelihood 

of criminal offending. We will see that some of this data involves birth complications, 

and in what might be a partial affirmation of attachment theory, 

maternal rejection. 

III. NEUROIMAGING 

Using neuroanatomy as a tool to study criminal propensity is an idea that dates 

back to the early eighteenth century when the German physician Franz Joseph 

Gall developed phrenology. Phrenology purported to analyze the shape of cranial 

bones to make scientific inferences as to both the size and function of underlying 

brain areas. Later technological advances replaced the pseudoscience of phrenology, 

allowing for the scientific study of how brain structure and function 

relate to antisocial behavior. A comprehensive review of the neuroanatomic 

literature as it pertains to antisocial behavior is available (Yang et al., 2008). 

The two main technological advances that allowed images of the brain 

itself to be generated are computerized axial tomography (CAT) scans and 

magnetic resonance imaging (MRI) scans. CAT scans are produced using a series 

of X-rays taken along the axis of the body. The X-rays pass unevenly through 

tissues of different densities, allowing for distinctions between fluid, bone, and 

brain tissue to be made. A computer then assembles these slices into a sequence 

of cross-sectional images. MRI scans are created by using powerful magnetic 

fields to orient all the hydrogen atoms (primarily found in water molecules) in 

the brain in the same direction. A radiofrequency electromagnetic field is 

introduced which then produces a signal that is detected by the MRI scanner’s 

receiver. These signals are then assembled into high-resolution images that can 

distinguish the gray matter from the white matter of the brain. MRI scans don’t 

use radiation and produce more detailed pictures than do CAT scans, but they 

also take much longer to obtain and are much more expensive. 

A. Structural imaging studies 

Structural neuroimaging studies the size of brain regions of interest (ROI). One 

early study found that when CAT scans of the brains of sexual sadists were 

studied, about 50% of them had abnormal brain structures, especially in the 

temporal lobes (Langevin et al., 1988). Other researchers found that nearly 50% 

of 19 murder suspects studied had atrophic brains on CAT scan (Blake et al., 

1995). Later studies using MRI scans found brain atrophy as well, especially in 

the frontotemporal region (Aigner et al., 2000; Sakuta and Fukushima, 1998).


Another qualitative structural imaging study found that 6 of 10 of the violent 

psychiatric inpatients they studied had atrophic temporal regions (Chesterman 

et al., 1994). 

A number of studies in structural imaging have used larger samples and 

reported their findings in quantitative terms. Raine and colleagues viewed 21 

individuals with antisocial personality disorder and compared them to a matched 

group of substance users and normal controls (Raine et al., 2000, 2010). This 

work reported an 11% reduction in the gray matter of the prefrontal cortices of 

the antisocial group. A second study by this group found reduced prefrontal 

cortical gray matter volumes in unsuccessful psychopaths (i.e., psychopaths who 

had been criminally convicted at least once), compared to successful psychopaths 

(i.e., psychopaths who had never been convicted of a crime), and normal 

controls (Yang et al., 2005). In addition, Yang et al. revealed reduced cortical 

gray matter thickness in the frontal and temporal regions in psychopaths when 

compared to normal controls (Yang et al., 2009). Other groups have found that, 

compared to normal controls, subjects with antisocial personality disorder have 

smaller temporal lobes (Dolan et al., 2002; Laakso et al., 2002), as well as 

reductions in their dorsolateral, medial frontal, and orbitofrontal cortices 

(Laakso et al., 2002). 

One team of researchers demonstrated smaller gray matter volumes in 

the orbitofrontal and temporal lobes of children with conduct disorder compared 

to normal controls (Huebner et al., 2008). Reductions in gray matter concentration 

have also been observed in the frontal and temporal lobes of criminal 

psychopaths compared to normal controls (Muller et al., 2008). Along 

these same lines, another research group found insignificant prefrontal lobe 

volume reductions, but significant temporal lobe volume reductions, in conduct 

disordered children (Kruesi et al., 2004). 

Buried deep in the temporal lobe is the amygdala, which is associated 

with fear conditioning, and the hippocampus, a structure associated with 

learning and memory. Laakso and colleagues found, in a group of violent 

offenders with alcoholism and antisocial personality disorder, that smaller posterior 

hippocampus measures matched higher psychopathy rating scores (Laakso 

et al., 2000, 2001). Other researchers report that adolescents with conduct 

disorder demonstrate reduced gray matter volumes in the insula and amygdala 

compared to normal controls (Sterzer et al., 2007). 

A relatively new technique called diffusion tensor imaging (DTI) allows 

images to be taken of the structural integrity of the white matter tracts connecting 

various parts of the brain. One DTI study showed evidence of abnormal white 

matter tract structure in the frontotemporal regions of adolescents with disruptive 

behavior compared to normal controls (Li et al., 2005). A second study 

showed similar evidence of abnormal white matter tracts connecting the amygdalas 

and orbitofrontal cortices of criminal psychopaths when compared to


normal controls (Craig et al., 2008). Other studies looking at abnormalities in 

connectivity have focused on white matter structures. Raine et al. (2003a,b) 

found that compared to a normal comparison group, psychopathic, antisocial 

subjects had a longer, thinner corpus callosum with overall increased volume. 

They also found a correlation between psychopathy scores and larger callosal 

volumes (Raine et al., 2003a). 

B. Functional imaging studies 

Not only does current technology allow us to study the structure and connectivity 

of brain regions, it also allows us to image the functioning of brain areas as 

well. One form of functional neuroimaging is photon emission tomography 

(PET). This technique relies on injecting subjects with radioactively labeled 

substance such as glucose. Images of their brains can then be obtained. Areas of 

higher radioactive signal have more glucose metabolism and are thought to be 

more active (Yang et al., 2008). A second form of functional neuroimaging is 

single photon emission tomography (SPECT). This form of imaging also 

involves the injection of a radioactive tracer. The camera detects the amount 

of radiation coming from different parts of the brain. These differences are due to 

differences in regional cerebral blood flow (rCBF) and are thought to reflect 

different levels of activity in various parts of the brain (Yang et al., 2008) 

Functional magnetic resonance imaging (fMRI) studies measure changes in 

blood oxygen in ROI in the brain before and after cognitive tasks are undertaken. 

These blood oxygen level dependent (BOLD) signals are used as a proxy for how 

active a region of the brain is. By comparing subjects of interest with matched 

controls, the patterns of activation or inactivation in the brain can be studied to 

learn how the functioning of various brain regions relates to the condition at 

hand (Yang et al., 2008). 

One early PET scan study showed that, compared to controls, antisocial 

subjects demonstrated reduced glucose metabolism in the prefrontal and temporal 

areas of their brains (Volkow et al., 1995). A SPECT study of aggressive 

psychiatric patients also found reduced rCBF in the prefrontal cortex, as well as 

increased blood flow to the left temporal and the anterior medial frontal cortices 

(Amen et al., 1996). 

Other PET studies have investigated how glucose metabolism responds 

to difficult cognitive tests, such as a continuous performance task (CPT). One 

group found that the number of impulsive–aggressive acts perpetrated by subjects 

with personality disorders, including antisocial personality disorder, was negatively 

correlated to glucose metabolism in the orbitofrontal, anterior medial 

frontal, and left anterior frontal cortices (Goyer et al., 1994). Raine et al. 

(1994a,b) found that after a CPT, a sample of murderers demonstrated reduced 

glucose metabolism in the anterior medial prefrontal, orbitofrontal, and superior


frontal cortices compared to a normal comparison group (Raine et al., 1994b). 

A follow up study with a larger sample but a similar methodology found the same 

pattern of reduced glucose metabolism in the anterior frontal cortices, and in the 

amygdalas and hippocampi as well (Raine et al., 1997a). 

The amygdala is a structure in the brain that plays a significant role in 

emotion processing. This makes it an important structure in associative learning, 

in which individuals assign an affective valence to the consequences of their 

actions. These associations can be positive, such as learning to feel good after 

helping someone, or negative, such as learning to feel guilty or bad after harming 

someone. It has been theorized that associating harmful actions with the distress 

of others could thus discourage antisocial behavior (Blair, 2006a,b). 

A study using PET technology looked at a sample of normal controls, a 

sample of schizophrenic patients with a history of repeated violent offending and 

a sample of schizophrenic patients with a history of nonrepetitive violent offending 

(Wong et al., 1997). This team found that, compared to the normal controls, 

the patient samples had reduced glucose metabolism in the anterior inferior 

temporal lobes. This reduction was bilateral in the nonrepetitively violent 

group, but isolated to the left side in the repetitively violent group. Later, a 

research group using SPECT found that, compared to normal controls, antisocial 

populations have reduced rCBF to the frontal cortex and temporal cortex, and 

that psychopathy scores are negatively correlated with the degree of rCBF 

reduction to these areas (Soderstrom et al., 2000, 2002). 

One fMRI study looked at patterns of brain activation in 13 adolescent 

aggressive conduct disordered males and 14 matched controls as they looked at 

neutral pictures and pictures with a strong negative affective valence. It was 

found that when the conduct disordered youth viewed the distressing pictures 

they had significantly reduced activity to their left amygdalas compared to the 

control subjects (Sterzer et al., 2005). Similar findings have been described in 

adult populations (Kiehl et al., 2004; Muller et al., 2003). 

Another group used a similar methodology to study the reaction of a 

sample of 36 children and adolescents as they viewed photographs of neutral, 

angry, or fearful faces. 12 of the participants had callous–unemotional traits and 

oppositional defiant disorder or conduct disorder, 12 had attention deficit hyperactivity 

disorder and 12 were comparison subjects. When compared to the other 

two groups, the group with callous–unemotional traits demonstrated significantly 

reduced amygdala activation on viewing the fearful (but not the angry or 

neutral) faces (Marsh et al., 2008). In addition, in a functional connectivity 

analysis, the callous–unemotional children showed reduced connectivity between 

the ventromedial prefrontal cortex and the amygdala. Further, the degree 

of reduction in this connectivity was negatively correlated with the score on the 

scale that measured the degree of callous–unemotional traits. This is particularly 

interesting as the ventromedial prefrontal cortex has been implicated in


processing punishment and reward (Rolls, 2000), affective theories of the mind 

(Shamay-Tsoory et al., 2005), response inhibition (Aron et al., 2004; Vollm 

et al., 2006), and emotional regulation (Ochsner et al., 2005). 

IV. NEUROPSYCHOLOGICAL TESTING 

Neuropsychological tests provide another method for testing the capabilities and 

functioning of various brain areas. One of the most consistent findings in the 

neuropsychological aspects of criminality is that antisocial populations have 

lower verbal IQs compared to nonantisocial groups (Brennan et al., 2003; Déry 

et al., 1999; Raine, 1993; Teichner and Golden, 2000). Researchers have found 

that verbal deficits on testing at age 13 predict delinquency at age 18 (Moffitt 

et al., 1994). A number of authors have found evidence that such neuropsychological 

deficits show interactive effects when they are present in children with 

social risk factors (Aguilar et al., 2000; Brennan et al., 2003; Raine, 2002a,b). 

Executive functioning is another neuropsychological function of interest 

in criminology (Moffitt, 1990, 1993). Executive functioning refers to the 

group of cognitive processes that produce goal-directed, flexible, and strategically 

effective behavior (Lezak et al., 2004; Luria, 1996; Spreen and Strauss, 1998). 

Executive dysfunction involves impairments in impulse control, self-regulation, 

abstract reasoning, concept formation, sustained attention, planning, organization, 

problem solving, and cognitive flexibility (Raine, 2002a,b). A meta-analysis 

of 39 studies incorporating data from 4589 individuals studied the relationship 

between executive dysfunction and antisocial behavior(Morgan and Lilienfeld, 

2000). These authors found significant effect sizes (d¼0.86 for juvenile delinquency 

and d¼0.46 for conduct disorder) for the association between antisocial 

behavior and executive dysfunction. 

Another neuropsychological test that has been studied in antisocial 

populations tests selective attention, or the ability to attend to one or more 

stimuli while ignoring others. The dichotic listening test is used to probe selective 

attention by having subjects wear headphones and then sending different auditory 

stimuli to each ear, while instructing them to respond to only 1 ton and ignore 

others. Both adult (Hare and Jutai, 1988) and juvenile (Raine et al., 1990a) 

populations with psychopathic traits have been shown to have abnormalities on 

this test when verbal stimuli are used. These researchers have hypothesized that 

this reduced lateralization of linguistic processes might indicate that people with 

psychopathic traits have a reduced use of language to regulate their behavior. 

Other neuropsychological tests have focused on how antisocial populations 

respond to affectively charged stimuli. Loney et al. (2003) found that 

juveniles with callous–unemotional traits showed slower reaction times after 

being presented with emotionally negative words, while those with impulsive 

traits showed faster reaction times to such stimuli. Adult psychopaths have been


found to have deficits in passive-avoidance learning tasks (Newman and Kosson, 

1986) and adolescent psychopaths have been shown to demonstrate hyperresponsivity 

to rewards (Scerbo et al., 1990). Taken together, these data suggest 

that psychopathic individuals will be less sensitive to punishment and more 

sensitive to the possibility of rewards as a consequence to their behavior. Also, 

given the executive functioning literature, they may be less able to plan, act in a 

rationally self-interested fashion, control their impulses and respond flexibly to 

the various problems encountered in everyday life. 

V. PSYCHOPHYSIOLOGICAL EVIDENCE 

The autonomic underarousal and hyporesponsivity noted in various electrophysiological 

studies have given rise to fearlessness theory. This theory posits that the 

low level of arousal noted in the somewhat stressful testing situations can be 

taken as evidence of a lack of normal fear (Raine, 1993, 1997). An alternative to 

fearlessness theory is the stimulation-seeking theory, which presumes that the 

observed hypoarousal is experienced by affected individuals as unpleasant, and is 

compensated for using risk-taking/thrill-seeking behaviors. Supporting this hypothesis 

is the observation that 3-year-old children who show high levels of 

sensation seeking and lower levels of fearlessness demonstrate increased levels of 

aggression at age 11 (Raine et al., 1998). 

It is likely that stimulation-seeking and fearlessness explain some part of 

the low resting heart rate shown in antisocial youth, but a causal link between 

the low resting heart rate and criminal behavior is more elusive (Raine, 2002a,b). 

A third theory, the prefrontal deficit theory, argues that the low arousal seen 

arises from abnormalities in the prefrontal cortical–subcortical circuits involved 

with arousal and stress response (Raine, 2002a,b). 

A number of psychophysiological studies have also elucidated biological 

correlates of criminal behavior. These studies have typically focused on heart 

rate, skin conductance and electrocortical measurements. In-depth descriptions 

of the methodologies used in psychophysiological research are available 

(Cacioppo et al., 2007). 

A. Electrocortical measures 

1. Electroencephalogram (EEG) 

The electrical activity in the cerebral cortex can be measured by a noninvasive 

test, the EEG (Hugdahl, 2001). In an EEG, the subject has electrodes placed in 

specific points over the scalp. These electrodes detect the brain’s electrical 

impulses, which are then recorded and analyzed by a computer. The frequency 

and amplitude of the resultant signals are then interpreted.


Increasing frequency is associated with increasing arousal, and lower 

frequency is associated with lower arousal (Hugdahl, 2001). Slower EEG activity 

in children and adolescents is associated with later criminal behavior (Mednick 

et al., 1981; Petersen et al., 1982). Raine and colleagues demonstrated that, 

compared to their peers with higher arousal, 15-year-old boys with lower arousal 

as measured by resting EEG were more likely to become criminals at age 24 

(Raine et al., 1990b). Children with externalizing and antisocial behaviors have 

been noted to demonstrate abnormal patterns of EEG asymmetry in their frontal 

lobes (Ishikawa and Raine, 2002; Santesso et al., 2006). 

It has been noted that dominant EEG frequencies increase with age 

(Dustman et al., 1999). The EEG abnormalities noted with respect to criminal 

behavior have been hypothesized to be due to cortical immaturity (Volavka, 

1987). It has been suggested that abnormal frontal EEG asymmetry might belie 

language and analytic reasoning deficits, thus impairing emotion regulation 

(Santesso et al., 2006). 

2. Event-related potentials (ERPs) 

A stimulus perceived by the brain will cause a change in the brain’s electrical 

activity. An ERP is a measure of the magnitude of that change after the 

presentation of specific stimuli. The change, or deflection, may be positive or 

negative in direction, and occurs within milliseconds of the onset of the stimulus. 

Typically an ERP is measured several times, and the average of all the trials is 

taken (Hugdahl, 2001). The P300 is a waveform that typically occurs approximately 

300 ms after the presentation of a stimulus. Early onset of drug abuse and 

criminal behavior has been shown to be related to smaller P300 amplitudes 

(Iacono and McGue, 2006). Other studies have demonstrated that greater 

negative amplitude at 100 ms and faster latency at 300 ms at age 15 are predict 

criminal behavior at age 24 (Raine et al., 1990b). A meta-analysis of studies of 

ERP in antisocial populations found that, in general, antisocial individuals have 

smaller P300 amplitudes and longer latencies (Gao and Raine, 2009). 

3. Low resting heart rate 

Low resting heart rate is the best-replicated biological correlate of antisocial 

behavior in juvenile samples (Ortiz and Raine, 2004). In a meta-analytic review 

of 29 samples, the average effect size was 0.56. This effect was demonstrated in 

both genders and irrespective of measurement technique (Raine, 1996). This 

relationship is not artifactual, as confounding variables such as height, weight, 

body composition, muscle tone, poor school performance, low IQ, hyperactivity,


low attention, drug and alcohol use, participation in sports and exercise, social 

class, and family size and composition have all been ruled out (Farrington, 1997; 

Raine et al., 1990b, 1997b; Wadsworth, 1976). 

The finding that low resting heart rate predicts later crime has been 

replicated in the United States, Germany, England, Canada, Mauritius, and New 

Zealand (Farrington, 1997; Mezzacappa et al., 1997; Moffitt and Caspi, 2001; 

Raine et al., 1997b; Rogeness et al., 1990; Schmeck and Poustra, 1993). In 

longitudinal studies, low resting heart rate has been shown to accurately identify 

individuals who are at risk for later developing antisocial behavior. This finding 

is specific for antisocial behavior (Rogeness et al., 1990) and has not been shown 

in other psychiatric syndromes. 

In the Cambridge Study in Delinquent Development, a series of six 

regression analyses were used to identify the best independent risk factors of 

violence (Farrington, 1997). Only two risk factors, low resting heart rate and 

poor concentration, were found, independently of all other risk factors, to predict 

violence. This same study found evidence of an interaction between low resting 

heart rate and several environmental risk factors (e.g., coming from a large 

family, having a teenaged mother, being of low socioeconomic status) in producing 

violent behavior. Lastly, it has been shown that having a high resting heart 

rate is negatively correlated with later violent behavior (i.e., a high resting heart 

rate is a protective factor against developing crime development) (Raine et al., 

1995). 

4. Skin conductance 

The ease with which the skin can conduct electrical impulses is a function of 

sympathetic nervous system activity. Increased sweating leads to improved 

electrical conductance along the surface of the skin. In times of stress, sympathetic 

nervous system activity increases, and skin conductance will also increase. 

A classically conditioned fear response (as measured by an increase in skin 

conductance) can be produced by pairing a stressful stimulus, such as a noxious 

sound, with a neutral stimulus, such as a light turning on. Studying skin conductance 

under different paradigms can thus provide insight into the functioning of 

the sympathetic nervous system. 

Low skin conductance has been shown to be associated with conduct 

problems (Lorber, 2004). Boys with conduct disorder have been shown to have 

reduced fluctuations in skin conductance and impairments in conditioned fear 

responses (Fairchild et al., 2008; Herpertz et al., 2005). Longitudinal studies have 

demonstrated that reduced skin conductance arousal at age 15 has been associated 

with criminal offending at age 24 (Raine et al., 1995) and that low skin 

conductance at age 11 predicts institutionalization at age 13 (Kruesi et al., 1992).


Impaired fear conditioning as measured by skin conductance at age 3 has been 

shown to predict aggression at age 8 and criminal behavior at age 23 (Gao et al., 

2010a,b). 

Low sympathetic reactivity has been shown in psychopathy-prone adolescents 

and in children with conduct disorder and callous–unemotional traits 

(Anastassiou-Hadjichara and Warden, 2008; Kimonis et al., 2006; Loney et al., 

2003). At age 3, having an abnormal skin conductance response to unpleasant 

stimuli is a risk factor for displaying psychopathy in adulthood (Glenn et al., 

2007). 

VI. GENETICS 

As described in more detail in a separate chapter in this volume, a growing body 

of evidence has shown that there is a strong genetic contribution to juvenile 

delinquency (Popma and Raine, 2006). Although a number of genes have been 

shown to have an association with antisocial behavior, no one gene seems to 

“explain” criminal behavior (Goldman and Ducci, 2007). Investigating the 

potential genetic basis for complex behaviors is inherently complicated as they 

are likely to involve multiple genes, in contrast to conditions where there is a 

single-gene effect, as in classic Mendelian genetics (Uhl and Grow, 2004). 

Studies report heritability estimates that range widely, although the majority of 

investigators find heritability estimates that fall between 40% and 60% 

(Arsenault et al., 2003; Beaver et al., 2009; Jaffee et al., 2004, 2005; Lyons 

et al., 1995; Moffitt, 2005; Rhee and Waldman, 2002; Slutske et al., 1997). 

A. Twin studies 

One way to investigate a genetic component to a behavior is by comparing the 

frequency with which the disease occurs in different kinds of siblings. Monozygotic 

(also called identical) twins arise from a single fertilized ovum, meaning 

they have exactly the same genetic material. Dizygotic (also called fraternal) 

twins arise from two separate fertilized ova. Like any siblings, they share 50% of 

the same genes. A twin pair demonstrates concordance when both individuals 

demonstrate the condition in question, while twin pairs with only one affected 

individual are said to show discordance. The heritability of a disease can be 

estimated by comparing the rates of concordance and discordance in both 

monozygotic and dizygotic twins (Jorde et al., 1995). 

One study that investigated the genetic contribution to childhood 

antisocial and aggressive behavior investigated 605 families of 9- to 10-yearold 

twins and triplets (Baker et al., 2007). In this economically and ethnically 

diverse sample, such behavior was strongly heritable. Another study analyzed


self-report measures of aggression in 182 monozygotic and 118 dizygotic twins 

(Coccaro et al., 1997a). The investigators found significant heritability for three 

out of the four forms of aggression studied. Although twin studies provide the 

opportunity study individuals with identical genetic make-ups or identical prenatal 

histories, other methodologies have also sought to gain understanding into 

the relative contribution of genes and parenting on later problematic behavior. 

B. Adoption studies 

Adoption studies provide another mechanism for studying the genetic versus the 

environmental contributions to antisocial behavior. In such studies, the characteristics 

of a child’s biological and adoptive parents are considered relative to 

the child’s own behavior. One early such study (Bohman, 1978) found evidence 

for a genetic predisposition to alcohol, but not to criminality, while another 

study from that same year (Cadoret, 1978) found evidence for heritability of 

antisocial behavior. A study of 862 Swedish male adoptees found that genetic 

influences were the most significant contributor to later criminal behavior 

(Cloninger et al., 1982). Another large sample of adoptees in Denmark similarly 

found strong evidence for a genetic propensity for criminal behavior (Gabrielli 

and Mednick, 1984). 

C. Molecular genetics 

Although it was previously noted complex behavioral syndromes don’t follow 

ordinary Mendelian patterns of inheritance, there is a notable exception to this. 

One group of researchers identified a family that demonstrated X-linked inheritance 

of borderline intellectual functioning and “abnormal behavior.” (Brunner 

et al., 1993) The behaviors exhibited by affected males included aggression, rape, 

exhibitionism, and arson. The researchers found that all had inherited a deficiency 

in the gene that coded for monoamine oxidase A (MAO-A). 

D. ACE model 

In behavioral genetic research, the heritability (i.e., the portion of the phenotypic 

variance explained by genetic factors) is represented by the letter “A.” The 

letter “C” is used to represent the family-wide, common, or shared environment. 

This includes influences that siblings would share, such as parenting styles or 

neighborhood characteristics. The letter “E” is used to represent environmental 

conditions uniquely encountered by an individual, such as getting a head injury. 

These are also called nonshared environmental influences.


One such study investigated the genetic basis for psychopathy (Larsson 

et al., 2006). The researchers found that “A” accounted for 63% of the variance, 

“C” accounted for 0%, and “E” accounted for 37% of the variance. 

One meta-analytic study that used the ACE model found that, in 

children, genes (“A”) and shared environment (“C”) were equally important in 

explaining aggressive behavior (Miles and Carey, 1997). The researchers also 

found that heritability was slightly higher for males than for females, and that in 

adulthood the role of heritability increased while the role of shared environment 

fell to inconsequential levels. 

Another meta-analytic study of over 100 behavioral genetic studies 

showed that 40–50% of the variance of antisocial behavior is due to heritability, 

30% is due to the nonshared environmental influences, and 15–20% is due to 

shared environmental influences (Rhee and Waldman, 2002). 

It has been demonstrated that the influence of genes on criminal 

behavior varies over the life course (Goldman and Ducci, 2007). The majority 

of reports find that heritability estimates for antisocial behavior are lower, and 

shared environmental effects on antisocial behavior are higher, in childhood 

than in adolescence (Jacobson et al., 2002; Lyons et al., 1995; Miles and Carey, 

1997). It further seems that some genes affect the propensity for criminal 

involvement in adolescence, while others exert their effects in adulthood 

(Goldman and Ducci, 2007). 

The effects of genetics are also moderated by the type of criminal 

offending being considered. Heritability estimates for aggressive offending are 

higher than those for nonaggressive offending, such as rule breaking and theft 

(Eley et al., 2003). The opposite appears to be true for nonaggressive offending, 

which may be influenced more by shared environmental factors, such as family 

criminality, family poverty, and poor parenting, although research suggests that 

genetic influences also affect several of these risk factors (Moffitt, 2005). 

E. Gene–environment interaction 

Other studies have focused on how a person’s genetic endowment interacts with 

the environment in which the person lives. In the Swedish adoption study 

described above (Cloninger et al., 1982), the researchers found that if a person 

had both a biological parent and an adoptive parent who were criminals, then 

the person’s likelihood of criminal behavior was greater than the sum of the 

individual risks. In other words, there was a multiplicative effect of having a 

biological predisposition to crime and then being raised in a criminogenic 

environment. 

Another large study of gene–environment interaction identified people 

who carried a genotype that conferred a low expression of MAO-A activity 

(Caspi et al., 2002). The researchers looked at the people with high versus low


MAO-A activity and also whether or not the individual had been abused as a 

child. They found evidence of a strong interaction between low MAO-A activity 

and childhood maltreatment in the likelihood of developing conduct disorder. 

VII. NONGENETIC RISK FACTORS 

There are many different types of the kinds of environmental risk factors 

captured by the ACE model. Researchers have identified a number of intriguing 

risk factors, some of which could be shared by siblings, some of which are less 

likely to be, which have been associated with later problematic behavior. These 

risk factors can be broken into those that arise during pregnancy (prenatal), 

those that arise during birth (perinatal) and those that arise in childhood 

(postnatal). 

A. Prenatal 

1. Minor physical anomalies (MPAs) 

MPAs are subtle physical defects such as having a curved fifth finger, a single 

palmar crease, low seated ears, or a furrowed tongue, are thought to arise from 

abnormalities in fetal development. These are thought to serve as biomarkers for 

abnormalities in neural development as well. MPAs may have a genetic basis, but 

they might also be due to anoxia, bleeding, or infection (Guy et al., 1983). Early 

studies showed an increase in the prevalence of MPAs in school-aged boys 

exhibiting behavioral problems (Halverson and Victor, 1976). MPAs have also 

been shown to be correlated to aggressive behaviors in children as young as 3 

years old (Waldrop et al., 1978). It has also been shown that MPAs identified at 

age 14 predict violence at age 17 (Arsenault et al., 2000). 

Mednick and Kandel studied MPAs in a sample of 129 12-year-old boys 

(Mednick and Kandel, 1988). They found MPAs were related to violent offending 

as assessed 9 years later when subjects were 21 years old. Interestingly, when 

subjects were divided into those from unstable (i.e., non-intact) homes versus 

those from stable homes, a biosocial interaction was observed. MPAs only 

predicted violence in those individuals raised in unstable home environments. 

Similarly, a study of 72 male offspring of psychiatrically ill parents found 

that those with both MPAs and family adversity had especially high rates of adult 

violent offending (Brennan et al., 1997). Another study showed that the presence 

of MPAs significantly interacted with environmental risk factors (e.g., 

poverty, marital conflict) to predict conduct problems in adolescence (Pine 

et al., 1997).


2. Tobacco 

There is a significant body of evidence that demonstrates that maternal smoking 

during pregnancy predisposes children to developing antisocial behavior 

(Wakschlag et al., 2002). Maternal prenatal smoking predicts externalizing behaviors 

in childhood and criminal behavior in adolescence (Fergusson et al., 1993, 

1998; Orlebeke et al., 1997; Rantakallio et al., 1992b;Wakschlaget al., 1997). 

Researchers have elucidated a clear dose-dependent relationship between smoking 

and later criminal behavior (Brennan et al., 1999; Maughan et al., 2001, 2004). 

Although the mechanism by which smoking produces these effects is 

unknown, basic science research has shown that the byproducts of smoking may 

affect the brain’s dopaminergic and noradrenergic systems (Muneoka et al., 

1997) and glucose metabolism (Eckstein et al., 1997). Smoking may affect 

various brain structures, for example, the basal ganglia, cerebral, and cerebellar 

cortices—implicated in the deficits observed in violent offenders (Olds, 1997; 

Raine, 2002a,b). 

3. Alcohol 

There is also a great deal of evidence that prenatal exposure to alcohol predisposes 

individuals to antisocial behavior (Fast et al., 1999; Olson et al., 1997; 

Streissguth et al., 1996). Although Fetal Alcohol Syndrome (FAS) does not arise 

in all children exposed to alcohol in utero, evidence shows that children who do 

not display the full FAS syndrome can have some of the functional deficits 

characteristic of the syndrome (Schonfeld et al., 2005). Children who do not 

meet diagnostic criteria for FAS, yet were exposed to high levels of alcohol in 

utero, are at increased risk of antisocial behavior (Roebuck et al., 1999). 

B. Perinatal risk factors 

Obstetrical complications are untoward events that occur at the time of delivery 

and include such things as maternal preeclampsia, premature birth, low birth 

weight, use of forceps in delivery, transfer to a neonatal intensive care unit, 

anoxia, and low Apgar scores. Maternal complications have been shown to have 

deleterious effects on neonatal brain function (Liu, 2004; Liu and Wuerker, 

2005). Newborns who suffer obstetrical complications are more likely to exhibit 

externalizing behaviors at age 11 than those without complications (Liu et al., 

2009). Obstetrical complication was found to mediate the relationship between 

low IQ and externalizing behaviors. 

It has also been demonstrated that obstetrical complications interact 

with other environmental factors to predict later antisocial behavior. Raine et al. 

(1994a,b) investigated a cohort 4269 Danish men. The investigators found that


birth complication significantly interacted with severe maternal rejection (e.g., 

efforts to abort the pregnancy, reporting the pregnancy as unwanted, or attempting 

to give up custody of the baby) to predict violent crime in adolescence (Raine 

et al., 1994a). This study has since been replicated in the United States, Sweden, 

Finland, and Canada, and has repeatedly shown that birth complications interact 

with a number of psychosocial risk factors to produce antisocial behavior 

(Arsenault et al., 2002; Hodgins et al., 2001; Kemppainen et al., 2001; Tibbetts 

and Piquero, 1999). 

C. Postnatal 

Poor nutrition has been investigated as a risk factor for criminal behavior for 

some time. An association between aggressive behavior and vitamin and mineral 

deficiency has been described (Breakey, 1997; Werbach, 1995). The exact 

mechanism by which malnutrition affects later antisocial behavior is not well 

understood, it has been hypothesized that proteins or minerals may either 

regulate neurotransmitters and hormones, or ameliorate neurotoxins (Coccaro 

et al., 1997b; Liu and Raine, 2006). 

Although most studies have focused on nutrition in the postnatal period, 

one study investigated the role of malnutrition in the prenatal period in producing 

antisocial behavior (Neugebauer et al., 1999). This group studied the offspring of 

women who were pregnant during the German food blockade of Dutch cities in 

World War II. The blockade produced near starvation and severe food shortages. 

The researchers found that the male offspring of women who were in the first and 

second trimesters (but not the third trimester) of pregnancy during this time had 

two and a half times the rate of antisocial personality disorder than did the 

offspring of women who were not affected by food shortages. 

Another study of prenatal nutrition studied a sample of 11,875 pregnant 

women. Those women who ate less seafood (i.e., less than 340 g a week), which 

is rich in omega-3 fatty acids, had offspring that demonstrated significantly lower 

scores on a number of neurodevelopmental outcomes, including prosocial behavior, 

than the offspring of mothers who ate more seafood (Hibbeln et al., 

2007). 

Studies have also shown that deficiency in nutrients such as proteins, 

zinc, iron, and docosahexaenoic acid (a component of omega-3 fatty acid) can 

lead to impaired brain functioning and a predisposition to antisocial behavior in 

childhood and adolescence (Arnold et al., 2000; Breakey, 1997; Fishbein, 2001; 

Lister et al., 2005; Liu and Raine, 2006; Rosen et al., 1985). 

Longitudinal studies have shown that malnutrition in infancy is associated 

with aggressive behavior and attentional deficits in childhood (Galler and 

Ramsey, 1989; Galler et al., 1983a,b). Liu et al. conducted a prospective longitudinal 

study to investigate how early malnutrition can predispose to behavior


problems later in life (Liu and Raine, 2006). The researchers found that, compared 

to controls, children with protein, iron, or zinc deficiencies at age 3 had significantly 

more aggressive and hyperactive behavior at age 8, more antisocial behavior 

at age 11, and more excessive motor activity and conduct disorder at age 17. 

Significantly, this team also found a dose-dependent relationship between the 

extent of malnutrition and the extent of later behavior problems. 

1. Traumatic brain injury (TBI) 

Another risk factor that has been studied in relation to antisocial behavior is 

TBI. One group of investigators found that half of the juvenile delinquents in 

their sample had a history of TBI, and a third of the delinquents with TBI were 

thought by their parents to have neuropsychological sequelae from their injuries 

(Hux et al., 1998). Another study, which used more severe criteria in the 

definition of TBI than the previous study, found that 27.7% of the delinquents 

in their sample had a history of TBI (Carswell et al., 2004). A number of large, 

longitudinal studies of have repeatedly shown an increased incidence of delinquent 

behavior among youth with a history of TBI (Asarnow et al., 1991; Bloom 

et al., 2001; Butler et al., 1997; McAllister, 1992; Rantakallio et al., 1992a; Rimel 

et al., 1981; Rivera et al., 1994). 

VIII. THE LIMITATIONS AND POTENTIAL OF NEUROCRIMINOLOGY 

The field of neurocriminology has struggled to free itself from associations to 

earlier efforts to incorporate biology into the field of criminology. The reductionism 

of Lombroso’s biological positivism, the pseudoscience of phrenology, 

and the appalling racism of social Darwinists have all cast long shadows that 

have affected how contemporary efforts have been received by sociologically 

oriented criminologists. 

There is a danger that the kind of neurocriminological data could be 

used in a sensationalistic or superficial manner to implicate or exculpate individual 

offenders. Although the current state of imaging and other forms of biological 

research have not advanced to the point where an individual’s data could be 

confidently compared against a reliable database of normal controls, the possibility 

exists that such databases could be created and validated (Yang et al., 

2008). Until such time, however, it is important to note that studies of the sort 

reviewed in this chapter cannot be taken to imply that any one biological factor 

causes criminal behavior. Rather, the presence of these factors only increases the 

probability that problematic behavior will be present in people with a given 

biological risk factor.


We have now reviewed a number of studies that describe such increased 

probabilities of biological risk factors in criminal behavior. The sociological roots 

have crime have also been widely studied. This chapter has also reviewed a 

number of examples of how biological and environmental forces can interact to 

produce problematic behavior. We can see that criminal behavior can be investigated 

and explained at many different levels of abstraction. 

The psychiatrist and philosopher Kenneth Kendler illustrates this phenomenon 

with a hypothetical case of a pharmacologist running a randomized 

controlled trial of a medication for a psychiatric condition (Kendler, 2005). 

Although it is undoubtedly true that the medication is a molecule, and molecules 

are made up of atoms and atoms are made up of subatomic particles, it does not 

necessarily make sense to consult with a particle physicist in conducting the 

study. Thus, some levels of abstraction may be more or less efficient in explaining 

the phenomenon in question. However, each time a new level is identified, new 

possibilities for intervention arise as well. In uncovering biological leads relevant 

to crime the potential for new strategies for crime prevention are created as well. 

IX. MODIFIABLE RISK FACTOR INTERVENTIONS 

Not all risk factors for criminal behavior (e.g., male gender, having a biological 

parent with a history of criminal behavior) are modifiable. There are a number of 

risk factors (e.g., smoking, nutrition), however, that can be modified. Successful 

interventions have been developed to reduce prenatal alcohol exposure (Chang 

et al., 1999, 2005). Interventions have also been designed to reduce smoking in 

pregnancy, but these have been notably less effective than the interventions for 

alcohol use (Ershoff et al., 2004). Of note, women who persist in smoking 

throughout pregnancy are more likely than those who quit to have a personal 

history of conduct disorder (Kodl and Wakschlag, 2004). 

Other studies have sought to correct nutritional deficits. One randomized, 

double blind, placebo-controlled study was performed in a sample of 486 

public schoolchildren to see if a daily multivitamin and mineral supplement 

could reduce antisocial behavior (Schoenthaler and Bier, 2000). The researchers 

found that, compared to the placebo group, the treatment group had a 47% 

reduction in antisocial behavior after 4 months. Previously, this team had 

investigated the effect of vitamin and mineral supplementation in a group of 

juvenile delinquents confined to a correctional setting. The results of this 

randomized, double blind, placebo-controlled trial showed that, compared to 

the placebo group, the treatment group had significantly less violent and nonviolent 

antisocial behaviors (Schoenthaler et al., 1997). Another randomized, 

double blind, placebo-controlled trial of omega-3 fatty acid supplementation 

was done in a sample of 50 children. Compared to the placebo condition, the


intervention group had a 42.7% reduction in conduct disorder problems (Stevens 

et al., 2003). A study using omega-3 fatty acid supplementation in ADHD failed 

to reveal a benefit (Hirayama et al., 2004). 

Other interventions address more than one risk factor at a time. For 

example, one highly successful intervention for prevention of later criminal and 

antisocial behavior involves home nursing visits for pregnant and new mothers. 

Parenting, health, and nutritional guidance are provided in the sessions (Olds 

et al., 1998). Other authors have also shown that prenatal education on nutrition, 

health, and parenting can lead to reductions in juvenile delinquency at age 

15 (Lally et al., 1988). 

Another multidimensional intervention was tested in a randomized, 

controlled fashion (Raine et al., 2003b). In this study, an intervention consisting 

of physical exercise and nutritional and educational enrichment was tested on a 

sample of 3–5 year olds. The study found that the intervention significantly 

reduced antisocial behavior at age 17 and criminal behavior at age 23. The 

intervention was found to be especially effective for the subgroup of children 

who displayed signs of malnutrition at age 3, suggesting the nutritional aspect of 

the treatment was particularly beneficial. The intervention was shown to produce 

lasting psychophysiological changes at age 11, including increased skin 

conductance, more orienting, and more arousal on EEG (Raine et al., 2001, 

2003b). These changes might then protect against the development of criminal 

offending (Raine et al., 1995, 1996). 

X. CONCLUSION 

Human beings are biological creatures. Whatever the truest essence of our souls 

may be, our subjective mental lives are mediated by and expressed through a 

system that is undeniably biological. This biological self exists in a specific social 

reality, which, in turn, shapes and alters the biological self in ways that will find 

some biological expression. What this chapter has sought to do is clarify how 

these biological aspects of the self can be used to understand, identify and, 

hopefully, predict individuals who criminally offend. Understanding these processes 

is the first step in then being able to modify risk factors or target at-risk 

individuals for services designed to attenuate their criminal propensity. 

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Index 

Adoption study, human aggression 

assumption and generalizability, 193–194 

forms of 

BDHI subscales, 192–193 

etiology, 191–192 

reactive and proactive aggression, 192 

relational, 192 

G x E interaction 

alcohol usage, 202–203 

family adversity and social disadvantages, 

199–201 

violent media exposure, 201–202 

heritability and environmental factors 

biological resemblance, 175 

effect size for, 175–184 

meta-analysis of, 175 

phenotype, 184 

sex-limitation, 185–186 

vs. twin study, 193 

Adrenocorticotropin (ACTH), 231–232 

Aggression 

analysis of, 3 

conflict situations, 1 

definition, 2 

drug-induced 

amphetamine, 138 

cocaine, 137 

in human, 137 

neural reorganization, 137 

in prairie vole, 136–137 

in Syrian hamsters, 137–138 

evolutionary aspects, 8 

in human (see Human aggression) 

hyperaggressive phenotypes, 2–3 

impulsive, 152 

incidence, 216 

in mammals 

mating opportunities (see Mating) 

A 

sexual dimorphism, 16–20 

(see also Mammals, aggression) 

sexual selection (see Sexual selection) 

mechanism, 4 

perinatal risk factors 

alcohol exposure, 230–232 

birth complications, 228–229 

drug, 232–233 

environmental factors, 237–238 

epigenetics, role of, 241–242 

genetic factors, 238–239 

G x E interactions, 239–241 

maternal psychological stress, 236–237 

preterm birth and low birth weight, 

229–230 

smoking, 233–235 

signaling (see Signaling aggression) 

in songbirds (see Songbirds) 

terminology, 5 

types of, 1–2, 152 

and violence, regulation of 

autonomic arousal, 225–226 

electroencephalography (EEG), 226–227 

hormones, 223–225 

neurobiological base, 218–221 

neurochemical signals, 221–223 

types of, 218 

in voles (see Prairie vole, selective aggression) 

Agonistic behavior 

in cephalopods, 37 

definition, 2 

game theory models, 38 


Amphetamine (AMPH), 138 

Anabolic-androgenic steroids (AASs), 137 

Androgens, aggressive behavior, 134–135 

Anterior hypothalamus (AH), 96–97 

Antisocial personality disorder (AsPD), 152, 259 

Arginine vasopressin (AVP) 

in hamsters, 130–132 

285

286 Index 

Arginine vasopressin (AVP) (cont.) 

in human, 129–130 

in marmoset monkey, 130–132 

in vole, neuropeptide regulation 

distribution pattern of, 128–129 

mating-induced aggression, 129–130 

selective aggression, 130–131 

signaling and structural, 130–131 

Aromatase, 93 

Astatolapia burtoni, 61 

Autonomic arousal 

heart rate and electrodermal activity, 225–226 

measurement of, 225 

Bateman’s principles, 10–11 

Bed nucleus of the stria terminalis (BNST) 

high Fos expression, 126–127 

in prairie voles, 128–129 

social behavior regulation, 127 

3-hydroxysteroid dehydeogenase, 94 

Black-throated blue warblers, 35 

Borderline personality disorder (BPD), 152 

Catechol O-methyltransferase (COMT), 

240–241 

Cephalopods, visual signaling 

chromatic skin patterns, 38 

cuttlefish agonistic bouts, 38–39 

facultative nature, 37 

during fight, aggressive motivation, 38 

parallel positioning and arm posture, 38 

rapid adaptive polyphenism, 37 

squid agonistic bouts, 40–41 

in squid, contact pheromon, 40–43 

Challenge hypothesis, 86 

Chemical signals, 25 

Chickens, dominance hierarchies in, 56 

Child Behavior Checklist (CBCL), 184 

Cichlid fish, 14–15, 67–68 

Clozapine, dibenzodiazepine antipsychotic 

agent, 160 

Cocaine, 137 

Cognitive-behavioral therapy (CBT), 235 

Computerized axial tomography (CAT) scan, 

258 

Corticosterone (CORT), 231–232 

B 

C 

Crex crex, 36–37 

Crocuta crocuta,60 

Crustaceans, 57 

D 

Dendroica caerulescens,35 

Dendroica pensylvanica, 88 

Diffusion tensor imaging (DTI), 259–260 

Dominance relationships and hierarchies 

animal models 

chickens, 56 

crustaceans, 57 

fish, 56–57 

primates, 57 

behavioral process 

animal cognitive abilities and interaction 

process, 74 

jigsaw puzzle model (see Jigsaw puzzle 

model) 

social organization, 70 

definition 

behavioral measure of, 53–54 

individual majority, 54–55 

obtaining desired food, by animal pairs, 

54–55 

two hens interactions, music notation graph 

of, 54–55 

factors, animal pairs 

behavioral states, 62–63 

genetic variations, 60–62 

physical differences, 58–59 

physiological differences, 59–60 

in groups 

hierarchy formation, 64–67 

linear hierarchy formation, 67–70 

prior attributes hypothesis, 64 

Dopamine (DA) 

human aggression 

in BPD patients, 157–158 

catecholamine neurotransmitter, 157 

in CNS, 157 

nucleus accumbens (NAc), 158 

receptor antagonist, 158 

role, 157 

specific gene polymorphism, 157–158 

in male, aggressive behavior, 99 

perinatal risk factors, 240 

prairie vole, selective aggression 

pathways, 132

Index 287 

receptors, 132–133 

regulation of, 132–134 

Drug abuse and aggression 

amphetamine, 138 

cocaine, 137 

in human, 137 

neural reorganization, 137 


in Syrian hamsters, 137–138 

Electroencephalogram (EEG) 

aggression and violence, regulation of, 

226–227 

neurocriminology, 263–264 

Endogenous opioid, 100 

Environmental Risk Longitudinal Twin study 

(E-risk study), 175–184 

Equal environment assumption (EEA), 195 

Estradiol (E2) blocker, 93 

Estrildid finches, 101–102 

Ethnographic Atlas Codebook, 20 

Event-related potentials (ERPs) 

neurocriminology, 264 

perinatal aggression, 226 

Evolutionarily stable strategy (ESS), 15–16, 

26–27 

Fetal alcohol spectrum disorder (FASD), 

230–231 

Fetal alcohol syndrome (FAS), 230–231, 270 

Field endocrinology, 89 

Functional neuroimaging, neurocriminology 

fMRI study, 260, 261 

PET technique, 260 

reduced glucose metabolism, 260–261 

reduced rCBF, 260 

schizophrenic patients, 261 

SPECT technique, 260 

Gallus gallus domesticus, 91–92 

Game theory, 3–4 

Gamma-aminobutryic acid (GABA) 


behavioral aggression, role in, 160 

E 

F 

G 

in CNS, 160 

deficiency in, 161 

in human aggression, 161 

and serotonin, 161 

subtypes, 161 

neurochemical regulation, selective 

aggression, 135 

Gene by environment (G x E) interactions 


alcohol use, 202–203 

family adversity and social disadvantage, 

199–201 

specific genes, 204–205 



perinatal aggression 

catechol O-methyltransferase, 240–241 

dopaminergic function, 240 

monoamine oxidase, 239–240 

Glutamate, 135 

Golden hamsters, 154–155 

Gonadotropin-releasing hormone (GnRH1), 61 

H 

Hawk–Dove game, 26–28 

Hormones 

aggression 

cortisol, 224–225 

oxytocin, 225 

testosterone, 223–224 

norepinephrine (NE), 158–159 

prairie vole, selective aggression, 134–135 

songbirds (see Songbirds) 

territoriality (see Territoriality) 

Human aggression 

in certain circumstances, 172 

genetic and environmental influences 

adoption study (see Adoption study, human 

aggression) 

forms of, 191–193 

G x E interaction (see Gene by environment 

(G x E) interactions) 

specific gene, genetic risk at, 203–205 

study design, 193 

twin study (see Twin study, human 

aggression) 

multidimensional behavior, 152 

neurochemistry of 

dopamine (see Dopamine)

288 Index 

Human aggression (cont.) 

GABA (see Gamma-aminobutryic acid 

(GABA)) 

impulsive, 152 

norepinephrine (see Norepinephrine) 

peptides, 162 

serotonin/5-HT (see Serotonin (5-HT), 

human aggression) 

neurotransmitters, 152 

signaling 

natural selection, 44 

vocal and facial expressions, 43–44 

vocal frequency, 43–44 

social factors, 172 

6-Hydroxydopamine, 159 

5-Hydroxytryptamine (5-HT). See Serotonin 

(5-HT), human aggression 

I 

Impulsive aggression, serotonin 

in animal, 156 

in human, 153 

norepinephrine, 160 

Intermittent explosive disorder (IED), 152 

International Center for the Study of Aggression, 

5–6 

Jigsaw puzzle model 

in hens, 72 

intransitive dominance relationship, 72 

modification of, 73 

self-structuring, 71 

sequences, 71 

transitive relationship, 71 

Lekking birds, 14–15 

Linear hierarchy 

behavioral process 

cognitive abilities and interactions, 74 

jigsaw puzzle model (see Jigsaw puzzle 

model) 

social factors influence on 

in animal group, 70 

cichlid fish, 67–68 

individual attributes, 68 

J 

L 

isolated vs. embedded fish pairs, 69–70 

round-robin competition, 67–68 

winner, loser and bystander effects, 68–69 

Loligo pealei, 40–42 

Low resting heart rate, 264–265 

M 

Magnetic resonance imaging (MRI) scan, 258 

Mammals, aggression 

mating opportunities 

cost-benefit analysis, 13 

harem holder, paternities by, 14–15 

hawk-dove game, 15–16 

sequential assessment game, 13–14 

strategies, 15–16 

pattern, 20 

sexual dimorphism 

brain structure, 19–20 

harem size and body weight, 16–17 

limited resources, 19 

male-biased, 19 

patterns of, 16–18 

phylogenetic tree, 17–19 

sexual selection 

large body size, 11 

male domination, 11 

weapons, presence and absence of, 11 

Mating 


mammals, opportunity in 

cost-benefit analysis, 13 

harem holder, paternities by, 14–15 

hawk-dove game, 15–16 

sequential assessment game, 13–14 

strategies, 15–16 

selective aggression, 123–125 

squids and cuttlefish, 37 

VMH contribution, 93–94 

Melospiza georgiana,35 

Melospiza melodia, 31, 87–88 

Mesocricetus auratus, 130 

Methylation, 241–242 

Microtus ochrogaster. See Prairie vole, selective 

aggression 

Minnesota Study of Twins and Families (MFTS), 

175–184 

Minor physical anomalies (MPAs), 269 

Monoamine oxidase (MAO), 239–240

Index 289 

N 

Neural circuits 

aggression 

dopamine, 222–223 

norephinephrine, 223 

serotonin, 222 

prairie vole, selective aggression, 124, 127 

in selective aggression, 127 

songbirds 

in BSTm, VT-Zenk colocalization, 101–102 

dopaminergic mechanism, 100 

IEG labelling, 103 

neuropeptides, 100 

stress-related process, 100–101 

V1a antagonist, 102 

Neurobiology, aggression and violence 

amygdala, 219 

in animal and human, 218 

anterior cingulate cortex (ACC), 219–220 

hypothalamus, 221 

prefrontal cortex, 220–221 

Neurocriminology 

CAT scan, 258 

functional neuroimaging 

fMRI study, 260, 261 

PET technique, 260 

reduced glucose metabolism, 260–261 

reduced rCBF, 260 

schizophrenic patients, 261 

SPECT technique, 260 

genetic contribution 

ACE model, 267–268 

adoption, 267 

gene-environment interaction, 268–269 

molecular genetics, 267 

twins, 266–267 

limitations and potential, 272–273 

modifiable risk factor interventions 

home nurse visiting, 274 

nutritional deficits, 273–274 

during pregnancy, reduce smoking, 273 

MRI scan, 258 

neuropsychological testing, 262–263 

nongenetic risk factors 

perinatal, 270–271 

postnatal, 271–272 

prenatal, 269–270 

psychodynamic theory 

concepts of, 257–258 

early problems, 257 

psychophysiological evidence 

electroencephalogram, 263–264 

event-related potentials, 264 

low resting heart rate, 264–265 

skin conductance, 265–266 

structural neuroimaging 

amygdala and hippocampus, 259 

antisocial personality disorder, 259 

atrophic brains, 258–259 

brain ROI, size of, 258–259 

conduct disoder patient, 259 

reduced gray matter volumes/thickness, 259 

white matter tracts, 259–260 

Neuropeptides 

in prairie vole, selection aggression, 128–132 

somatostatin, 62 

VT and VIP, 100 

Neuropsychology, 262–263 

Neurotransmitters. See specific 

Neurotransmitters 

New World sparrows, 87–88 

Nicotine replacement therapy (NRT), 235 

Norepinephrine (NE) 


activity, 160 

clozapine, schizophrenia treatment, 160 

fight-or-flight response, 159 

impulsive aggression, role in, 160 

shock-induced aggression, 159 

stress hormone, 159 

impulsive aggression, serotonin, 160 


Orthoptera, 25 

Oxytocin 

and human aggression, 162 


selective aggression, neurochemical, 128 

Papio anubis,57 

Paraventricular nucleus of the hypothalamus 

(PVN), 97 

Parus major,88 

Passer domesticus, 89–90 

Peptides, in human aggression, 162 

O 

P

290 Index 

Perinatal aggression 

alcohol exposure 

animal models, 231–232 

in children, 230 

disorders, 230–231 

birth complications, 228–229 

drugs exposure 

CNS alterations, 232 

cocaine, 232 

dopamine activity, 233 

on fetal organogenesis, 232 

5-HT and norepinephrine, 232 

on social relationship, 233 

environmental context, 237–238 

epigenetic, role of, 241–242 

genetic risk factors, 238–239 

G x E interactions 

catechol O-methyltransferase, 240–241 

dopaminergic function, 240 

monoamine oxidase, 239–240 

maternal psychological stress, 236–237 


preterm birth and low birth weight 

CNS damage, 229 

neuropsychological deficits, 229 

prevalence of, 230 

sex, depends on, 229–230 

smoking 

animal models, 235 

in childern’s, 234 

effects of, 235 

nAChRs, 234–235 

nicotine exposure, 234 

women, in United States, 233–234 

P300 event-related potentials, 264 

Photon emission tomography (PET), 260 

Postnatal, neurocriminology, 271–272 

Prairie vole, selective aggression 

drug abuse, 136–137 

function, 123–125 

inter- and intrasexual, 122 

mating, 123–125 

molecular genetics of, 136 

neural circuitry, 124, 127 

neural correlates of, 124, 125–127 

neurochemical regulation of 

dopamine, 132–134 

neuropeptides, 128–132 

neurotransmitters, 135 

steroid hormones, 134–135 

offensive and defensive types, 123 

pair bonding, 123 

resident–intruder test (RIT), 123 

Pregnancy, risk factors during 

alcohol, 270 

minor physical anomalies, 269 

obstetrical complications, 270–271 

in postnatal period, nutrition deficiency, 

271–272 

tobacco, 269 

traumatic brain injury, 272 

Prenatal 

alcohol exposure, 230–232 

birth complications, 228, 229 

drug exposure, 232–233 


Primates, aggression in 

dominance hierarchies, 57 

male-male aggression, 19 

nonhuman, 221 

prenatal alcohol exposure, 231 

sexual selection, 8 

Prior attributes hypothesis, 64 

Procambarus clarkii, 57 

Prolactin, 154–155 

Psychodynamic theory 

concepts of, 257–258 

early problems, 257 

Psychopathy 

genetic basis, 268 

instrumental aggression, 218 

scores, 259–260 

skin conductance, 266 

Psychophysiology 

electro cortical response measures, 226–227 

electroencephalogram (EEG), 263–264 



neurocriminology 

electroencephalogram, 263–264 





Quinpirole D2 receptor agonist, 99–100 

Q

Index 291 

R 

Reactive and Proactive Aggression 

Questionnaire (RPQ), 184 

Resident–intruder test (RIT), 123 

Regional cerebral blood flow (rCBF), 260 

Sepia officinalis, 38 

Serotonin (5-HT), human aggression 

binding potential, 155–156 

in central nervous system, 156 

components, 153 

D,L-fenfluramine, releasing agent, 154 

enhancing agent, 153 

expression, 155 

failure, 156–157 

functions, 152–153 

metabolism, 153 

neuroimaging studies, 156 

postsynaptic function, 154 

prolactin, 154–155 

subtypes, 155 

Sex 

birth control methods, 8–9 

evolutionary explanation for, 8–9 

humans, 8–9 

Sexual selection 

Bateman’s principles, 10–11 

conflicts of interest, 9 

inter- and intrasexual selection, 9–10 

limiting resources, 10 

in mammals 

large body size, 11 


weapons, presence and absence of, 11 

sex role reversal, 10 

Signaling aggression 

animal models and techniques, 30 

cephalopods, visual display in 

chromatic skin patterns, 38 

cuttlefish agonistic bouts, 38–39 

facultative nature, 37 

during fight, aggressive motivation, 38 

parallel positioning and arm posture, 38 

rapid adaptive polyphenism, 37 

squid agonistic bouts, 40–41 

in squid, contact pheromon, 40–43 

chemical signals, 25 

S 

classic game theory model 

ESS strategies, 26–27 

Hawk–Dove game, 26–27 

ethological approach, 25–26 

evolutionary issues, 29–30 

games 

Hawk/Dove models, 28 

mutual, 27–28 

in humans 

natural selection, 44 

vocal and facial expressions, 43–44 

vocal frequency, 43–44 

incomplete honesty challenge, 30 

songbirds 

aggressive escalation, 33 

black-throated blue warblers, 35 

display measures, 33–34, 34 

mate attraction, 31 

musculature function, 31 

signaler’s advantages, 36–37 

singing behaviors, 32–33 

soft song, 36 

song sparrow, spectrograms of, 31–32 

song types and variants, 31 

swamp sparrows, 35 

territory defense, 31 

threat displays 

aggressiveness motivation, 28 

modulates, social interaction, 28 

performance signals, 28–29 

resource-holding potential, 28 

strategic signals, 29 

visual sign, 25 

Single photon emission tomography (SPECT), 

260 

Skin conductance, 265–266 

Sociogenomics, definition of, 60 

Somatostatin, 62 

Songbird model, 4 

Songbirds 

causality, 107 

context, 84–87 

endocrine and neuroendocrine correlation, 

105–106 

hormonal mechanism 

evolution and life history, 95 

flocks, nonbreeding season, 91–93 

territoriality (see Territoriality) 

neural circuits, brain 

in BSTm, VT-Zenk colocalization, 101–102

292 Index 

Songbirds (cont.) 

dopaminergic mechanism, 100 

IEG labelling, 103 

neuropeptides, 100 

stress-related process, 100–101 

V1a antagonist, 102 

phentypic engineering, 107 

signaling 

aggressive escalation, 33 

black-throated blue warblers, 35 

display measures, 33–34 

mate attraction, 31 

musculature function, 31 

signaler’s advantages, 36–37 

singing behaviors, 32–33 

soft song, 36 

song sparrow, spectrograms of, 31–32 

song types and variants, 31 

swamp sparrows, 35 

territory defense, 31 

transcriptional activity 

arginine vasotocin (VT), 97–99 

Fos-ir cell count, correlations between, 

97–98 

IEG transcript, 95–96 

limbic areas, similarities in, 95–96 

paraventricular nucleus, 97–99 

social behavior network, 96–97 

white-throated sparrow 

genetic basis of, 104 

plumage polymorphism, 103–104 

social behavior, 103–104 

ZAL2 m mapping, 107–109 

Song sparrow. See also Songbirds 

aromatase mRNA expression, 93–94 

soft song, 33 

song rate, 33 

song-type matching, 33 

spectrograms of, 31–32 

T treatment of, 95 

Spizella pusilla, 87–88 

Steroid hormone 

and central DA, 135 

role of, 94 

testosterone, 134–135 

in voles (see Prairie vole, selective aggression) 

Sturnus vulgaris, 100 

Swamp sparrows 

types of calls, 35 

wing-waving, 35 

Syrian hamsters 

aggressive behavior in, 130 

drug abuse, during adolescence, 137 

T 

Taeniopygia guttata, 94 

Teacher’s Report Form (TRF), 184 

Teratogens, 230 

Territoriality 

in breeding season 

central perch, 88 

distinct species’ song, 88 

feather puffing, 88 

high-quality territory establishment, 87–88 

physical fights, 88 

simulated territorial intrusion, 88–89 

hormones 

gonadal hormone secretion, 89 

and plasma T, correlation between, 89 

plasma T profile, male breeding season, 

89–90 

in nonbreeding season 

aromatase activity, in brain, 93–94 

autumnal aggression, 93 

flocking behavior, 91–93 

gonads and ovaries regression, 91 

reduced plasma gonadal steroids, 91 

steroid hormones, role of, 94 

Testosterone (T) 

aggression and territoriality, 89–90 

aggressive behavior, 134–135 

low levels of, 85–86 

perinatal aggression, 223–224 

Traumatic brain injury (TBI), 272 

Twin study, human aggression 

additive and nonadditive, 174–175 

assumption and generalizability 

EEA, 195 

genetic and environmental influences, 

196–197 

psychiatric disorders, 194 

random mating, 195–196 

vs. singletons, 194–195 

in child, adolescent and samples, 175 

correlation across 

age groups, 187–188 

assessment methods, 189–191 

effect size for, 175–184 

between family members, 174

Index 293 

forms of, 191–193 

G x E interaction 

alcohol usage, 202–203 

family adversity and social disadvantages, 

199–201 


indirect hostility, 192–193 

meta-analysis of, 175 

monozygotic and dizygotic, 174–175 

phenotype, 184 

sex-limited effects, 185–186 

shared and nonshared environmental factors, 

174–175 

vs. sibling adoption design, 193 

verbal hostility, 192–193 

in voles, selective aggression (see Arginine 

vasopressin (AVP)) 

Vasotocin (VT), 97–99 

Violence. See Aggression 

W 

White-throated sparrow 

dominance hierarchies, 91–92 

territorial aggression in, 86–87 

genetic basis of, 104 

plumage polymorphism, 103–104 

social behavior, 103–104 

VT administration, 105–106 

Winner-loser models, 62–63 

Wood warblers, 31 

Vasoactive intestinal polypeptide (VIP), 100 

Vasopressin (VP) 

PVN, 97–99 

V 

Z 

Zebra finch, 94, 102 

Zonotrichia leucophrys, 87–88 

Zonotrichia querula, 91–92


0.1 

Human (Homo sapien) 

Other primate (consensus) 

Pig (Sus scrofa) 

Rat (Rattus norvegicus) 

Mouse (Mus musculus) 

Red jungle fowl (Gallus gallus) 

Zebra finch (Taeniopygia guttata) 

Ostrich (Struthio camelus) 

Northern pike (Esox lucius) 

Atlantic salmon (Salmo salar) 

Zebrafish (Danio rerio) 

Lancet (Branchiostoma belcheri) 

California mussel (Mytilus californianus) 

Pacific oyster (Crassostrea gigas) 

Bay scallop (Argopecten irradians) 

Limpet (Lottia gigantea) 

Longfin squid (Loligo pealeii) 

Abalone (Haliotis diversicolor) 

Bobtail squid (Euprymna scolopes) 

Rotifer (Adineta vaga) 

Human (Homo sapien) CRISP 

Mouse (Mus musculus) CRISP 

Snake (Rhinoplocephalus nigrescens) CRISP 

Frog (Xenopus laevis) CRISP 

Phylum Chordata Phylum Mollusca Phylum Rotifera 

Chapter 3, Figure 3.6. (See Page 43 of this volume). 

Chapter 5, Figure 5.5. (See Page 104 of this volume).

A B C 

10 

200 

b 

F 

AVP-ir/Fos-ir cells (density) 


8 

6 

4 

2 

0 

40 

30 

20 

10 

0 


female 

Naive 

a 

a 

CSF 

a 

a 

AVP AVP+ 

V1aR Ant 

Paired 

b 

Stranger 

male 

D E F 

b 

* 

CSF V1aR Ant 

Naive 

AH 

OT 

AH 

Paired 

AVP release (% baseline) 


150 

100 

50 

0 

80 

60 

40 

20 

0 

Partner 

* 

Stranger 

female 

* 

Control AAV-V1aR 

Chapter 6, Figure 6.2. (See Page 131 of this volume).

full text - Caspar Bgsu - Bowling Green State University

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