Development of the Social Brain, Volume 39 E-Book

• Herausgeber: John Wiley & Sons
• Kategorie: Geisteswissenschaft
• Serie: Minnesota Symposia on Child Psychology
• Sprache: Englisch

Seitenzahl: 427

Veröffentlichungsjahr: 2018

Beschreibung

Social relationships play a central role in the evolution and development of human culture and cognition. Volume 39 of the Minnesota Symposium on Child Psychology (Development of the Social Brain) adresses the ontogeny and phylogeny of the social brain from multiple perspectives and levels of analysis. The chapters in this volume shed light on shared versus unique features of social information processing across different species, and sketch out some of the cognitive and neural mechanisms that underlie such processing. A collection of chapters from distinguished contibutors offer new insights into the unique nature of human development. Flexibly and efficiently navigating the complex dynamics of social interaction remains one of the remarkable achievements of human evolution. As life in social contexts evolved, so did information processing abilities that afforded new ways of interacting with others, emerging into what we now refer to as cultural cognition or cultural practices. The primary objective of the current volume was to consider phylogenetic and ontogenetic influence on specialized social information processing capactities. The volume brings together, for the first time, distinguished research scholars to consider central themes and principles associated with the development of the social brain. Readers will take away a fresh perspective on nature of human nature.

Leseprobe

Table of Contents

Cover

Preface

List of Contributors

CHAPTER 1: The Evolution and Ontogeny of Deep Social Mind and the Social Brain

INTRODUCTION

PRIMATE MACHIAVELLIAN INTELLIGENCE AND THE SOCIAL BRAIN

FROM MACHIAVELLIAN INTELLIGENCE TO THE CULTURAL INTELLIGENCE HYPOTHESIS

THE EVOLUTION OF DEEP SOCIAL MIND

THE ONTOGENY OF DEEP SOCIAL MIND: THE LIFE HISTORY MATRIX

THE ONTOGENETIC DEVELOPMENT AND EVOLUTIONARY FOUNDATIONS OF DEEP SOCIAL MIND AND ITS SOCIAL BRAIN

CONCLUDING REMARKS

REFERENCES

PART I: Animal Models of Social Brain Function

CHAPTER 2: Neurobiology of Infant Sensitive Period for Attachment and Its Reinstatement Through Maternal Social Buffering

INTRODUCTION

NEUROBEHAVIORAL ASSESSMENT OF LEARNED MATERNAL CUES DURING THE ATTACHMENT SENSITIVE PERIOD

UNCOVERING THE EFFECTS OF EARLY-LIFE ADVERSITY

CONCLUDING REMARKS

ACKNOWLEDGMENTS

REFERENCES

CHAPTER 3: Marmoset Monkey Vocal Communication: Common Developmental Trajectories With Humans and Possible Mechanisms

INTRODUCTION

THE MARMOSET MONKEY MODEL SYSTEM

BABBLING AND PERINATAL INFLUENCES ON VOCAL OUTPUT

DEVELOPMENT OF VOCAL TURN-TAKING

TURN-TAKING AS THE DEVELOPMENTAL SYSTEM UPON WHICH INFANT VOCALIZATIONS ARE LEARNED

THE AUTONOMIC NERVOUS SYSTEM AS THE ENGINE FOR VOCAL DEVELOPMENT

EVOLUTIONARY ORIGINS

CONCLUSIONS

ACKNOWLEDGMENTS

REFERENCES

PART II: Higher-Order Human Social Brain Function

CHAPTER 4: The Social Brain in Adolescence and Adulthood: Lessons in Mindreading

INTRODUCTION: WHAT AM I THINKING?

READING MINDS AT ONE'S FOURTH BIRTHDAY PARTY: THE COGNITIVE FOUNDATIONS OF MENTALIZING

A PRIMER FOR THE NEURAL FOUNDATIONS OF THEORY OF MIND

WHAT THE DIFFICULTIES OF ADULTS CAN TELL US ABOUT THEORY OF MIND REASONING

READING MINDS LIKE BREATHING AIR: “AUTOMATIC” PERSPECTIVE TAKING

BUILDING A THEORY OF MIND: FUNCTIONAL AND NEURAL CHANGES THROUGH CHILDHOOD AND ADOLESCENCE

CONCLUSION

REFERENCES

CHAPTER 5: Developmental Social Neuroscience of Morality

INTRODUCTION

DEFINITIONAL ISSUES AND THEORETICAL PERSPECTIVES

PERCEPTION AND SENSITIVITY TO INTERPERSONAL HARM

NEURODEVELOPMENTAL CHANGES IN THIRD-PARTY PERCEPTION OF INTERPERSONAL HARM

NEUROLOGICAL LESIONS THAT IMPAIR MORAL COGNITION AND BEHAVIOR

ATYPICAL FUNCTIONAL AND ANATOMICAL CONNECTIVITY

WHAT WE HAVE LEARNED

WHERE SHOULD DEVELOPMENTAL NEUROSCIENCE BE HEADING?

REFERENCES

NOTE

PART III: Summary and Future Directions

CHAPTER 6: Development of the Social Brain: From Mechanisms to Principles

INTRODUCTION

MECHANISTIC FEATURES OF NEURAL DEVELOPMENT

THE SOCIAL ENVIRONMENT: PERMISSIVE, INSTRUCTIVE, ENABLING, AND/OR BUFFERING?

CAUSALITY: PARTIAL CORRELATION VERSUS TEMPORAL ORDER

WHAT ARE THE PROCESSES? INSIGHTS FROM THE VARIED NATURE OF MENTALIZING

DOMAIN SPECIFICITY REVISITED

FROM MECHANISMS TO PRINCIPLES

ACKNOWLEDGMENTS

REFERENCES

Author Index

Subject Index

End User License Agreement

List of Tables

Chapter 1

Table 1.1 Articles indexed in Web of Knowledge according to key words in title or in topic field.

List of Illustrations

Chapter 1

Figure 1.1 Group size and encephalization (here, executive brain ratio = volume of cortex over rest of brain) in primates.

Figure 1.2 Social learning and encephalization in primates. Frequency of social learning in the survey of Reader and Laland (2002) is plotted against executive brain ratio (see text for further explanation). Labels refer to three species with complex cultures discussed extensively in the text.

Figure 1.3 Deep Social Mind. Principal classes of social cognition (in bold capitals) in hunter-gatherer bands and inferred reinforcing relationships between them, with causal link indicated by directional arrows (after Whiten & Erdal, 2012). Note that such relationships cannot be exhaustively illustrated in a single legible figure; those shown are indicative only. For explanation and discussion see text.

Chapter 2

Figure 2.1 This schematic represents pups' transitions in attachment learning with odor-0.5mA shock conditioning. Pups younger than PN10 have robust attachment learning during a sensitive period due to low CORT levels. This learning circuit requires low levels of CORT and involves maternal behavior stimulation of the locus coeruleus to release norepinephrine into the olfactory bulb to induce the neural changes required for pup learning. Older pups readily learn amygdala-dependent fear because of CORT's action on the amygdala to permit learning-induced plasticity, although maternal presence through social buffering lowering of CORT enables the reinstatement of the sensitive period (Moriceau, Wilson, Levine, & Sullivan, 2006; Upton & Sullivan 2010).

Figure 2.2 This figure summarizes how the HPA axis, social buffering, and its impact on amygdala-dependent fear changes during development. In the youngest pups, during the sensitive period for attachment, the stress hyporesponsive period (SHRP) means pups have low CORT even when receiving stimuli such as shock and adult-like social buffering does not occur. This age range is associated with attachment learning with a wide range of stimuli, including milk, tactile stimulation, or pain from shock or an abusive mother. The maternal odor activates the paraventricular nucleus (PVN) and the prefrontal cortex (PFC). With maturation, pups enter the transitional sensitive period and amygdala-dependent fear learning occurs. However, maternal odor socially buffers pups, and entirely blocks CORT release and amygdala-dependent fear. Finally, as pups approach weaning and independence, the system becomes more adult-like with amygdala-dependent fear and social buffering that does not block fear learning. While social buffering at this age only blocks CORT release by half, additional blockade of CORT to more fully block CORT still does not reinstate attachment learning. This suggests a fundamental change in the ability of social buffering to alter pups' neurobehavioral function (Moriceau et al., 2006; Upton & Sullivan, 2010).

Chapter 3

Figure 3.1 Infant marmoset vocalizations undergo dramatic acoustic changes. (A) Vocalizations from one infant. (B) Twitters and trills change usage whereas cries, phee-cries, and subharmonic-phees transition to phee calls.

Figure 3.2 Babbling sequences and their similarity among twins. (A) Transition diagrams visualizing vocal sequences from two subjects at different postnatal time points. Each node in the diagram corresponds to a type of call, and the arrows correspond to the transitions between call types. The five most frequently produced call types are: phee (Ph), twitter (Tw), trill (Tr), cry (Cry), and phee-cry (P-C). Node size is proportional to the fraction of the call types, and edge size is proportional to the transition probability between calls. Thin dashed arrows are where transitions dropped below 5% occurrences. (B) Transition diagrams of vocal sequences from the first postnatal week for three sets of twins. Each twin set is arranged in the vertical order with the highlighted most frequent four-call transitions plotted on the right. (C) Comparison of JSDRs in three relationship categories: twins (= 5), nontwin siblings (

n

= 12), and nonsiblings (

n

= 28), p = 3.8e-5, ANOVA.

Figure 3.3 Transition from cry to phee is influenced by contingent parental calls. (A) Weighted average entropy of infant calls produced before adult call onset and after adult call offset. The shaded regions indicate the respective 95% confidence intervals. (B) Correlations between the transition day and the proportion of contingent (left) and noncontingent (right) parental responses, respectively.

Figure 3.4 Vocal-production learning by infant marmoset monkeys. (A) Twin infants received either high-contingency playbacks (100%) or low contingency playbacks (10%). Spectrograms depict when such playbacks were delivered relative to the infant vocalizations. (B) Wiener entropy (in decibels) changes over postnatal days for high and low contingency infants. (C) Dominant frequency (in kilohertz) changes over postnatal days for high and low contingency infants. Shaded regions indicate 1 standard error intervals.

Figure 3.5 Physiological mechanisms of vocal development in marmoset monkeys. Figure shows a schematic illustrating spontaneous vocal production as a function of ANS oscillation and the threshold to vocalize. The continuously produced vocalizations by very young infant marmosets are driven by the natural rhythmic activity of respiration whose power is modulated by the slower, ∼0.1 Hz rhythm of the ANS. This consequently changes the quality of the vocalizations so that they fluctuate between high (cry) and low (phee) levels of entropy.

Chapter 5

Figure 5.1 Converging evidence from social neuroscience and neurology demonstrates that brain regions underpinning moral reasoning are widely distributed and share computational resources with circuits controlling other capacities such as emotional saliency, mental state understanding, valuation of rewards, and decision-making. These regions include the posterior temporal cortex (pSTS) near the temporoparietal junction, amygdala, insula, ventromedial prefrontal cortex (vmPFC), dorsolateral prefrontal cortex (dlPFC), and medial prefrontal cortex (mPFC). Importantly, both empathic concern and moral decision-making require involvement of the vmPFC, a region that bridges conceptual and affective processes, necessary to guide moral behavior and decision-making. Human neuroimaging and primate electrophysiology studies show that the vmPFC tracks the personal subjective value of a wide range of stimuli during active decision-making and even in the absence of choice. Early damage to this region leads to impaired moral judgments and decision-making, a lack of concern for others, and failure to learn from repeated mistakes, despite normal intellect and explicit knowledge of the consequences of one's decisions.

Chapter 6

Figure 6.1 Trying to understand a microprocessor by lesioning every single one of its transistors. The map of transistors (right) shows which locations, when lesioned, prevented the execution of one of three video games or their combination (inset: Donkey Kong, Space Invaders, or Pitfall). Yet these mere mappings produced no understanding of how the microprocessor works at all, illustrating that the functions implemented by individual transistors are difficult to map onto the overall function of the chip in playing video games.

Figure 6.2 Levels of abstraction in a developmental social neuroscience. Inspired by David Marr's well-known scheme (Marr, 1982), and variously applied already to social cognition (Mitchell, 2006), the figure makes the point that we ultimately need to understand the adaptive problem in the service of which a particular mechanism was selected through evolution. Mediating between this broad driving force of evolution's design, and the causal mechanisms we can trace in the brain, are process-level computations or algorithms (although they need not be written as an equation or script) that serve to summarize how neurobiological data achieve the functions that they do.

Guide

Cover

Table of Contents

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E1

Minnesota Symposia on Child Psychology

Development of the Social Brain

Volume 39

Edited by

Jed T. Elison

Maria D. Sera

Copyright © 2018 by John Wiley & Sons, Inc. All rights reserved.

Published by John Wiley & Sons, Inc., Hoboken, New Jersey.Published simultaneously in Canada.

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FIRST EDITION

Preface

The origin for what would become the Minnesota Symposia on Child Psychology, formally established in a 1966 meeting and subsequent volume the following year, can potentially be traced to an event in December 1955 organized by Dale Harris, director of the Institute of Child Development at the time. Among the participants at this meeting, and contributors to the volume published in 1957 as The Concept of Development: An Issue in the Study of Human Behavior, was T.C. Schneirla. Schnierla's theoretical and empirical contributions were rather disruptive at the time, and in some respect remain so, challenging popular notions of instincts and simplistic conceptualizations of maturational processes, among others. More relevant to our concerns, Schneirla's work consistently considered developmental change across ontogenetic and phylogenetic frames of reference. He also attempted to explicate a precise and parsimonious description of development, hence the invitation from Professor Harris.

The concept of development would remain the organizing theme for the Minnesota Symposia meetings/volumes until the first topical meeting was held in 1977 on language development. This would become the 12th volume, published in 1979. How did the concept of development fill 11 volumes from 1967 to 1978? In his contribution to the eighth volume in 1974, Irv Gottesman paraphrased Paul Meehl's paraphrase of Albert Einstein: “The trouble with The Concept of Development – the annual organizing theme of these volumes – is that it is too difficult for developmental psychologists, and further, that it is too difficult for developmental biologists.” In partial homage to Schneirla and Gottesman, we opted to embrace the complexity of ontogenetic and phylogenetic development in the current volume.

Ninety years after the founding of the Institute of Child Development, 70 years after Harris's meeting, nearly 40 years after Nicolas Humphrey's The Social Function of Intellect, 30 years since Michael Gazzaniga's The Social Brain: Discovering Networks of the Mind, and 25 years after Leslie Brothers published The Social Brain: A Project for Integrating Primate Behavior and Neurophysiology in a New Domain, we organized the 39th Minnesota Symposium on Child Psychology around the topic of the Development of the Social Brain. I had preferred the title Phylogeny and Ontogeny of the Social Brain, but as we attempt to impress on our trainees, concise writing generally represents the best course of action (although the previous sentence may betray my career stage). This topic attempts a synthesis across two distinguishable lines of research: the phylogenetic line, which focuses on identifying the factors that could possibly account for the disproportionate expansion of the primate neocortex, and a second line of research focused on characterizing the conditions by which specific neural circuits become dedicated to processing social information across ontogeny.

To this end, the primary objectives of the two-day symposium held in October of 2015 and this, the subsequent volume were fourfold:

To delineate the prerequisites for the existence of neural circuitry dedicated to processing social information

To consider the specialized computational features of putative social brain networks

To consider shared versus unique features of social information processing strategies across species

To advance a comprehensive yet parsimonious conceptualization of the necessary and sufficient features that constitute the putative social brain

Developmental social neuroscience represents an emerging field of study that attempts to identify the necessary and sufficient developmental processes that explain specialized social information processing abilities observed in young children. Of course it is easy to counter the claim of newness, especially if we broaden the search space to include examples like the work of Klüver and Bucy from 1939 or more recent work from Jocelyne Bachevalier or David Amaral. One assumption of this program of research is that the complexity of human social cognition stems from the complexity of structural and functional patterns of neural connectivity, which is shaped by both phylogenetic and ontogenetic developmental processes. Arguably, yet consistent with the phylogenetic theme of our opening chapter, much of child development, both behaviorally and at the neural level, prepares individuals to flexibly and efficiently navigate the complex dynamics of social interaction inherent to the unique cultural demands of our species. Neural circuitry within the putative social brain has proven vulnerable to abnormal function across a variety of psychiatric and neurological conditions. And as psychiatric disorders are recast as disorders of neurodevelopment (or circuit level dysfunction that accumulates over time), understanding the processes that shape brain development prior to the onset or consolidation of clinically impairing features is critical. The contributions herein largely focus on typical or normative processes but all have relevance to at-risk or clinical samples.

The primary strength of this volume is the unique collection of distinguished contributors. It is easy for developmental psychologists to find themselves in echo chambers – of course we think development is complex and that the concept of development deserves 11 consecutive published volumes. Why would we choose to spend a career tinkering about on something simple? But when you mix the right neuroscientists, neurobiologists, primatologists, and experimental psychologists in a room full of eager developmentalists, you've got a recipe with great potential.

Andrew Whiten opens the volume with a history and summary of work that culminates in his characterization of the Deep Social Mind, a distinctly human phenotype created by cumulative culture, hypercooperation, egalitarian dispositions, the capacity to use inferences about others' mental states to guide one's own behavior, and language. Next, the volume proceeds into specific comparative examples of social brain function. Sullivan and Opendak describe a body of work highlighting the maternal caregiver's capacity to buffer a rodent's stress response system at a specific time during early development. The role of the social environment is also a key element of Ghazanfar and colleague's contribution. They offer a compelling example of convergent evolution among marmosets and humans, describing the shared developmental processes that shape specialized vocal communication. Both of these chapters highlight careful explications of time, or sensitive periods for foundational social behaviors. The two subsequent chapters transition to higher-order representation in humans, drawing on evidence from a diverse suite of neuroscience methodologies implemented with developing samples. Theory of Mind (c.f. Pollard, Heyes, and Apperly) and moral cognition (Decety and Cowell) both represent “top-of-the-food-chain” constructs to some degree. Although much attention has been allocated to these areas of research in (a) traditional social neuroscience studies with adults and (b) developmental studies (sans neuroscience methods), the time is ripe for an integrative approach to these themes from a developmental social neuroscience perspective. The volume concludes with a summary by Ralph Adolphs and myself specifically crafted to motivate and inform future studies.

Many people who deserve recognition contributed to the two-day event and the generation of this volume. I want to thank my co-organizer and co-editor, Maria Sera, who was with me at each step with valuable advice and guidance. I am indebted to Melissa Koenig, Suma Jacob, Alan Love, and Michael Wilson (a psychologist, psychiatrist/neurobiologist, philosopher, and primatologist, respectively) for participating in a panel discussion to close the first day of the symposium. It is difficult to quantify the behind-the-scenes coordination for the event, but Delores Mordorski, Brittany Howell, Angela Fenoglio, Katie Ridge, Max Herzberg, Sarah Suarez, and Brandon Almy deserve special recognition. Lastly, I want to express the utmost gratitude to our speakers and contributors; Andy Whiten, Regina Sullivan, Maya Opendak, Asif Ghazanfar, Daniel Takahashi, Yisi Zhang, Jeremy Borjon, Tobias Grossmann, David Pollard, Stephanie Heyes, Ian Apperly, Jason Cowell, Jean Decety, and Ralph Adolphs. Chapters are difficult sells in our current publishing climate. Although I would predict that each contributor participated in part to disseminate their science, I suspect that each was fully aware that they were helping out an assistant professor with a crazy idea about the social brain, and for this I am grateful.

Jed Elison

List of Contributors

Ralph Adolphs, PhD

California Institute of Technology

Pasadena, CA

Ian Apperly, PhD

University of Birmingham

Birmingham, UK

Jeremy I. Borjon

Princeton University

Princeton, NJ

Jason M. Cowell, PhD

University of Wisconsin – Green Bay

Green Bay, WI

Jean Decety, PhD

University of Chicago

Chicago, IL

Jed T. Elison, PhD

University of Minnesota

Minneapolis, MN

Asif A. Ghazanfar, PhD

Princeton University

Princeton, NJ

Stephanie Burnett Heyes, PhD

University of Birmingham

Birmingham, UK

Maya Opendak, PhD

New York University

New York, NY

David Pollard

University of Birmingham

Birmingham, UK

Maria D. Sera, PhD

University of Minnesota

Minneapolis, MN

Regina M. Sullivan, PhD

New York University

New York, NY

Daniel Y. Takahashi, PhD

Princeton University

Princeton, NJ

Andrew Whiten, PhD

University of St. Andrews

St. Andrews, UK

Yisi S. Zhang, PhD

Princeton University

Princeton, NJ

CHAPTER 1The Evolution and Ontogeny of Deep Social Mind and the Social Brain

ANDREW WHITEN

INTRODUCTION

A core hypothesis of the theory of Deep Social Mind (DSM) is that the extraordinary evolutionary success of our species is explicable not through some one critical mental attribute (intelligence, culture, language) as is often proposed, but rather by an adaptive cognitive complex that involved a whole suite of interrelated refinements to our ancestral ape psychology (Whiten & Erdal, 2012). More specifically, the proposal is that the human mind became more profoundly and deeply social than the minds of our primate relatives and ancestors in a cluster of dimensions, involving enhanced cooperation, egalitarianism, culture, mindreading, and language. This has obvious implications for understanding both the underlying neural machinery of the social brain that implements these functions and for the developmental psychological processes that build deep social minds in each generation – the foci of this volume.

The concept of the social brain – itself multistranded, as we shall see – has its roots in the study of primate social complexity, and I begin this chapter with an overview of the rationale and scope of the key ideas and empirical findings of this research field, with a focus on the variants variously described as the “social intellect hypothesis,” “Machiavellian intelligence hypothesis,” and “social brain hypothesis.” This leads in turn to what may be regarded as part-offspring and part-competitor of these hypotheses: the “cultural intelligence hypothesis.” The latter also forks into interesting subcomponents, as we shall see.

These hypotheses and the findings that bear on them provide foundations for the subsequent part of the chapter, which addresses the scope of Deep Social Mind in its particularities. I review both the characteristics that differentiated evolving human minds from those of their primate ancestors, and what we know of those ancestral minds that so importantly provided the foundations for these special human achievements. We can then address the ontogenetic development of Deep Social Mind in humans, and its foundations in the life histories that characterized our primate ancestry.

The intertwined concepts of social intelligence and social brain have been increasingly influential in research endeavors across the behavioral and cognitive sciences. Table 1.1 is offered to illustrate this, showing the numbers of relevant publications in 5-year blocks during the past quarter century. The accelerating pace of work in these domains is clear. Accordingly, what follows below is necessarily highly selective. My aim is to offer overviews of major themes and discoveries that link comparative, evolutionary, developmental, and neuroscientific studies.

Table 1.1 Articles indexed in Web of Knowledge according to key words in title or in topic field.

1991–1995

1996–2000

2001–2005

2006–2010

2011–2015

TOTAL

SOCIAL INTELLECT

*

in title

21

31

43

121

109

325

SOCIAL BRAIN in title

0

4

38

100

151

251

SOCIAL INTELLECT

*

as topic

60

80

155

348

464

1,107

SOCIAL BRAIN as topic

3

10

64

255

537

869

*SOCIAL INTELLECT = social intellect or social intelligence or Machiavellian intelligence.[Note: Searches use operator “Near/0” to include paired terms only when adjacent, e.g., “social brain.”]

PRIMATE MACHIAVELLIAN INTELLIGENCE AND THE SOCIAL BRAIN

In “The Social Function of Intellect,” Nick Humphrey (1976) is generally recognized as the first to clearly articulate what came to be called “the social intellect hypothesis.” The key idea, a radical one at the time, was that the acknowledged distinctive intelligence of nonhuman primates (henceforth “primates”) was not so much an evolutionary product of dealing with physical problems in their natural lives, like how and where to best forage or avoid predators, but was rather an adaptation to grappling with the special complexity being revealed in primates' social lives. Humphrey's proposition had been prefigured by some earlier glimmerings of the significance of primate social complexity (e.g. Jolly, 1966) but it was Humphrey who expressed the theory most explicitly and fully, leading a small but growing band of primatologists to shape their empirical work around it in the years that followed.

Over a decade later there were sufficient developments to fill a book on the topic, and Richard Byrne and I assembled Machiavellian Intelligence (Byrne & Whiten, 1988) to do so. The title was created in part under the influence of de Waal's (1982) Chimpanzee Politics, an account of the complex and dynamic power struggles amongst shifting alliances in a colony of chimpanzees, our closest living relatives. De Waal was often able to quote the advice given by Nicolo Machiavelli (1513) to the politicians (princes) of the day about how to subtly and skillfully manipulate one's social companions, because the advice matched up with the tactics of the chimpanzees. In adopting the tag of “Machiavellian Intelligence” we sought not to emphasize the nasty side of social scheming that is sometimes associated with Machiavelli's name in everyday language, but rather the fine adjustment of both competitive and cooperative maneuvers that Machiavelli explicated in his writings. This is the crucial link because although there is always a thread of competition attendant on living in any social group in the wild, in monkeys and apes this competition is subserved by the formation of alliances and coalitions, and these fluctuate in dynamic ways. Social skill in some thus creates pressure for greater skill in others, in a potentially spiraling “arms race.” Humphrey compared primate social life to something like a game of chess, in which one's gambits were always played out in a social arena where the other players are constantly reactive and responsive, creating a moving landscape in which nimble social tactics are constantly selected for.

Whiten and Byrne (1988a) pointed out that, in fact, three different manifestations or levels of the social or Machiavellian intellect hypothesis (MIH) should be distinguished. The most basic is simply the hypothesis that in contrast to much of the earlier work focused on intelligence engaged with the physical problems typically posed in the comparative psychologist's laboratory, primate intelligence is also much engaged with social life. This version of the hypothesis may seem elementary, but it has led to what are now decades of rich and fascinating research that explores and identifies the complexities of primate social cognition in both wild and captive primates (Seyfarth & Cheney, 2015a, 2015b). The second and more ambitious version of the hypothesis is the claim that intelligence has been molded and enhanced more by social life than by other challenges such as foraging and predator evasion. The third version goes further to propose that the very nature of intelligence has been shaped by these social forces, so that there are characteristics of the primate mind and brain specifically adapted for the application of intelligence to the social realm. What Humphrey called “natural psychology,” nowadays referred to by terms like Theory of Mind or mindreading, would be one such phenomenon (discussed later, under the heading “Mentalizing”), evolving as an adaptation to deal specifically with one's social world.

To many primatologists who in their research on primate social life were daily impressed by its intricacies, hypotheses such as these had an immediate and inherent plausibility. Testing them rigorously is another matter. Interestingly, this challenge was first taken up, influentially, by a focus on the brain. Robin Dunbar (1995) examined the relationship between measures of a primate species' relative brain size – encephalization – and a simple index of social complexity, the typical size of social groups in that species, and found the positive relationship the social intellect hypothesis predicts, whereas ecological variables did not have the same predictive power. Dunbar later dubbed the neural version of the MIH highlighted by this discovery the Social Brain Hypothesis (Dunbar, 1998; but see also Brothers, 1990, for a pioneering, earlier exploration of the Social Brain). Among the principal merits of Dunbar's approach is that the variables involved – namely, group size and neural volumes – are much more amenable to straightforward measurement than concepts like either social complexity or the sophistication of social cognition; among its limitations, of course, is that for those principally interested in these latter phenomena, the variables subjected to test represent relatively simplistic, surrogate entities. Nevertheless, the basic tractability of the approach has allowed a plethora of related research to expand on this foundation.

Testing and Elaborating on the Social Brain Hypothesis

Even the “simple” brain and group size measures for such analyses need to be carefully chosen to make the tests meaningful. Larger animals tend to have larger brains in any case – in absolute terms, whales' and elephants' brains are larger than ours – so this basic allometric relationship needs to be compensated for. Equally, in hierarchically structured primate communities, it is by no means straightforward to assess what are the most meaningful social entitities to subject to quantification.

The body size issue has been addressed in many different ways, either by controlling directly for this variable – not straightforward because the effects are nonlinear – or in other ways. For example, Dunbar (1998) approached the issue by focusing on the neocortex ratio, the ratio of neocortex volume to the volume of the remainder of the brain, and found that this was positively correlated with a species' average group size (Figure 1.1); whereas it was not related to other, ecological variables like home range size that would have been expected if primate intellect was for dealing with physical complexities such as navigation and foraging on the complex distributions of food items. Instead, the social brain hypothesis was supported. Other studies have focused on more refined measures on the societal side, such as the size of social cliques marked by the most intense social relationships (Kudo & Dunbar, 2001), or on indices of social skills, such as the frequency of tactical deception episodes reported (Byrne & Corp, 2004; Whiten & Byrne, 1988b), and found the relationships with neocortex ratio predicted.

Figure 1.1 Group size and encephalization (here, executive brain ratio = volume of cortex over rest of brain) in primates.

Source:From Dunbar and Shultz(2007), with permission.

Such analyses have since been extended not only to mammals other than primates, but also to birds. For the latter, the interesting finding was that it was not the size of social communities or social systems that explained relative brain size, but rather the mating system, with the greatest encephalization in those species with long-term pair bonding (Emery, Seed, von Bayern, & Clayton, 2007). Shultz and Dunbar (2007) also explored the sociality–encephalization relationship in carnivores, bats, and ungulates as well as primates and found that it was also pair-bonding that was most strongly related to relative brain size in all these taxa, except the primates. There is thus something special about the primate order to which we belong. These authors share the interpretation that for birds and most mammals, pair-bonding and the biparental care that accompanies it requires the management of intricate coordination and synchrony and thus encephalization, with analogous, bonded, negotiated relationships extending these principles in the societies of monkeys and apes (Emery, Seed, et al., 2007; Shultz & Dunbar, 2007). Shultz and Dunbar (2010) further showed that encephalization is not a universal trend in different orders of mammals, but is more marked in those with higher degrees of sociality like primates, supporting the social brain hypothesis from another perspective.

This broader taxonomic corpus of work (for more extensive reviews, see papers cited in the previous paragraph and Dunbar & Shultz, 2007, 2010) has interesting implications for the evolution of the human social brain. On the one hand we are primates, and this line of research shows that our sophisticated social brains did not spring out of the blue but instead have likely been built on neural adaptations for complex social life widespread among the primate order, especially monkeys and apes. On the other hand, the evidence of a link to pair-bonding and biparental care in birds and nonprimate mammals is intriguing because we are the only great apes to have evolved pair-bonding and biparental investment. Such familial characteristics are typical across those hunter-gatherer societies that offer the best models for our evolutionary past ways of life (Whiten & Erdal, 2012). Accordingly these two features, complex primate social life and pair-bonded parental investment embedded within band life, may together help explain our unique degree of encephalization.

Efforts to pursue links between social complexity and brain variation in humans have simultaneously extended to focus on particular parts of the brain (Platt, Seyfarth, & Cheney, 2016). For example individuals' social network size has been found to predict the volume of regions such as the amygdala, which is implicated in emotional responses and vigilance (Bickart, Wright, Dautoff, Dickerson, & Barrett, 2011) and other parts involved in social functions including orbitofrontal cortex (Powell, Lewis, Roberts, Garcia-Finana, & Dunbar, 2012) and ventromedial prefrontal cortex (Lewis, Rezaie, Brown, Roberts, & Dunbar, 2011). Kanai, Bahrami, Roylance, and Rees (2011) showed that the number of an individual's Facebook friends is associated with the density of gray matter in the superior temporal sulcus (STS) and temporal gyrus.

However, some researchers have failed to find the relationships between social factors and encephalization that the social brain hypothesis predicts. For example, Reader, Hager and Laland (2011) reported that in their analyses across 62 primate species, social dimensions did not have special predictive power in relation to brain volume, but were instead correlated with other measures, supportive of hypothesized variation in general intelligence or “primate gs.” These authors suggest that “this highly correlated composite of cognitive traits suggests social, technical and ecological abilities have coevolved in primates, indicative of an across-species general intelligence that includes elements of cultural intelligence” (p. 1017).

Primate Social Complexity and Social Cognition

Other lines of research proliferating since the early days of Machiavellian Intelligence have focused on exploring social complexity and social cognition, leaving the question about encephalization to one side. There is not space here to do justice to this corpus of work, but a selection of findings can be highlighted for illustration. For a more extensive recent review see Seyfarth and Cheney (2015b).

Cheney and Seyfarth and their associates have completed an impressive series of field experiments on social cognition with African vervet monkeys and baboons – often a challenging endeavor because of the difficulty of engineering control conditions in the wild. These studies have been particularly instructive in revealing surprisingly deep levels of social knowledge in these primates. For example, baboons' knowledge of the relative ranks of others (third-party social knowledge) was investigated by playing back calls (Cheney, Seyfarth, & Silk, 1995). Normally, higher-ranked and lower-ranked individuals each use recognizably different vocalizations when interacting over the latter's infant; in the experiment these were swapped, and it was shown that the baboon subject hearing this attended for longer than in control conditions, showing they recognized the anomaly. Similar evidence that primates recognize the relative ranks of others comes from a variety of primates, most recently for vervet monkeys by Borgeaud, Alvino, van Leeuwen, Townsend, and Bshary (2013), who review this corpus of studies to date. In another experiment that underlines the sophistication of social knowledge possessed, baboons hearing a reconciliatory vocalization from a close relative of an opponent are more likely to approach the opponent and tolerate their approaches, showing a remarkable grasp of the way the social network of their companions operates (Wittig, Crockford, Wikberg, Seyfarth, & Cheney, 2007).

If a species' typical social complexity has selected for an adaptive brain size over evolutionary time, there is now also evidence that the experience of social complexity can affect brain structure during the lifetime. Sallet et al. (2011) assigned macaques to small groups of different sizes and found that group size predicted later gray matter thickness in a circuit including a number of regions including the amygdala and STS. These researchers even found a similar effect in a region in the prefrontal cortex predicted by a monkey's social rank in the group.

FROM MACHIAVELLIAN INTELLIGENCE TO THE CULTURAL INTELLIGENCE HYPOTHESIS

The relationship between measures of encephalization and of social complexity summarized earlier show a good fit across primates as a whole, but more so when the great apes are separated from monkeys (Figure 1.1). This is because the apes are yet more encephalized – and this is something the social intellect/brain hypothesis does not explain well, because the apes, as a group, are not supremely socially complex. It is true that chimpanzees are socially complex, living in particularly fluid, fission-and-fusion societies. But gorillas live in relatively stable and smallish groups, while orangutans are quite minimally social or even quite solitary. Accordingly, an alternative explanation explored by van Schaik (2006) and Whiten and van Schaik (2007) appeals instead to the role of culture, which our research has suggested reaches its most elaborate forms among the great apes.

Over the decades for which wild apes have been studied, evidence has accumulated for regional differences in behavior that circumstantial evidence of various kinds suggests are cultural; that is, they are passed from generation to generation by forms of social learning – learning from others. Whiten et al. (1999) collated the first systematic analysis of these discoveries in chimpanzees across long-term African study sites and concluded that as many as 39 different putative traditions existed, identified as behaviors common in some communities yet absent in others, without apparent ecological or genetic explanations. Although traditions were known in other species, such as regional bird song dialects, chimpanzee cultures appeared distinctive in their numbers and their range, incorporating such varied cases as tool use, foraging techniques, grooming methods, and courtship gambits. Moreover, each community was found to display a unique cluster of traditions, such that knowing enough of these, a researcher could allocate a chimpanzee to their home region on the basis of their cultural profile, as we can often do for humans. Shortly later, van Schaik et al. (2003) collated equivalent records for orangutans, showing a remarkably similar, if somewhat less rich, overall picture of cultural complexity (and as I write, Robbins et al. (2016) have now reported the same for gorillas). Accordingly Whiten and van Schaik (2007) concluded that as long ago as the origin point of the great apes, around 14 million years ago, the foundations were in place for these unusually complex forms of animal culture. Humanity's extraordinary capacity for culture thus did not emerge out of the blue, but instead evolved by elaborating on great apes' “cultural brains.”

The cultural intelligence hypothesis corresponds to the social intelligence hypothesis, but posits that some evolutionary elaborations of intelligence are due not so much to social complexity manifested in the interplay of competitive and collaborative social relationships, as to a species' cultural complexity. We see this particularly in the great apes among primates, but in principle it can of course apply to any animals that display these characteristics; other prime candidates include cetaceans – whales and dolphins, which are also large-brained and for which evidence of multiple cultures in their vocal, migratory, and foraging behaviors are accumulating (Rendell & Whitehead 2001; Whitehead & Rendell 2015). The cultural intelligence hypothesis can accordingly be seen as a competitor to the social intelligence hypothesis insofar as its explanatory capability is concerned, but conceptually it could equally be seen as a particular version of the social intellect hypothesis that emphasizes one particular component of an animal's social life – that which embodies the transmission of culture.

There are also multiple potential causal pathways to recognize within the cultural intelligence hypothesis. In one, causality runs ontogenetically from culture to intelligence, and can be summed up in the proposition that culture makes you smart; what a child or juvenile chimpanzee can learn from its cultural environment gives it greater cognitive competences (like tool usage) to succeed in life, with the ultimate result of greater reproductive potential, the stuff of evolution. Another causal arrow from culture to intelligence is embedded in longer, evolutionary timescales because it concerns the selection pressures arising from the importance of culture to the species, which will mold culture's cognitive underpinnings and the corresponding components of the social/cultural brain. These include capacities supporting cultural transmission, such as imitation and teaching, and complementary powers of invention that create the innovations that are equally necessary to culture. In a sense, this embodies the slogan that culture makes you smart, but in this case we are talking not of ontogenetic timescales but of the importance of culture in shaping the long-term evolution of species' brains and cognitive capacities.

Evidence consistent with these hypotheses comes from a great variety of sources for different taxonomic groups, including humans, other apes, other primates and nonprimates, surveyed at length by Whiten and van Schaik (2007) and van Schaik and Burkart (2011). Here there is space only to indicate the scope of such evidence, and the reader is directed to these reviews for a more comprehensive treatment. For humans, of course, the proposition that culture makes you smart ontogenetically is not in dispute; the acquisition of the competences that allow our species to so dominate the world begins as infants learn from their parents and others, and indeed is the raison d'être of the whole of our modern educational systems. For the other apes, evidence comes in a variety of forms. First, a substantial corpus of social learning experiments now show that apes are capable of learning techniques, such as those for tool use and foraging, through observation of one or more of their group members trained to be expert at the task (Whiten, Horner, Litchfield, & Marshall-Pescini, 2004). One telling study of wild chimpanzees consistent with this work showed that juvenile female chimpanzees were much more assiduous than their male peers in observing the skilled use of tools to extract prey from termite mounds, and they became “smarter” in successfully applying the technique a whole year ahead of their male peers (Lonsdorf, Pusey, & Eberly, 2003). This kind of effect can have significant survival value, with some studies noting that some forms of tool use allow chimpanzees to survive through dry, bottleneck seasons in which only the corresponding embedded food sources are available (Yamakoshi, 1998). A second form of evidence is that in both chimpanzees and orangutans, greater opportunities to learn from others due to more extended times in association with groupmates in some communities are linked to acquisition of the more complex techniques of their cultures, like those involving tool use (Whiten & van Schaik, 2007). A third, quite different kind of evidence is that the enculturation that occurs when young apes are raised in intimate relationships with humans and their cultures creates an enhanced capacity to learn by imitation and a correspondingly large repertoire of competences, from symbolic communication to technological abilities never otherwise seen in apes (Tomasello & Call, 2004; Tomasello, Savage-Rumbaugh, & Kruger, 1993; Whiten, 2011).

Evidence that culture, or at least transmission via social learning, selects for enhanced cognition comes from an analysis that found stronger relationships between a measure of encephalization (executive brain ratio – the volume of the cortex and striatum relative to that of the brain stem) and reports in the research literature of primate species' prevalence of social learning, innovation, and tool use, than for social group size (Reader & Laland, 2002). Social learning explained more of the variance than any of the other variables examined, with r2 as high as 0.48 (Figure 1.2). Reader and Laland (p. 4440) concluded that their results “suggest an alternative social intelligence hypothesis to those stressing the Machiavellian characteristics of mind-reading, manipulation and deception”; instead, “individuals capable of inventing new solutions to ecological challenges, or exploiting the discoveries of inventions of others, may have had a selective advantage over less able conspecifics, which generated selection for those brain regions that facilitate complex technical and social behavior.” This is clearly a conclusion consistent with the cultural intellect/brain hypothesis.

Figure 1.2 Social learning and encephalization in primates. Frequency of social learning in the survey of Reader and Laland (2002) is plotted against executive brain ratio (see text for further explanation). Labels refer to three species with complex cultures discussed extensively in the text.

Note that three species are picked out with labels in Figure 1.2 – chimpanzees, orangutans, and capuchin monkeys. These three are particularly relevant to the hypothesis under discussion here. As we have already seen, the two ape species have been described as exhibiting the most complex cultures known amongst animals, and their brains are large in both absolute terms and in relation to their body size, as well as on other measures like that shown in Figure 1.2. Among monkeys, the capuchins have offered evidence of the most complex cultures (see Whiten & van Schaik, 2007) and correcting for body size, they are the largest-brained monkeys.

Finally, there is evidence for a link between such complex cultures and cognition in the form of the social learning capacities exhibited. Whiten and van Schaik (2007) review evidence that apes show the most well-formed imitation, which extends to copying the sequential structure of actions (Whiten, 1998); rationality in copying, expressed in selectivity of copying in relation to both physical causation (Horner & Whiten, 2005) and intentional actions (Buttelmann, Carpenter, Call, & Tomasello, 2007; Tomasello & Carpenter, 2005); and recognition of the act of imitation itself, as in learning to “do-as-I-do” (Custance, Whiten, & Bard, 1995). Burkart, Schubiger, and van Schaik (2017) propose, further, that enhanced cultural intelligence also selects for and indeed explains rises in general intelligence, because of the expanded opportunities it creates for exploration of new potentials in an animal's niche, perhaps consistent with the results of findings on cultural and general intelligence such as those of Reader et al. (2011) noted earlier.

The Cultural Intelligence Hypothesis and the Vygotskian Intelligence Hypothesis

The cultural inheritance hypothesis discussed earlier was developed to explain variance among primates and the cultural richness of great apes in particular. In 2007, Moll and Tomasello focused instead on our own species and offered what they described as a “Vygotskian intelligence hypothesis,” which represents a human-focused version of the cultural intelligence hypothesis. Vygotsky's name was an apt one to choose for a label to distinguish this version from the more general, primate-wide one that Whiten and van Schaik described in the same-themed journal issue (“Social Intelligence: From Brain to Culture”; Emery, Clayton, & Frith, 2007), because as Moll and Tomasello's abstract explained, “Nicholas Humphrey's social