M. A. Hofman and D. Falk (Eds.)Progress in Brain Research, Vol. 195ISSN: 0079-6123Copyright � 2012 Elsevier B.V. All rights reserved.

CHAPTER 11

Human brain evolution writ large and small

Chet C. Sherwood*,{, Amy L. Bauernfeind{, Serena Bianchi{, Mary Ann Raghanti{

and Patrick R. Hof},}

{ Department of Anthropology, The George Washington University, Washington, DC, USA{ Department of Anthropology and School of Biomedical Sciences, Kent State University, Kent, OH, USA

} Fishberg Department of Neuroscience and Friedman Brain Institute,Mount Sinai School of Medicine, New York, NY, USA

} New York Consortium in Evolutionary Primatology, New York, NY, USA

Abstract: Human evolution was marked by an extraordinary increase in total brain size relative to bodysize. While it is certain that increased encephalization is an important factor contributing to the originof our species-specific cognitive abilities, it is difficult to disentangle which aspects of humanneural structure and function are correlated by-products of brain size expansion from those that arespecifically related to particular psychological specializations, such as language and enhanced“mentalizing” abilities. In this chapter, we review evidence from allometric scaling studiesdemonstrating that much of human neocortical organization can be understood as a product of brainenlargement. Defining extra-allometric specializations in humans is often hampered by a severe lack ofcomparative data from the same neuroanatomical variables across a broad range of primates. Whenpossible, we highlight evidence for features of human neocortical architecture and function that cannotbe easily explained as correlates of brain size and, hence, might be more directly associated with theevolution of uniquely human cognitive capacities.

Keywords: pyramidal neuron; cortical area; chimpanzee; great ape.

Human brain evolution writ large

The most obvious and distinctive evolutionaryspecialization of the modern human brain is its

*Corresponding author.Tel.: þ1-202-994-6346; Fax: þ1-202-994-6097E-mail: sherwood@gwu.edu

237DOI: 10.1016/B978-0-444-53860-4.00011-8

exceptionally large size. Although elephants andwhales have larger brains than humans, allometricscaling analyses have demonstrated that humansare the most encephalized of all mammals(Jerison, 1973; Martin and Harvey, 1985), with abrain that is more than three times larger thanwould be expected for a primate at the same bodymass (Holloway, 1979). This disproportionate

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growth of the brain in the human lineage is a rel-atively recent phenomenon, having increased dra-matically in the past 2.5 million years (Falk et al.,2000; Holloway et al., 2004). Although it is appar-ent that large brain size is a hallmark of humancognitive and cultural evolution, consensus islacking on the selection pressures drivingencephalization. Among the hypotheses put for-ward, it has been proposed that the complexityof social interaction, with a greater focus on coop-eration and learning from others (Boyd et al.,2011), as well as deception (Byrne and Whiten,1988), might have played a role.

While difficult to test, these hypothesizedcauses of encephalization are appealing becausethey attempt to explain the evolutionary benefitsassociated with such a prominent feature ofhuman neuroanatomy. Given the high energeticcosts of growing and maintaining neural tissue(Aiello and Wheeler, 1995; Chugani and Phelps,1986), it is reasonable to conclude that there mustbe decisive fitness benefits associated withincreased investment in brain mass beyond whatis minimally necessary for a given body size.Indeed, it has been demonstrated across taxa thatthere is a trade-off between relative brain massand other metabolically expensive tissues, aswell as the extent and timing of life historystages (Barrickman et al., 2008; Barton andCapellini, 2011; Deaner et al., 2002). Some haveproposed that encephalization (Jerison, 1973) orgreater total numbers of neurons (Herculano-Houzel, 2011) can be taken as a satisfactory,or singular, explanation for our cognitive cap-acities. Among primates, correlations have beenfound between relative brain size and anenormously diverse range of variables, includingexercise capacity (Raichlen and Gordon, 2011),the total amount of visual input as measured bythe size of the optic canal (Kirk, 2006), the extentof stereoscopy as indicated by the degree oforbital convergence (Barton, 2004), behavioralinnovation (Reader and Laland, 2002), sociality(Shultz and Dunbar, 2010a), and executivefunction (Shultz and Dunbar, 2010b). The adage,

“a theory that explains everything really explainsnothing” seems apt.

To some extent, explaining humancognitive uniqueness as merely a by-product ofencephalization, absolute brain size, or total num-bers of neurons reflects the infancy of studies inevolutionary neuroscience. If the goal is to under-stand the distinctive neural bases of the specificbehavioral abilities that are unique to humans,then how can any unitary variable explain sucha multifaceted suite of characteristics? Althoughstill a source of debate, there appears to be agrowing consensus that human cognition is mostunique in (1) the representational understandingof one’s own and other’s mental states, such asbeliefs, desires, and goals—that is, “theory ofmind” or “mentalizing”—and (2) syntacticallyordered symbolic communication in the form oflanguage (Hauser et al., 2002; Herrmann et al.,2007; Suddendorf et al., 2009). Even if brainsize can be understood as a major contributorto human cognitive uniqueness in these respects,it would still be necessary to learn more abouthow this single large variable translates tosmaller-scale differences that can be interpretedin terms of the development of connectivity,the integration and signaling of neurons, and theflow of information within the central nervoussystem. Further, advances from modern behav-ioral neuroscience and clinical neuropsychologyshow that dramatic differences in behavior,including social cognition and language, can bemediated by subtle microstructural and molecularchanges in brain organization (Arnold andBreedlove, 1985; Craig and Halton, 2009;Donaldson and Young, 2008; Robinson andBecker, 1986; Rosenzweig and Bennett, 1996),most often in the absence of any major differencein brain size.

At present, however, we have only a rudimen-tary understanding of the anatomical, functional,and energetic consequences of increased brainsize or encephalization in human evolution. Inlarge part, this is because only a few studies haveyet probed the differences between human brains

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and those of our close relatives, the great apes, inany detail. Consequently, many questions remainunanswered. For example, the extent to whichparticular modifications of neuronal morphologyand cell type distributions regularly scale up withincreases in brain size is poorly known; it isunclear whether all regions of the cerebral cortextend to increase in size at the same rate, or ifthere are particular areas that grow dispropor-tionately in correlation with brain size evolution;and it has not been determined how the connec-tivity of the cerebral cortex varies with brain size.While theoretical models exist to predict some ofthese scaling regularities across mammals (Kaas,2000; Striedter, 2005), the absence of sufficientcomparative data from hominoid primates pre-cludes clear assessment of whether human neuralorganization is largely determined by increasedbrain size, or alternatively, whether certainfeatures have emerged as departures from allo-metric expectations.Within this framework, we will discuss changes

in neocortical architecture in the evolution of thehuman brain. Specifically, we will review evi-dence for microstructural modifications of neo-cortical structure as reflected in cellulardistributions and neuronal morphology, and wewill consider their implications for energetics.Other excellent recent reviews discuss the allome-tric scaling of larger anatomical components ofthe brains among humans and other primates(Rilling, 2006; Schoenemann, 2006).

Scaling regularities and the human brain writsmall: Cellular distributions and morphology

One way of exploring how the human brain differsfrom other primates is to determine whetherfeatures of neocortical architecture deviate frompredictions derived from other smaller-brainedprimates, with the aim of identifying scalingregularities and evolutionary specializations (deSousa et al., 2010a; Rilling, 2006; Rilling and Insel,

1999b; Rilling and Seligman, 2002; Semendeferiand Damasio, 2000; Semendeferi et al., 1998,2001, 2002; Sharma et al., 2010; Sherwood et al.,2004, 2005a,b, 2006, 2007, 2010). In many ways,after taking overall brain size into account, com-parative evidence indicates that human neuro-anatomy is not unexpected. For example, it hasbeen shown that the total number of neurons inthe neocortex of humans closely matchesexpectations for a primate of the same brain size(Azevedo et al., 2009), that total neocortical whitematter and corpus callosum size are predictedby scaling (Bush and Allman, 2003; Rilling andInsel, 1999a), and that the frontal cortex ofhumans is not any larger than expected for brainsize (Bush and Allman, 2004; Semendeferi et al.,2002). Human neocortical architecture at thehistological level may also be examined fromthe perspective of allometric scaling. For example,the ratio of glial cells to neurons and theproportion of different subtypes of inhibitoryGABAergic interneurons in the dorsolateralprefrontal cortex (Brodmann’s area 9) of humanshave been shown to be explained by scalingpredictions (Sherwood et al., 2006, 2010). Thus,at present, scaling exponents have been calculatedfor a number of macro- and microscopic neocorti-cal variables, including neuron number anddensity, cortical thickness and surface area, whitematter volume, number of brain areas, numberof synapses per neurons, synaptic density, cellsoma size, and axon diameter (for review seeChangizi, 2001). Accordingly, many anatomicalcharacteristics of the human brain are likely tobe closely intertwined with an increase in overallsize. Table 1 summarizes results from severalstudies that have examined whether human neu-roanatomical structure is predicted by allometricscaling equations derived from smaller-brainedprimates.

While scaling regularities may reflect underly-ing biophysical, computational, or biochemicallaws that operate to maintain functional equiva-lence across variation in brain size (as is probablythe case for increases in white matter and

Table 1. Percent difference from allometric predictions for various neuroanatomical variables in humans

Variable

Percentdifferencefromallometricprediction

Independentvariableused in theprediction

Nonhumanspecies usedin thepredictionequation

Humansamplesize Data source

Volumes of structuresNeocortex (gray and white matter) þ9% Brain Anthropoids n¼6 Rilling (2006), data from Rilling and Insel

(1999b)Frontopolar cortex (area 10) þ6% Brain Hominoids n¼1 Holloway (2002), data from Semendeferi et al.

(2001)Primary visual cortex (area 17) �121% Brain Primates n¼1 Holloway (2002), data from Stephan et al. (1981)Hippocampus �6% Brain Primates n¼1 Holloway (2002), data from Stephan et al. (1981)Striatum �69% Brain Primates n¼1 Holloway (2002), data from Stephan et al. (1981)Thalamus �39% Brain Primates n¼1 Holloway (2002), data from Stephan et al. (1981)Lateral geniculate nucleus �144% Brain Primates n¼1 Holloway (2002), data from Stephan et al. (1981)Cerebellum �20% Brain Anthropoids n¼6 Rilling (2006), data from Rilling and Insel

(1999b)Midbrain �14% Brain Primates n¼1 Holloway (2002), data from Stephan et al. (1981)Medulla �74% Brain Primates n¼1 Holloway (2002), data from Stephan et al. (1981)Trigeminal motor nucleus �17% Medulla Primates n¼5 Sherwood et al. (2005a)Facial motor nucleus þ3% Medulla Primates n¼5 Sherwood et al. (2005a)Hypoglossal nucleus þ24% Medulla Haplorhines n¼4 Sherwood et al. (2005a)

Cellular organizationGlia-neuron ratio in DLPFC (area 9) �5% Brain mass Anthropoids n¼6 Sherwood et al. (2006)CB-ir interneuron density in DLPFC(area 9)

�40% Total neurondensity

Anthropoids n¼6 Sherwood et al. (2010)

CR-ir interneuron density in DLPFC(area 9)

�35% Total neurondensity

Anthropoids n¼6 Sherwood et al. (2010)

PV-ir neuron density in DLPFC (area 9) �43% Total neurondensity

Anthropoids n¼6 Sherwood et al. (2010)

Number of TH-ir neurons in locuscoeruleus

þ3% Medulla vol Catarrhines n¼4 Sharma et al. (2010)�126% Neocortex vol

Number of ChAT-ir neurons in nbM �110% Brain mass Anthropoids n¼2 Raghanti et al. (2011b)�104% Neocortex vol

DLPFC, dorsolateral prefrontal cortex; CB, calbindin; CR, calretinin; PV, parvalbumin; ChAT, choline acetyltransferase; ir, immunoreactive; nbM, nucleus basalis of Meynert.All variables represent volumes unless otherwise indicated. All percent differences between observed and predicted values are based on contemporary species data, not independent co-ntrasts. We include percent differences only from studies where this value was calculated and reported. Other scaling analyses have also examined whether humans are within the 95%prediction intervals generated from nonhuman data, but do not calculate a percent difference between the observed and predicted values. We excluded those studies from this table.

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glia–neuron ratios), deviations from scalingpredictions provide strong evidence for particularevolutionary specializations, as has been shownfor the reduction of primary visual cortex(de Sousa et al., 2010a) and the expansion of thetemporal lobe (Rilling and Seligman, 2002).With regard to scaling regularities and evolu-

tionary specializations, pyramidal cell structuredeserves particular attention. The excitatory pyra-midal cells constitute approximately 70% of theneurons of the neocortex, with variation amongregions and species. Morphologically, they arecharacterized by a triangular-shaped soma, anaxon for long-distance projection, one apicaldendrite extending toward the pial surface, anda skirt of dendritic arbors that sample inputs fromadjacent cells. Since the early observations byRamon y Cajal (1909), it had become apparentthat the morphology of pyramidal cells variesacross species, with the greatest degree of varia-tion being observed in the structure of the den-dritic arbors. To a certain extent, this variationmay be explained by scaling with body and brainsize (Purves, 1988; Wittenberg and Wang, 2007).As brains become larger, neuron density isreduced and greater dendritic arbors may be

(a) (b)

Fig. 1. Morphology of layer III pyramidal neurons in a human and aa neuron from primary motor cortex (area 4) in a human. (b) Trachuman individual as in (a). (c) Photomicrograph of a neuron in fnote the greater extent of dendritic branching in the region of theTracings of human neurons modified from Jacobs et al. (2001). Scal

needed to maintain connections with neighboringcells (Purves, 1988). While scaling exponents havebeen proposed for neuronal features such as cellbody size and axon diameter (Changizi, 2001),less is known about the scaling properties ofdendrites.

In fact, recent studies examining dendritic mor-phology across different cortical areas indicatethat pyramidal cell size may depend more onregional specializations than solely on brain size(Elston et al., 2001). In particular, it has beenshown that some features of dendrites (i.e., den-dritic spine density), but not others (i.e.,branching patterns, cell size, and total spine num-ber), correlate with overall brain size (Elstonet al., 2001). Moreover, examination of regionaldifferences in the pyramidal cell phenotype ofhumans and nonhuman primates has revealedsubstantial variation across cortical areas, withpeaks of branching complexity and spine densitytypically observed in the prefrontal region (Fig. 1;Elston, 2000; Elston et al., 2001; Jacobs et al.,2001). As greater dendritic branching and higherspine densities allow sampling and integration ofa larger number of inputs from neighboring cells,these regional differences may reflect functional

(c)

chimpanzee as revealed by Golgi impregnation. (a) Tracing ofing of a neuron from frontopolar cortex (area 10) in the samerontopolar cortex (area 10) of a chimpanzee. In the human,prefrontal cortex as compared to the primary motor cortex.e bar¼100mm.

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differences in neuronal computational power(Elston, 2000; Elston et al., 2001; Jacobs et al.,2001). Interestingly, when compared to macaquemonkeys, the closest human relative yet exam-ined for comparative studies of pyramidal mor-phology, the prefrontal cortex of humansexhibits a greater degree of branching complexityas well as spine density and total spine number(Elston et al., 2001, 2006). By contrast, pyramidalneurons of the primary visual cortex do not dem-onstrate as much species-specific variation amongprimates (Elston et al., 2006). Comparative stud-ies of neuropil in the neocortical gray matter(which is primarily occupied by dendrites, axon,and synapses) across hominoid primates alsoshow increased neuropil selectively in the fronto-polar cortex of humans (Semendeferi et al., 2011).Taken together, these data support the suggestionthat increased connectivity within the prefrontalcortex is an evolutionary specialization of thehuman neocortex (Elston, 2003). Because thereis not a significant correlation between the frac-tion of neuropil in the neocortex (as measuredin areas 4, 10, 13, 17, and 18) and brain size inhominoids (de Sousa et al., 2010b; Sherwoodand Hof, 2007), the evidence for increased con-nectivity in the human prefrontal cortex may bean evolutionary change that cannot be accountedfor by models of scaling.

One possibility that needs further testing, how-ever, is whether regional differences in dendriticmorphology straightforwardly reflect variation inneuronal density and neuropil fraction acrosscortical areas. As shown by a recent study ofgalagos, macaques, and baboons, neuronal den-sity varies up to five times within species, withthe highest density being observed in the primaryvisual cortex (Collins et al., 2010). Moreover,interpreting the functional implications of struc-tural differences may be further complicated bythe fact that, although cell morphology does notcorrelate with cortical area size, increasingor decreasing the dimension of neurons mayhave different impacts on small or large areas(Kaas, 2000).

The neuroanatomy of cognitive specializations:Comparing cortical area size andneurotransmission between humans and apes

In addition to investigations of scaling regularitiesthat might account for the evolution of humanbrain organization, other analyses that make thenarrow comparison of neocortical areas betweenhumans and our close relatives, the great apes,also provide important insight. Although suchcomparison would ideally incorporate data froma greater number of primate species to examinebrain size-related correlations, this is not alwayspractical. Nonetheless, these studies provide anessential step to locate changes in the brain whichmight relate to the recently evolved cognitivespecializations of humans by focusing on particu-lar cortical areas that are known to be involvedwith language and cognition. Broca’s area andWernicke’s area in the left hemisphere, for exam-ple, are principal nodes in a network that isstrongly activated during language processing(Friederici et al., 2006). Regions of the medialprefrontal cortex and along the posterior superiortemporal sulcus have been consistently found tobe involved in “theory of mind” tasks (Saxe,2006). Identifiable homologues exist in otherprimates for all the basic circuitry that isemployed for language function and “theory ofmind” in humans (Petrides and Pandya, 1994,2002; Petrides et al., 2005; Preuss and Goldman-Rakic, 1991a,b). Therefore, understanding theneural basis for the origin of these functionsrequires examining how evolution has modifiedthese regions or their connections in humans.

One important characteristic of the functionalcontrol of language in humans is that it is stronglylateralized to the left hemisphere in most people(Toga and Thompson, 2003). This functionaldominance is associated with certain anatomicalasymmetries, such as an increased size of theplanum temporale on the left (Geschwind andLevitsky, 1968; Toga and Thompson, 2003). Toexamine the coevolution of the brain and lan-guage, Broca’s area (area 44 and area 45) and

Table 2. Comparison of fold-differences in the sizes ofneocortical areas between humans and chimpanzees

Structure

Humanversuschimpanzeefold-difference Data source

Brain 3.6 Holloway (1996)Neocortical gray 4.0 Rilling and Insel (1999b)Area 44 (left) 6.6 Amunts et al. (1999),

Schenker et al. (2010)Area 10 (right) 6.3 Semendeferi et al. (2001)Area 45 (left) 6.0 Amunts et al. (1999),

Schenker et al. (2010)Area 45 (right) 5.0 Amunts et al. (1999),

Schenker et al. 2010Area Tpt (left) 4.2 Galaburda and Sanides

(1980), Spocter et al. (2010)Area 44 (right) 4.1 Amunts et al. (1999),

Schenker et al. (2010)Area 6(hemisphereunknown)

2.5 Glezer 1958a

Area Tpt (right) 2.0 Galaburda and Sanides(1980), Spocter et al. (2010)

Area 17 (left) 1.8 de Sousa et al. (2010a)Area 13 (right) 1.4 Semendeferi et al. (1998)Area 4(hemisphereunknown)

0.8 Glezer (1958)a

aAll comparisons are based on volumes, except for the data fromGlezer (1958) which provide surface area measurements.

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Wernicke’s area (the posterior part of area 22;also called area Tpt) in chimpanzees have beenstudied using magnetic resonance imaging, histo-logical data, and associated behavioral informa-tion (Hopkins et al., 2008, 2010; Schenker et al.,2010; Sherwood et al., 2003a, 2010; Spocteret al., 2010). Using cytoarchitecture to define cor-tical areas, it has been shown that humans andchimpanzees are similar in showing a popula-tion-level bias toward leftward asymmetry ofWernicke’s area (area Tpt) volume (Spocteret al., 2010). By contrast, Broca’s area (area 44and area 45) of chimpanzees does not displayhuman-like lateralization (Schenker et al., 2010).In addition, when the size of these cortical areasis compared between humans and chimpanzees,it is evident that Wernicke’s area has increasedin size only proportionately with overall neocor-tex in human evolution, whereas Broca’s areahas increased in size to a substantially greaterextent (Table 2; Fig. 2). In fact, of the corticalareas measured for their volume in both humansand chimpanzees so far, area 44 in the left hemi-sphere displays the greatest enlargement inhumans. These results allow us to speculate thatthe uniqueness of human language function maydepend more critically on modifications to theprocessing capacity of the inferior frontal cortexfor syntax, lexical retrieval, and other hierar-chically ordered information but is built uponmore ancestral functions of the superior temporalcortex (area Tpt) in phonological processing.At present, only a small number of regions in

both humans and chimpanzees have beenmeasured for their size based on cytoarchitecture(Table 2). Interestingly, from the cortical areasthat have been compared, a similar pattern of dis-proportionate regional expansion seems to alsocharacterize differences in the size of corticalareas between human and macaques, as well asthe heterogeneous growth of the cerebral cortexthat occurs over the course of postnatal develop-ment in humans (Hill et al., 2010; Fig. 2). Thissuggests that the difference in cortical area sizesthat evolved in humans after branching from the

rest of the ape lineage may be an extension ofcommon scaling trends across primate phylogenythat are mediated by conserved developmentalmechanisms (see Chapter 4). More detailed par-cellations and volumetric comparisons of the tem-poral cortex and inferior parietal cortex in apesare warranted and may provide insight into addi-tional cortical modifications that have contributedto the evolution of human language and othercognitive functions.

In addition to clarifying which regional sizedifferences appear to be most significant inhuman brain evolution, recent research has alsorevealed human-specific changes to the micro-structure of connections and distributions of

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Fig. 2. Maps illustrating the disproportionate expansion of the neocortex in human evolution and development. (a) Fold-differencein size of cortical areas between humans and chimpanzees. Values were taken from Table 1 and overlaid on Brodmann’s map of thecerebral cortex. All data are from the left hemisphere except where only right hemisphere or unknown were available. (b) Fold-difference in surface area of cerebral cortex between humans and macaque monkeys expressed relative to the total neocorticalsize difference between species, modified from Hill et al. (2010). Right hemisphere is shown. (c) Fold-difference in surface areaof cerebral cortex between neonatal and adult humans, modified from Hill et al. (2010). Right hemisphere is shown.

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neuron types. The supply of neurotransmitterafferents to the cerebral cortex, originating fromsubcortical neuron populations located in thebasal forebrain and brainstem, plays a key rolein the balance of excitation and inhibition under-lying information processing in the neocortex.These neurotransmitters (e.g., dopamine, norepi-nephrine, acetylcholine, and serotonin) have dif-fuse termination zones and have long-termeffects on the processing characteristics of post-synaptic cells by interacting with multiple

G-protein-linked receptor subtypes. Severe psy-chiatric disturbances in human patients have beenshown to correlate with abnormalities in the syn-thesis, transport, and metabolism of these neu-romodulatory systems (for review see Briandet al., 2007). By using immunohistochemical sta-ining to identify individual axon fibers in combi-nation with stereologic quantification, it hasbeen shown that the extrinsic supply of serotoner-gic, dopaminergic, and cholinergic axons to theprefrontal cortex has been selectively altered in

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Fig. 3. Tracings of axon fibers immunoreactive for tyrosinehydroxylase (TH), a marker for dopamine, serotonintransporter (SERT), a marker for serotonin, and cholineacetyltransferase (ChAT), a marker for acetylcholine, indorsolateral prefrontal cortex (area 9) of macaque monkeys,chimpanzees, and humans. Images modified from Raghantiet al. (2008a–c). Scale bar¼250mm.

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humans and chimpanzees as compared tomacaque monkeys (Raghanti et al., 2008a–c). Inboth humans and chimpanzees, a greater axonallength density of fibers that are immunoreactivefor these neurotransmitters innervates prefrontalcortex (areas 9 and 32) in a layer- and species-specific manner (Fig. 3). Because these neuro-transmitter systems are involved in behavioralflexibility, attention, and learning, it is temptingto speculate that this evolutionary shift mightcontribute to the some of the cognitive abilitiesthat are exclusively shared between ourselvesand the great apes, such as increased behavioralinhibition, enhanced attention to the gaze ofothers, greater social tolerance, diffusion of sociallearning through regional traditions, and a capac-ity for self-awareness (Barth et al., 2005; Beranand Evans, 2006; Boesch, 1993; Evans and Beran,2007a,b; Suddendorf and Whiten, 2001).Notably, comparative allometric scaling ana-

lyses have revealed that the subcortical neuronpopulations that provide neurotransmitter inner-vation to the prefrontal cortex do not show acorresponding relative increase in humans,despite the enlargement of human cerebral cor-tex. Surprisingly, for both the locus coeruleus(supplying norepinephrine) and the nucleusbasalis of Meynert (supplying acetylcholine), thehuman subcortical neuron populations actuallyare smaller than expected relative to brain sizeand neocortical volume in comparisons involvinglarge samples of nonhuman primates (Table 1;Raghanti et al., 2011b; Sharma et al., 2010).Taken together, these results indicate thatmodifications in the anatomy of these neurotrans-mitter systems in human evolution involvedalterations in terminal axon patterns, independentof correlated changes in numbers of neurons inthe basal forebrain nuclei themselves.Additional studies focusing on intrinsic sources

of neurotransmitters within the cortex have alsorevealed that there is a significant degree ofvariability in both the density and distribution ofcortical neurons immunoreactive for various

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neurotransmitters among primates. As with neu-rotransmitter-immunoreactive axons, thesepopulations of cortical neurons are also selec-tively targeted in human neuropathologies(Fukuda et al., 1999; Marui et al., 2003; Niheiand Kowall, 1993). Tyrosine hydroxylase-immu-noreactive neurons are found sparsely in the cere-bral cortex of several mammals; however, humansare the only species that possess these neuronsdistributed throughout the entire cerebral cortex,with the highest densities occurring in the dorso-lateral prefrontal cortex and anterior cingulatecortex (Benavides-Piccione and DeFelipe, 2007;Kohler et al., 1983). However, while present inthe siamang, these cells are conspicuously andconsistently absent among the great apes (chim-panzee, bonobo, gorilla, and orangutan),indicating that this neurochemical phenotype hasindependently evolved in humans (Raghantiet al., 2009). It is unclear why this biochemicalexpression pattern has reemerged in humans,after having been previously lost from the greatape lineage.

Neuropeptide Y-immunoreactive cortical cellsare another class of neurons that are present inhuman and nonhuman primates, including thegreat apes. As with the neuron populationsexpressing tyrosine hydroxylase, there are spe-cies-specific patterns of variation, but quantitativeanalyses do not reveal anything unique about theirdensities or distributions in humans (Raghantiet al., 2011a).

Fig. 4. von Economo neurons (VENs) as revealed by Nisslstaining from layer V of anterior cingulate cortex in greatapes and humans. (a) human, (b) chimpanzee, (c) bonobo,and (d) gorilla. Scale bar¼100mm.

The emergence of neuronal specializations forsocial cognition: VENs

Another interesting feature of the hominoid cere-bral cortex is the presence of VENs (Fig. 4;Allman et al., 2010; Nimchinsky et al., 1995,1999; Seeley et al., 2012; von Economo, 1926).VENs are projection neurons located principallyin layer V of the anterior cingulate andfrontoinsular cortices and, in more limited num-bers, in the superior frontal cortex (area 9;

Fajardo et al., 2008). Current data suggest thatVENs represent a specialized neuronal type witha characteristic morphology that evolved onlyin a restricted number of species, most likely froma population of pyramidal neurons present inancestral mammals (Butti and Hof, 2010; Buttiet al., 2011). VENs, which are especially numer-ous in the hominoid lineage, are particularly

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vulnerable in neuropsychiatric conditions inwhich social and emotional skills are characteristi-cally affected. Moreover, recent evidence on theneurochemical profile, morphologic features, andlaminar and regional distribution of VENssuggests that the functional specificity of this neu-ronal population could be critically involved inautonomic regulation.VENs are generally larger than layer V pyrami-

dal neurons and their somatic volume is stronglycorrelated with the encephalization quotient,unlike that of pyramidal cells (Nimchinsky et al.,1999). In adults, VENs are more abundant inthe right hemisphere (Allman et al., 2010), possi-bly reflecting asymmetries in the organization ofafferents from the autonomic nervous system(Craig, 2005). Their densities, however, are lowin all species in which they occur, representingonly a few percent of the total number of pyrami-dal neurons (Allman et al., 2010). VENs have beenshown to be enriched in nonphosphorylatedepitopes of neurofilament proteins, similar to largepyramidal neurons (Nimchinsky et al., 1995), andto express several markers such as dopamine D3receptor, vasopressin 1a receptor, activating tran-scription factor 3, interleukin-4 receptor a chain,neuromedin B, gastrin-releasing peptide, and dis-rupted on schizophrenia-1, in higher levels thanneighboring pyramidal cells (Allman et al., 2010,2011; Stimpson et al., 2011).The function of VENs remains poorly under-

stood. Nonetheless, it is interesting that VENsare affected in a number of neuropsychiatricillnesses that present impairments of social andcommunication skills, emotionality, morality, andself-awareness. They are severely lost in thebehavioral variant of frontotemporal dementiaand in agenesis of the corpus callosum (Kaufmanet al., 2008; Kim et al., 2012; Seeley et al., 2006),exhibit decreased densities in schizophrenia(Brüne et al., 2010), and show abnormal corticaldistribution and increased number in young chil-dren with autism (Santos et al., 2011), as well asincreased densities in suicide victims with psycho-sis (Brüne et al., 2011). The specific localization

of VENs in cortical areas in which informationon the physiological state of the body is used toguide behavioral choices (Craig, 2009), theirinvolvement in diseases in which social conductis dramatically affected, their richness in markerssuch as bombesin-related peptides, and their posi-tion in a layer characteristically sending subcorti-cal projections (Brodal, 1978; Glickstein et al.,1985) suggest a role for VENs in cortico-auto-nomic pathways, supporting the original intuitionof von Economo (1926) on the involvement ofVENs in autonomic function. The fact that theyhave also independently emerged in other large-brained social mammals, such as elephants andwhales (Butti et al., 2009; Hakeem et al., 2009;Hof and Van der Gucht, 2007), strongly suggeststhat their development is mediated bymechanisms related to brain size scaling.

Energetics and microstructural changes inhuman neocortical evolution

Kleiber’s law states that the mass-specific ener-getic cost of an organ declines with increases intotal mass (Kleiber, 1961). Accordingly, becausethe energy required for the maintenance anddevelopment of neural tissue is correlated withthe overall mass of the brain, greater metabolicefficiency of the human brain would be predictedbecause of its large size. However, contrary to thisexpectation, recent comparative studies of geneexpression indicate that the human cerebral cor-tex is characterized by an upregulation of RNAtranscripts involved in energy metabolism com-pared to the cortex of great apes (Caceres et al.,2003; Fu et al., 2011; Khaitovich et al., 2008; Pre-uss et al., 2004; Uddin et al., 2004). Moreover, theobservation that genes coding for synaptic func-tion are also highly expressed in human samplessuggests that the human neocortex may be moremetabolically expensive as a way to support itsunderlying cytoarchitecture and greater demandfor synaptic signaling (Uddin et al., 2004).However, because these studies were performed

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with homogenates of tissue, it is still unknownwhich cellular and biochemical modifications areespecially responsible for the apparent increasedmass-specific metabolic demand of human neo-cortical tissue.

Studies have found that the metabolic expenseof the rodent brain is tightly correlated with neu-ral activity associated with the most prevalentexcitatory neurotransmitter in the brain, gluta-mate (Attwell and Laughlin, 2001; Sokoloff,1977). Among the most energetically expensiveaspects of neural activity are the depolarizationof a neuron’s membrane potential followingchemical stimulation at a synapse and presynapticneurotransmitter release and recycling (Lennie,2003). Together, these processes account for over60% of the cost of neural activity and localize themajority of metabolic expense to the excitatoryglutamatergic synapse (Raichle and Mintun,2006). If it is assumed that the primate brainallocates energy in the same proportions to neuralfunctions as the rodent brain, it would beexpected that cortical regions with a higher den-sity of excitatory synapses, or those regions moreconsistently stimulated by excitatory inputs,would be more energetically expensive to main-tain throughout adulthood. Thus, greater meta-bolic requirement may be predicted in regionssuch as in the human prefrontal cortex and otherassociation cortical areas, which have been shownto exhibit greater connectivity (Elston et al., 2006;Jacobs et al., 2001; Semendeferi et al., 2011).

Additionally, studies using radiolabeled glucoseto track energy uptake in the brain have foundevidence for a default mode network (DMN), agroup of regions including the medial prefrontaland medial parietal cortices that are active evenduring times of cognitive “rest” (Raichle andSnyder, 2007; Raichle et al., 2001). Although sim-ilar patterns and high levels of activity have beenfound during rest in chimpanzees (Rilling et al.,2007) and macaques (Vincent et al., 2007), recentstudies indicate that regions activated as part ofthe DMN in humans are the same regions thatfirst exhibit the pathophysiology unique to

Alzheimer’s disease, a uniquely human illness(Vaishnavi et al., 2010). If the consistently highlevels of activation in the DMN predisposehumans to neurological diseases not seen in otherprimates, a case for the uniqueness of neuralactivity and energy expenditure in the humanlineage is stronger than ever. Thus, human neuralconnectivity and the biochemical processesinvolved in energy metabolism may set humansapart from other primates in a manner not readilypredicted by brain size.

Conclusions

Only by examining the detailed architecture andfunction of the human neocortex in a comparativeperspective will it be possible ultimately touncover the neurobiological basis of humanbehavioral distinctiveness. It is to be expectedthat some modifications to neocortical organiza-tion will be consequences of overall brain-sizeexpansion. Others features, however, may proveto have emerged independent of encephalization.The complexity of the human mind, of course, isnot likely to be explained solely by either brainsize or by statistical residuals from allometric scal-ing equations. Rather, the human brain pheno-type is constructed dynamically in ontogenythrough the interaction of uniquely modifiedgenes that regulate neuronal proliferation (i.e.,the size of parts of the brain), cell migration(i.e., the histological organization of the brain),cell adhesion, and axon guidance (i.e., connectiv-ity), as well as the synthesis and turnover ofchemicals involved in signaling and energy utiliza-tion (Gilbert et al., 2005; Konopka andGeschwind, 2010). Many exciting discoverieshave already been made identifying genes thatcontrol these processes and which have unde-rgone adaptive evolution in human descent(Dorus et al., 2004; Enard et al., 2002; Evanset al., 2004; Konopka et al., 2009; McLean et al.,2011; Popesco et al., 2006; Uddin et al.,2008a,b). The complexity with which these gene

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networks are regulated through development andin response to environmental factors provides fur-ther opportunities for biocultural interactions toaffect the phenotype and function of modernhuman brains. We are only now scratching thesurface and beginning to reveal what makes thehuman brain phenotype truly special. This effortnecessitates interdisciplinary comparative ana-lyses involving a wide variety of molecular, histo-logical, and imaging techniques that include datafrom our closest kin, the great apes.

Acknowledgments

This work was supported by the National ScienceFoundation (BCS-0515484, BCS-0549117, BCS-0827531, BCS-0921079, DGE-0801634), theNational Institutes of Health (NS42867), and theJames S. McDonnell Foundation (22002078 toP. R. H. and C. C. S., and a Scholar Award inUnderstanding Human Cognition to C. C. S.).

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