Comparative Primate Neuroimaging: Insights Into Human Brain Evolution

Home , Altriciality, Primate

Review

Comparative primate neuroimaging:

insights into human brain evolution

1,2,3,4

James K. Rilling

Department of Anthropology, Emory University, Atlanta, GA 30322, USA

Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA 30322, USA

Yerkes National Primate Research Center, Emory University, Atlanta, GA 30322, USA

Center for Translational Social Neuroscience, Emory University, Atlanta, GA 30322, USA

Comparative neuroimaging can identify unique features We have extensive knowledge of rhesus macaque brain

of the human brain and teach us about human brain anatomy and physiology obtained through lesion studies,

evolution. Comparisons with chimpanzees, our closest single-cell electrophysiology, and tracer studies. Similar

living primate relative, are critical in this endeavor. detailed knowledge from humans and great apes is highly

Structural magnetic resonance imaging (MRI) has been desirable, but these invasive methods cannot be ethically

used to compare brain size development, brain structure applied in humans and great apes. Fortunately, the recent

proportions and brain aging. Positron emission tomog- advent of non-invasive neuroimaging techniques has

raphy (PET) imaging has been used to compare resting opened new possibilities for comparative studies (Box 2)

brain glucose metabolism. Functional MRI (fMRI) has [2].

been used to compare auditory and visual system path-

ways, as well as resting-state networks of connectivity. Structural MRI

Finally, diffusion-weighted imaging (DWI) has been used The earliest comparative neuroimaging studies utilized

to compare structural connectivity. Collectively, these structural MRI to compare the absolute and relative size

methods have revealed human brain specializations of brain structures across anthropoid primate species.

with respect to development, cortical organization, con- Similar studies had been conducted earlier using post-

nectivity, and aging. These ﬁndings inform our knowl- mortem brain specimens [6–8], but MRI offered the advan-

edge of the evolutionary changes responsible for the tage that data could be rapidly collected from living,

special features of the modern human mind. healthy, nonelderly adult subjects without sacriﬁcing ani-

mals or waiting for them to die. This facilitated collection of

The importance of comparative primate neuroimaging larger within-species sample sizes that permitted formal

In the quest for a scientiﬁc understanding of human na- statistical tests of between-species differences. Another

ture, no topic is more important than the evolution of the important advantage of MRI is that brain structure

special features of the human brain [1,2]. The fossil record volumes do not need to be corrected for shrinkage that

shows that brain size approximately tripled over the last occurs during the post-mortem ﬁxation process [9].

2.5 million years of human evolution [3]; however, the fossil Against the backdrop of evidence that brain structure

record cannot identify potential evolutionary changes to size could be accurately predicted from overall brain size

the internal organization of the brain [4]. To investigate across a broad sample of mammals [10], early MRI ﬁndings

this question, we must turn to the comparative study of the showed that human brains in fact deviated from predic-

brains of living primate species. If we can identify a tions derived from non-human anthropoid primates in

characteristic of the human brain that is not found in some important respects, and could not simply be consid-

the brain of any closely related primate species, then we ered scaled-up versions of typical non-human primate

can infer that the trait evolved in the hominin lineage (see brains [11]. In particular, relative to a hypothetical ‘typical’

Glossary) after we diverged from our common ancestor anthropoid primate of our brain size, humans have larger

with chimpanzees some 5–7 million years ago (mya). This

approach renders the study of chimpanzees crucial for

learning about human brain evolution: we cannot infer Glossary

that a trait uniquely evolved in the human lineage unless it

Allometry: study of how one part of an organism grows either in relation to the

is absent in modern chimpanzees (Box 1) [5]. whole organism or to some other part. Many allometric relationships are well

described by the equation Y = bX , where a is the allometry exponent. When

a = 1, the relationship is linear. When a > 1, increases in Y outpace increases in

Corresponding author: Rilling, J.K. ([email protected]).

X and the relationship is positively allometric. When a < 1, increases in Y do

Keywords: neuroimaging; evolution; comparative; human; chimpanzee.

not keep pace with increases in X and the relationship is negatively allometric.

1364-6613/$ – see front matter Hominin: living and extinct members of the human lineage after the split from

Homology: correspondence between species due to a common evolutionary

origin.

Voxel: the smallest volumetric element of a brain image, analogous to a pixel,

but with the added dimension of depth.

46 Trends in Cognitive Sciences, January 2014, Vol. 18, No. 1

Review Trends in Cognitive Sciences January 2014, Vol. 18, No. 1

Box 1. Primate phylogeny Box 2. Neuroimaging techniques

In taxonomic terms, primates are one of several orders in the MRI can be used to image either brain structure or brain function

mammalian class. The earliest primates appear in the fossil record using the same instrument. In MRI, the subject is positioned within

around 60 million years ago (mya), shortly after the dinosaurs the bore of a large magnet that exposes them to a strong magnetic

became extinct. The two primate suborders, anthropoids and field, which causes a small fraction of the protons in their body to

prosimians, diverged from each other early in primate evolution. orient in the direction of that magnetic field. If radiofrequency pulses

Modern day prosimians are generally believed to have retained are then applied at the precession frequency of these protons, they

more similarities with the earliest ancestral primates than anthro- are tipped out of alignment with the main magnetic field. The signal

poid primates have. Anthropoid primates include New World intensity of voxels in MRI images is related to the behavior of the

monkeys (from central and south America), Old World monkeys protons following this perturbation. This can be affected by (i) the

(from Africa and Asia), and the hominoids, which include lesser water and fat content of tissues, (ii) the direction of water diffusion,

apes (from Asia), great apes (from Africa and Asia), and humans. and (iii) the ratio of deoxygenated to oxygenated hemoglobin.

Among the hominoids, humans are most distantly related to the These variables can be used, respectively, to create images that

lesser apes, and most closely related to the African great apes. Our show (i) contrast between gray matter, white matter, and cere-

two closest living primate relatives are the chimpanzees and the brospinal fluid (structural images for morphometrics), (ii) images of

bonobos, both members of the genus Pan, with whom we shared a water diffusion (DWI images for measuring white matter integrity

common ancestor some 5–7 mya. Chimpanzees and bonobos are and tractography), and (iii) increases in blood flow in response to

believed to have shared their last common ancestor approximately stimuli (fMRI).

1–2 mya. To conclude that a neurobiological trait is uniquely human, PET involves the injection or consumption of radioactive com-

we would ideally show that it is not present in any other living pounds, followed by detection of the distribution and concentration

species. However, given the practical difficulty of doing so, the of radioactivity in the brain with an instrument known as a PET

minimum criterion for suggesting that a trait uniquely evolved in scanner. PET can be used to measure cerebral glucose metabolism

humans is to establish its absence in our closest living relative, and cerebral blood flow, both known correlates of synaptic activity

either chimpanzees or bonobos, as well as in some more distantly in the brain. PET can also be used to image the density and

related primate species that serves as an outgroup, to determine distribution of neurotransmitter receptors and transporters in the

whether a difference between chimpanzees and humans represents brain. This involves injection of a radioactively labeled molecule that

a chimpanzee or a human specialization. However, this more limited binds to a specific receptor (i.e., a ligand), followed by detection of

approach leaves open the possibility of parallel evolution of the the location and intensity of the radioactivity. A great deal of

human trait in a particular primate or even non-primate species. research is devoted to synthesizing radiolabeled ligands that have

the appropriate binding characteristics in terms of their specificity

and affinity for their receptors. Ligands are currently available for

several subtypes of dopamine and serotonin receptors, as well as

neocortices [9], temporal lobe volume [12,13], and estimat- their transporters. The number of available ligands will continue to

ed prefrontal white matter volume [14], as well as greater grow in the future.

All of these techniques are available for comparative neuroima-

gyriﬁcation (cortical folding) in prefrontal cortex [9] and

ging studies that teach us about human brain evolution.

more gyral white matter in the frontal and temporal lobes

[15] (Box 3). When combined with older post-mortem data

showing that primary sensory and motor areas are smaller Comparative structural neuroimaging studies have also

than expected in human brains [16–18], these MRI data led demonstrated that certain brain asymmetries originally

to the summary prediction that one special feature of the presumed to support uniquely human characteristics such

human brain is that it has relatively more association as language and (supposedly) handedness are in fact also

cortex compared with other primate brains [19]. present in great apes. For example, the surface area of the

As more sophisticated brain imaging software became planum temporale, a portion of Wernicke’s area known

available, it became possible to warp non-human primate since 1968 to be leftwardly asymmetric in humans [24],

cortical surfaces into the shape of the human cortex using a was more recently shown by MRI to be leftwardly asym-

set of suspected anatomical and functional homologies as metric in great apes as well [25,26]. The same is true of the

landmarks to constrain the registration. As predicted, knob area of the motor cortex responsible for motor skill of

macaque-to-human brain warping showed the largest rel- the hand. Population-level leftward asymmetries are found

ative expansion in human prefrontal, parietal, and tempo- in both humans and chimpanzees [27]. Subsequent MRI

ral association cortex, and the least expansion in primary studies have linked various brain asymmetries in chim-

sensory and motor areas [20]. A chimpanzee-to-human panzees with handedness behavior [28–31]. Thus, neuro-

brain warping study based on a more limited set of homol- anatomical asymmetry and functional laterality are likely

ogies also showed selective expansion of human prefrontal to have preceded the evolutionary divergence of humans

and lateral temporal association cortices [21]. Association and chimpanzees, although these have subsequently be-

cortex is known to be less well-myelinated than primary come more pronounced in humans [32–34].

sensory and motor cortices [22]. A recent MRI study gen- Comparative structural neuroimaging has also in-

erated maps of cortical myelin content in humans and formed our knowledge of the evolution of human brain

chimpanzees. These maps show qualitatively that less development. The most obvious difference between human

well-myelinated association cortex occupies a larger pro- and non-human primate brains is absolute size. The aver-

3 3

portion of the cortical surface in humans compared with age human brain is 1330 cm , compared with 405 cm in

either chimpanzees or rhesus macaques (Figure 1) [23]. chimpanzees [3] and 88 cm in macaque monkeys [35].

Collectively, these ﬁndings suggest that compared with How do these pronounced differences in brain size develop?

other living primate species, relatively more of the human The traditional answer based on analyses of post-mortem

cerebral cortex is dedicated to conceptual and other forms specimens has been that human and non-human primate

of higher-order cognitive processing as opposed to percep- brains grow at similar rates in utero, but that whereas the

tual processing. growth rate of non-human primate brains slow at birth,

Review Trends in Cognitive Sciences January 2014, Vol. 18, No. 1

Box 3. Comparative morphometrics [39]. Recent structural MRI scans from a small sample of

chimpanzees echo earlier post-mortem ﬁndings [40] in

Brain structure sizes can be compared across species in a variety of

showing that human brain growth rates are twice those

ways, each of which provides different information. Most obviously,

we can compare the absolute size of brain structures across species. of chimpanzee brain during early infancy, with the further

For example, because the human brain is approximately three times insight that these species differences in postnatal brain

larger than the largest non-human primate brain, we expect that

growth are driven by white matter rather than gray matter

most if not all brain structures are absolutely larger in humans

development [41]. Thus, maturation of white matter con-

compared with non-human primates. This is generally true, but

nections during infancy may be fundamental to the devel-

there are rare exceptions, such as the olfactory bulbs which are

smaller in humans than in great apes [92]. So do humans have a opment of unique features of human cognition.

larger prefrontal cortex than other primate species? Yes, absolutely,

Structural MRI has also been used to compare brain

obviously, and tremendously. A second method of comparing brain

aging between humans and other primates. As in humans

structure sizes across species is to compare the ratio of the size of

[42–46], gray matter volume decreases with age in chim-

the brain structure to the size of the entire brain. This tells us the

relative importance of that structure in that brain. For example, panzees and rhesus monkeys [47,48]. Also like humans,

humans have a larger ratio of prefrontal cortex surface area to total chimpanzees show a trend for decreased white matter

neocortical surface area compared with other primates [93],

volume with age, but this decrease occurs proportionally

suggesting that the prefrontal cortex has more influence or

later in the chimpanzee lifespan than in humans, implying

importance in the human brain [94]. The third type of comparison

that there is more time for white matter atrophy before

involves a concept known as allometry, in which we ask whether

species differences in relative structure sizes (i.e., ratios) are death in humans compared with chimpanzees. This may be

predictable consequences of differences in brain size. That is, part of the explanation for increased human vulnerability

primate brains may predictably change proportions as they vary in

to neurodegenerative diseases.

size owing to developmental constraints on brain growth. Thus, for

example, humans may have a large ratio of prefrontal to total

continues at the prenatal for another

neocortical surface area because they are following an allometric

rule of brain growth in which increases in prefrontal cortex area Structural MRI studies of non-human primates were fol-

outpace increases in the size of the rest of the neocortex as primate lowed in time by PET studies that enabled measurement of

brains become larger. In this case, the large human ratio would not

brain function by injection of radioactive tracers that could

be surprising. Indeed, prefrontal cortex area does scale with positive

measure regional cerebral blood ﬂow or glucose metabo-

allometry on total neocortex area [93]. However, the human

lism. An early application relevant to human brain evolu-

prefrontal cortex is even larger than predicted by the non-human

primate allometry [94]. This important fact suggests that human tion was to ask whether listening to species-speciﬁc

brains violate a rule of brain growth. Departures from allometry are

vocalizations activated homologs of human language areas

generally interpreted as evidence of adaptations due to natural

in macaque monkeys [49]. Indeed, in a small sample of

selection. Thus, the available data suggest that the large size of the

macaque monkeys, blood ﬂow responses were more pro-

human prefrontal cortex is a unique, species-specific adaptation of

the human brain. One limitation of allometry is that the slope of the nounced for species-speciﬁc calls compared with non-bio-

regression line relating brain structure size to brain size can vary logical sounds within cortical area Tpt and the dorsal

depending on the taxa through which the line is fitted. Thus,

frontal operculum, presumed homologs of Wernicke’s

predictions based on data from apes might differ from those based

and Broca’s areas, respectively. Notably, however, these

only on anthropoid primates or the entire order [95]. Therefore,

activations were not leftwardly asymmetric as is typically

allometric data must be interpreted with caution.

found in humans. Furthermore, some evidence suggests

that area Tpt, rather than being exclusively involved in

human brain growth continues at the prenatal rate for language-speciﬁc processes, is involved in early auditory

another year postnatally [36,37]. A remarkable prenatal processing more generally [50].

brain imaging study provides further insight into this PET imaging has also been used to suggest that, like

question. Sakai et al. used three-dimensional ultrasonic humans [51], macaque monkeys have a default mode of

imaging of two living chimpanzee fetuses to describe the brain function that is active at rest and suppressed during

trajectory of brain growth in utero in comparison with an attention-demanding cognitive tasks [52]. Similar to

existing human sample [38]. Beginning at 16 weeks of humans, blood ﬂow is higher at rest within medial prefron-

gestation, human brains are already twice as large as tal and medial parietal areas than during working memory

chimpanzee brains. Afterwards, brain growth velocity sim- tasks.

ilarly increases in both species until 22 weeks of gestation, In humans, default-mode network areas also have high

after which time chimpanzee brain growth velocity slows levels of resting glucose metabolism. A study of resting-

whereas human brain growth velocity continues to in- state brain glucose metabolism in chimpanzees showed the

crease. As a result, newborn human brains (400 cm ) highest level of activity within areas that overlapped ex-

are already approximately 2.7 times larger than newborn tensively with the human default-mode network, including

chimpanzee brains (150 cm ) at birth. However, this medial prefrontal and medial and lateral parietal cortices

difference falls short of the greater than threefold differ- (Figure 2) [53]. A subsequent study has established that

ence in adult brain size, implying that additional develop- these areas are also deactivated by focused cognitive activ-

mental differences occur postnatally. Despite their much ity [54], as is true of the human and macaque default-mode

larger size, newborn human brains are at an earlier stage networks. Given evidence that the default mode network is

of development at birth than other primate brains are. For involved in internal thought processes and mental self-

example, newborn human brains are approximately 25– projection [55], these ﬁndings raise the prospect that simi-

30% of the adult size, whereas newborn chimpanzee and lar thought processes may be ongoing in chimpanzees and

macaque brains are closer to 40% and 50%, respectively macaque monkeys at rest. However, this conclusion is

Review Trends in Cognitive Sciences January 2014, Vol. 18, No. 1

(A) (C)

1x 32x

(B)

TRENDS in Cognitive Sciences

Figure 1. Human brains have relatively more association cortex compared to non-human primate brains. (A) The degree of macaque cortical expansion required to warp

macaque to human cerebral cortex (adapted from [20]). (B) Colored regions of chimpanzee cortex must be expanded when warping chimpanzee to human cerebral cortex

(adapted from [21]). (C) Cortical myelin maps in humans (top), chimpanzees (middle), and rhesus macaques (bottom), illustrating the relative amount of lightly myelinated

association cortex across species. More heavily myelinated primary cortices are in color, whereas lightly myelinated association cortex is in gray. Adapted, with permission

from Glasser, M. et al. (2011) Comparative mapping of cortical myelin content in humans, chimpanzees, and macaques using T1-weighted and T2-weighted MRI. Poster

presented at the Society for Neuroscience Annual Meeting, Washington, DC, November 12–16, 2011.

contingent on the functional similarity of these regions very strong animals, or training them to lie still while

across species, a proposition that has yet to be fully inves- inside a conﬁned, noisy space. This is indeed a formidable

tigated. challenge.

Finally, PET imaging has recently been used to explore Several research groups have succeeded in collecting

the neural bases of object-directed grasping and its obser- fMRI data from awake monkeys. Comparative fMRI stud-

vation in chimpanzees [56] as a window onto the neural ies have begun mapping the visual systems of humans and

systems involved in social learning and imitation. Relative macaque monkeys in detail [58–61]. These studies involve

to rest, both grasping an object and observing object grasp- presenting awake monkeys and humans with identical

ing activated components of a putative mirror system visual stimuli and comparing patterns of activation. This

believed to be involved in action understanding, including body of research has shown that human early and mid-

inferior frontal and lateral temporal cortices. However, level visual areas are located more posteriorly and medi-

another mirror system component, the inferior parietal ally than their macaque counterparts [59]. For example,

cortex, was only active for execution of object grasping. visual motion area MT lies within the STS in macaques,

It has been suggested that imitation is supported by an but typically within either the anterior or inferior occipital

indirect pathway from superior temporal sulcus (STS) to sulcus in humans [62]. Thus, the distance between MT and

inferior frontal cortex via inferior parietal cortex, with primary auditory cortex is much greater in humans than in

inferior parietal cortex supporting the spatial mapping macaques, suggesting expansion of the intervening cortex

of observed actions. Thus, the lack of inferior parietal lobe in humans. These comparative fMRI studies have provided

activation during observation of object-directed grasping additional information that can be used as landmarks to

movements might relate to the chimpanzee penchant for constrain the inter-species registrations mentioned earli-

emulation, which involves reproducing only the goals of er. The new information has reinforced conclusions that

actions, over imitation, which also involves reproducing parietal and ventral temporal cortices have disproportion-

the speciﬁc movements used to achieve the goal [57]. ately expanded in humans relative to macaque monkeys.

The intraparietal sulcus (IPS) has been a particular region

Functional MRI of focus. It has expanded markedly in humans relative to

fMRI is able to measure changes in blood ﬂow without use macaques, and possesses four regions that are involved in

of the radioactive tracers required for PET imaging. fMRI the perception of three-dimensional structure from motion

images can also be acquired in less time than it takes to (3D-SFM), whereas macaque IPS has only one region with

acquire PET images (fMRI has higher temporal resolu- limited sensitivity to 3D-SFM [58]. Humans also possess a

tion). The lack of fMRI data from awake chimpanzees region in the anterior supramarginal gyrus that is respon-

constitutes a crucial gap in our knowledge of comparative sive to observation of tool-use actions, a region that is not

higher primate brain function. The sensitivity of fMRI to activated in tool-experienced monkeys viewing the same

head movement would require either restraint of these stimulus [61]. The authors proposed that this region

Review Trends in Cognitive Sciences January 2014, Vol. 18, No. 1

(A) (B) As the neuroimaging community has expanded its focus

on identifying networks of brain activity rather than

isolated activation foci, Mantini et al. used fMRI and

independent components analysis (ICA) to identify a large

set of resting-state networks in both humans and macaque

monkeys, including the default-mode network [67]. Al-

though 11 spatially corresponding networks were identi-

ﬁed in the two species, three networks were identiﬁed in

humans that are absent in macaques. Notably, all three

TRENDS in Cognitive Sciences

human-speciﬁc networks include cortical regions with larg-

er than average expansion relative to macaque monkeys

Figure 2. Similar brain regions show the highest resting glucose metabolism in

humans and chimpanzees. Medial (left) and lateral (right) views of the 5% most [20]. Two are fronto–parietal networks that have previous-

active voxels in (A) humans and (B) chimpanzees. Adapted, with permission, from

ly been identiﬁed as being related to tool use, among other

[53].

functions, and the third network involves the dorsal ante-

rior cingulate cortex (ACC) and anterior insula, both criti-

cally involved in empathy [68].

underlies a speciﬁc way of understanding tool actions Another resting-state fMRI study compared connectivi-

based on appreciation of the causal relationship between ty patterns of dorsal prefrontal cortex in humans and

the intended use of the tool and the result obtained by macaque monkeys [69]. Diffusion-weighted MRI tractogra-

using it. Without parallel data from other primates includ- phy (see below) was applied in humans to deﬁne ten dorsal

ing chimpanzees, it is premature to conclude that these frontal regions with distinct patterns of connectivity. For

features are truly human specializations that uniquely each of these regions, it was possible to identify regions of

evolved in human evolution. the macaque dorsal prefrontal cortex with similar patterns

Comparative fMRI has also been applied to investi- of resting-state functional connectivity. Thus, there did not

gate brain activity related to visual processing of faces. appear to be any uniquely human areas in human dorsal

Given that primates are highly social mammals and that prefrontal cortex. However, despite the overall impression

faces are a highly salient social stimulus for primates, of similarity, differences in the speciﬁc details of connec-

researchers have compared regions of face-selective cor- tivity patterns were observed that could potentially relate

tex in monkeys and humans. One comparative fMRI to human cognitive specializations. For example, consis-

study that presented monkeys and humans with identi- tent with the above study, speciﬁc regions within dorsolat-

cal face and non-face stimuli revealed multiple patches of eral prefrontal cortex (areas 9/46) were connected with

face-selective cortex along the rostral–caudal axis of the superior and medial parietal cortex in humans but not

temporal lobes in both humans and monkeys. However, in macaque monkeys. Furthermore, an earlier study by the

whereas the monkey face patches were in lateral tempo- same group demonstrated resting-state connections be-

ral cortex, most of the human patches were in ventral tween anterior prefrontal cortex and central inferior pari-

temporal cortex [63]. This ﬁnding is consistent with etal lobule (IPL) in humans that are absent in macaques

suggestions that an evolutionary expansion of lan- [70].

guage-related cortex displaced these areas in the human

brain (see below) [64]. Diffusion-weighted imaging

Cortical auditory systems have also been compared DWI is another structural neuroimaging method and the

between humans and macaques using fMRI. A recent most recent to be applied in a comparative framework.

study showed that whereas both humans and macaques DWI is able to measure the diffusion of water molecules in

activate the lateral sulcus and superior temporal gyrus the brain [71]. Because water preferentially diffuses par-

(STG) when listening to monkey and human vocalizations, allel to the direction in which axons are oriented, tracto-

only in humans did the STS also respond to intelligible graphy software can use this information to attempt to

human utterances. Macaque STS did not respond to mon- reconstruct the trajectory of major white-matter ﬁber

key calls. Notably, the human STS activations spanned tracts in the brain [72,73].

nearly the entire length of the sulcus, and the authors DWI has been used to describe differences between

concluded that the evolution of language appears to have humans and non-human primates in the white-matter

recruited most of STS in humans [65]. pathways involved in human language [74,75]. Gesch-

Whereas the above studies are focused on task-related wind’s classic model of the functional neuroanatomy of

activation, task-independent deactivation has also been language [76] postulates that a region in the posterior

explored in monkeys and humans to identify and compare portion of the left STG, Wernicke’s area, is responsible

the default-mode network in the two species. Following the for speech comprehension, whereas a region in the left

above PET study suggesting the existence of a default- inferior frontal cortex, Broca’s area, is involved in speech

mode network in monkeys that is similar to that of production. These two regions are connected by a large

humans, Mantini et al. conducted a meta-analysis of fMRI white-matter bundle known as the arcuate fasciculus.

imaging data collected in ten awake monkeys [66] to show Homologs of Broca’s and Wernicke’s areas apparently exist

consistent task-related deactivation within a similar net- in non-human primate brains [19]. Diffusion tractography

work as the PET study that included medial prefrontal and has revealed connections between Broca’s and Wernicke’s

medial and lateral parietal cortices. areas (or their homologs) via the arcuate fasciculus in

Review Trends in Cognitive Sciences January 2014, Vol. 18, No. 1 (A) (B) Human Dorsal (E)

y = 0 mm y = –3 mm

Ventral (F) (G) Chimpanzee Dorsal

(J)

(H) (I)

y = –2.4 mm

Ventral

TRENDS in Cognitive Sciences

Figure 3. Relative strength of dorsal (arcuate fasciculus) and ventral (extreme capsule) language pathways in humans and chimpanzees. (A–D) Group average left dorsal,

right dorsal, left ventral, and right ventral pathways, respectively, for 26 humans. (E) Left (y = –3 mm) and right (y = 0 mm) dorsal and ventral pathways in coronal slices; the

dorsal pathway is yellow–red and the ventral pathway is light blue–blue. (F–I) Group average left dorsal, right dorsal, left ventral, and right ventral pathways, respectively,

for 26 chimpanzees. (J) Left and right (both y = –2.4 mm) dorsal and ventral pathways in coronal slices. Surface regions of interest (ROIs) are displayed as white outlines.

Fascicle selection ROIs are displayed as a translucent white layer over the pathways. For surface results (coronal sections), the scale is 0 (clear) to 30 (red) streamlines; for

the volume results (surface views), the scale is 5 (clear) to 300 (yellow or light blue) streamlines. Reproduced, with permission, from [74].

humans, chimpanzees, and rhesus macaques. There is, the key substrate for human language evolution. Further-

however, one striking difference between humans and more, although language is typically left-lateralized, the

the other two species. In both rhesus macaques and chim- human arcuate fasciculus is leftwardly asymmetric, where-

panzees, the posterior terminations of the arcuate are as the extreme capsule is not (Figure 3) [74].

focused on the homolog of Wernicke’s area in the posterior In recent years, human researchers have launched a

STG. Humans, however, also possess a massive projection massive effort to map the human brain connectome using

of the arcuate into the middle and inferior temporal gyri, structural (DWI) and functional (resting-state fMRI) con-

ventral to the classic Wernicke’s area [75]. These projec- nectivity [79]. Similar efforts have just begun for non-

tions lie within a region of temporal association cortex that human primates. For chimpanzees and macaque monkeys,

seems to have expanded in human evolution, displacing diffusion tractography has been combined with graph the-

nearby extrastriate visual cortex in the process. The region ory to compare the distribution of cortical hubs, regions

of expanded cortex that receives arcuate projections has that are particularly well connected with other regions,

been dubbed an epicenter for lexical–semantic processing among humans, chimpanzees, and macaque monkeys [80].

based on lesion, fMRI, and structural and functional con- Although the accuracy of DWI-based area-to-area connec-

nectivity data [77,78]. Thus, this portion of the arcuate tivity patterns is still being evaluated [81], preliminary

fasciculus may carry lexical–semantic information to Bro- results reveal both cross-species similarities and species

ca’s area. Although some have postulated that evolution differences in hub distribution. For example, across all

recruited the extreme capsule pathway into the human three species, a hub was consistently identiﬁed in the

language system, and that it plays a key role in language medial parietal cortex. This ﬁnding is consistent with

evolution, comparative DWI data suggest that the evolu- graph theory analysis of monkey tracer data [82,83]. Given

tionary expansion of the arcuate fasciculus far exceeded that the large amount of information being integrated in medial

of the extreme capsule, implicating the arcuate fasciculus as parietal cortex, we might expect it to be among the most

Review Trends in Cognitive Sciences January 2014, Vol. 18, No. 1

for white matter integrity to deteriorate before death

compared with chimpanzees, and this may be part of the

explanation for higher rates of neurodegenerative diseases

among humans. According to one anthropological theory,

the human lifespan has been uniquely extended beyond

the female reproductive period because it enables grand-

parental provisioning for weaned offspring [87]. Our data

suggest that there has not been an accompanying delay in

the onset of white matter senescence in humans.

Concluding remarks

This review has highlighted neuroimaging studies that

compare humans and chimpanzees because these compar-

isons are the most informative with respect to understand-

ing the evolution of the unique features of the human

brain. What have these comparative neuroimaging studies

taught us about the evolution of the neural substrates of

human uniqueness? The most obvious specialization of the

human brain is its size. Comparative neuroimaging has

clariﬁed how these dramatic differences in brain size de-

velop. First, human brains are already twice as large as

chimpanzee brains from an early point in gestation (16

weeks). Although both show an increase in growth velocity

at this time, they diverge sharply at 22 weeks of gestation,

when human brain growth continues to accelerate, where-

as chimpanzee brain growth decelerates [38]. Finally,

during early infancy, humans experience a very rapid

increase in white matter volume that signiﬁcantly eclipses

that found in chimpanzees [41].

10% 100%

In adulthood, human brains are distinguished not only

by their size but also by a greater proportion of their

TRENDS in Cognitive Sciences

cortical surface allocated to higher-order association cortex

Figure 4. Map of putative hubs of white matter connectivity in humans (top), rather than primary sensory and motor areas [19–21,23].

chimpanzees (middle), and macaque monkeys (bottom). A medial parietal hub

This observation suggests that relatively more of the hu-

(blue circle) is found in all three species, but a medial frontal pole hub (green circle)

man cerebral cortex is dedicated to conceptual as opposed

is present only in macaques and chimpanzees. The color scale reflects the

frequency with which a region is identified as a hub across a range of five assumed to perceptual and motor processing. Within parietal asso-

network densities and two nodal spatial resolutions. Adapted, with permission,

ciation cortex, human–macaque comparisons suggest

from [80].

changes concentrated in the intraparietal sulcus that could

relate to human tool-use abilities (e.g., extracting 3D

metabolically active areas of the brain, and this is indeed shapes from motion) [58]. Within ventral temporal associ-

the case in both humans and chimpanzees [51,53]. There ation cortex, comparative data suggest expansion of cortex

are also potentially important species differences in the involved in language processing in humans, as well as the

location of cortical hubs. Preliminary ﬁndings suggest that white matter fascicle that innervates that cortex (the

macaques and chimpanzees have hubs in polar and medial arcuate fasciculus pathway) [21,23,59,63,74,75].

prefrontal cortex, whereas humans do not (Figure 4) [80]. Networks of resting-state functional connectivity, in-

These differences complement the morphometric evidence cluding the default-mode network, exist not only in

presented above implying important changes in prefrontal humans but also in macaque monkeys [52,66,67] and

cortex during human evolution, a region involved in myri- chimpanzees [53,54]. The presence of the default-mode

ad higher cognitive functions, including memory, lan- network in other primate species raises the possibility that

guage, planning, attention, cognitive control, decision- other primates may also engage in internal thought pro-

making, and emotion regulation. cesses that are not immediately related to their external

In addition to estimating structural connectivity, DWI environment when resting. However, humans also possess

can be used to estimate white matter integrity, which is resting-state networks that have not been identiﬁed in

believed to reﬂect ﬁber density and diameter and myelina- macaque monkeys and that may be involved in functions

tion status [84,85]. In healthy humans, white matter in- such as empathy, attention, and even tool use [67]. Struc-

tegrity increases during development, peaks in middle age, tural connectivity networks, as deﬁned by DTI, have iden-

and decreases in old age [86]. Chimpanzees show a similar tiﬁed a common hub in the medial parietal cortex of

lifespan trajectory; however, white matter integrity peaks humans, chimpanzees, and macaque monkeys. However,

and begins its decline relatively earlier in the human the apparent lack of medial prefrontal hubs in humans

compared to the chimpanzee lifespan [47]. Thus, as with that are present in chimpanzees and macaque monkeys,

white matter volume, humans apparently have more time coupled with evidence of increased gyriﬁcation in human

Review Trends in Cognitive Sciences January 2014, Vol. 18, No. 1

Box 4. Outstanding questions withdraw support for chimpanzee research, and the exist-

ing captive populations of chimpanzees continue to age

How does chimpanzee functional neuroanatomy compare with

without replacement through breeding, the future of chim-

that of humans and macaque monkeys? Although comparative

panzee research in the USA is in question [90]. Privately

PET studies have provided some important insights, fMRI studies

of awake chimpanzees would provide a wealth of additional funded chimpanzee research is still possible in the USA,

information, but present formidable challenges that have yet to be

and non-invasive chimpanzee research is allowed in coun-

overcome.

tries such as Japan, where such research is generating

Chimpanzees (Pan troglodytes) and bonobos (Pan paniscus) are

important insights into human neural and cognitive spe-

equally close phylogenetic relatives of humans. How do human

brains differ from those of our other closest living primate cializations [38,41,91]. In the USA, however, where large-

relative, the bonobo (Pan paniscus)? Answering this question will scale chimpanzee research facilities still exist, now is the

provide important new insights into human brain evolution, but

opportune time to collect a complete set of neuroimaging

the effort is hampered by the limited number of bonobos available

data from chimpanzees of various ages using the best

for study.

possible imaging sequences with every known neuroimag-

How do the density and distribution of neurochemical receptors

compare between humans and non-human primates? This can be ing modality. If done with the care and foresight of the

assessed with PET imaging. human connectome project [79], in which years were allo-

MRS has not yet been applied comparatively. How do regional

cated to carefully optimize protocols, the data could be of

concentrations of neurochemicals such as glutamate and GABA

sufﬁcient quality to serve humanity for generations as a

compare between humans and other primates?

valuable resource to deﬁne the unique features of the

How do brain structure sizes, white matter status, regional

glucose metabolism, and brain receptor and metabolite levels human brain, and teach us about the evolution of the most

change across development and aging, and how does this differ remarkable organ of our species.

between humans and other primates?

What genetic differences are responsible for the neurobiological

Acknowledgments

differences between humans and other primates and what are the

neurodevelopmental pathways by which these materialize? I thank Matthew Glasser, Longchuan Li, Todd Preuss, and Hanne Van

Der Iest for their many helpful comments and suggestions on this

manuscript.

prefrontal cortex, suggests important evolutionary References

changes in the connectivity of human prefrontal cortex 1 Passingham, R.E. (2008) What is Special about the Human Brain,

[80]. Oxford University Press

2 Preuss, T.M. (2011) The human brain: rewired and running hot. Ann.

Finally, comparative neuroimaging studies of brain

N. Y. Acad. Sci. 1225 (Suppl. 1), E182–E191

aging show that human white-matter ages relatively more

3 Holloway, R.L. et al. (2008) Evolution of the brain in humans:

rapidly than that of chimpanzees [47], perhaps rendering paleoneurology. In Encyclopedia of Neuroscience (Binder, M.D. et al.,

us more vulnerable to age-related cognitive decline. eds), pp. 1326–1338, Springer-Verlag

4 Holloway, R.L. (1968) The evolution of the primate brain: some aspects

There remain unexplored frontiers in comparative pri-

of quantitative relations. Brain Res. 7, 121–172

mate neuroimaging (Box 4). For example, in addition to

5 Preuss, T.M. (2006) Who’s afraid of Homo sapiens? J. Biomed. Discov.

measuring blood ﬂow and glucose metabolism, PET imag-

Collab. 1, 17

ing can be used to map the density and distribution of 6 Passingham, R.E. (1982) The Human Primate, W.H. Freeman

neurochemical receptors for the subset of receptors for 7 Deacon, T.W. (1988) Human brain evolution: II. Embryology and brain

allometry. In Intelligence and Evolutionary Biology (Jerison, H. and

which suitable PET ligands are available. Comparative

Jerison, I., eds), pp. 383–416, Springer-Verlag

studies of neurochemical receptor distribution using post-

8 Stephan, H. et al. (1988) Comparative size of brain and brain

mortem brains have already begun [88]. With these meth-

components. In Comparative Primate Biology (Steklis, H.D. and

ods, it should be possible, for example, to compare whole Erwin, J., eds), pp. 1–38, Alan R. Liss

brain maps of different serotonin and dopamine receptors 9 Rilling, J.K. and Insel, T.R. (1999) The primate neocortex in

comparative perspective using magnetic resonance imaging. J. Hum.

and transporters across species. In the future, we can

Evol. 37, 191–223

anticipate the exciting possibility of mapping receptors

10 Finlay, B.L. and Darlington, R.B. (1995) Linked regularities in the

for modulators of social behavior such as oxytocin, vaso-

development and evolution of mammalian brains. Science 268, 1578–

pressin, and sex steroid hormones, should such ligands 1584

11 Rilling, J.K. (2006) Human and non-human primate brains: are they

become available. Another neuroimaging method that has

allometrically scaled versions of the same design? Evol. Anthropol. 15,

yet to be applied in a comparative framework is magnetic

65–77

resonance spectroscopy (MRS), which can quantify the

12 Rilling, J.K. and Seligman, R.A. (2002) A quantitative morphometric

concentration of neurochemicals such as glutamate and comparative analysis of the primate temporal lobe. J. Hum. Evol. 42,

GABA, as well as a variety of other metabolites [89]. 505–533

13 Semendeferi, K. and Damasio, H. (2000) The brain and its main

In the USA, the National Institutes of Health (NIH) is

anatomical subdivisions in living hominoids using magnetic

phasing out almost all invasive biomedical studies on

resonance imaging. J. Hum. Evol. 38, 317–332

chimpanzees. It appears that non-invasive behavioral,

14 Schoenemann, P.T. et al. (2005) Prefrontal white matter volume is

genetic, and neuroimaging studies of chimpanzees should disproportionately larger in humans than in other primates. Nat.

be able to continue if they meet strict new criteria for Neurosci. 8, 242–252

15 Schenker, N.M. et al. (2005) Neural connectivity and cortical substrates

animal living conditions. Nevertheless, most of the NIH

of cognition in hominoids. J. Hum. Evol. 49, 547–569

research chimpanzees are scheduled to be retired to the

16 Holloway, R.L. (1992) The failure of the gyriﬁcation index (GI) to

national sanctuary, with plans to sustain a single colony of

account for volumetric reorganization in the evolution of the human

only 50 animals for future research. As the NIH begins to brain. J. Hum. Evol. 22, 163–170

Review Trends in Cognitive Sciences January 2014, Vol. 18, No. 1

17 Passingham, R.E. and Ettlinger, G. (1974) A comparison of cortical 44 Pfefferbaum, A. et al. (1994) A quantitative magnetic resonance

function in man and the other primates. Int. Rev. Neurobiol. 16, imaging study of changes in brain morphology from infancy to late

233–299 adulthood. Arch. Neurol. 51, 874–887

18 Blinkov, S. and Glezer, I. (1968) The Human Brain in Figures and 45 Raz, N. and Rodrigue, K.M. (2006) Differential aging of the brain:

Tables, Basic Books patterns, cognitive correlates and modiﬁers. Neurosci. Biobehav. Rev.

19 Preuss, T.M. (2004) What is it like to be a human? In The Cognitive 30, 730–748

Neurosciences (Gazzaniga, M.S., ed.), pp. 5–22, MIT Press 46 Walhovd, K.B. et al. (2005) Effects of age on volumes of cortex, white

20 Van Essen, D.C. and Dierker, D.L. (2007) Surface-based and matter and subcortical structures. Neurobiol. Aging 26, 1261–1270

probabilistic atlases of primate cerebral cortex. Neuron 56, 209–225 47 Chen, X. et al. (2013) Brain aging in humans, chimpanzees (Pan

21 Avants, B.B. et al. (2006) Lagrangian frame diffeomorphic image troglodytes), and rhesus macaques (Macaca mulatta): magnetic

registration: morphometric comparison of human and chimpanzee resonance imaging studies of macro- and microstructural changes.

cortex. Med. Image Anal. 10, 397–412 Neurobiol. Aging 34, 2248–2260

22 Glasser, M.F. and Van Essen, D.C. (2011) Mapping human cortical 48 Wisco, J.J. et al. (2008) An MRI study of age-related white and gray

areas in vivo based on myelin content as revealed by T1- and T2- matter volume changes in the rhesus monkey. Neurobiol. Aging 29,

weighted MRI. J. Neurosci. 31, 11597–11616 1563–1575

23 Glasser, M.F. et al. (2013) Trends and properties of human cerebral 49 Gil-da-Costa, R. et al. (2006) Species-speciﬁc calls activate homologs of

cortex: correlations with cortical myelin content. Neuroimage http:// Broca’s and Wernicke’s areas in the macaque. Nat. Neurosci. 9, 1064–

dx.doi.org/10.1016/j.neuroimage.2013.03.060 1070

24 Geschwind, N. and Levitsky, W. (1968) Human brain left–right 50 Binder, J.R. et al. (1996) Function of the left planum temporale in

asymmetries in temporal speech region. Science 161, 186–187 auditory and linguistic processing. Brain 119, 1239–1247

25 Hopkins, W.D. et al. (1998) Planum temporale asymmetries in great 51 Raichle, M.E. et al. (2001) A default mode of brain function. Proc. Natl.

apes as revealed by magnetic resonance imaging (MRI). Neuroreport 9, Acad. Sci. U.S.A. 98, 676–682

2913–2918 52 Kojima, T. et al. (2009) Default mode of brain activity demonstrated by

26 Gannon, P.J. et al. (1998) Asymmetry of chimpanzee planum positron emission tomography imaging in awake monkeys: higher rest-

temporale: humanlike pattern of Wernicke’s brain language area related than working memory-related activity in medial cortical areas.

homolog. Science 279, 220–222 J. Neurosci. 29, 14463–14471

27 Hopkins, W.D. and Pilcher, D.L. (2001) Neuroanatomical localization 53 Rilling, J.K. et al. (2007) A comparison of resting-state brain activity in

of the motor hand area with magnetic resonance imaging: the humans and chimpanzees. Proc. Natl. Acad. Sci. U.S.A. 104, 17146–

left hemisphere is larger in great apes. Behav. Neurosci. 115, 1159– 17151

1164 54 Barks, S.K. et al. (2013) The default mode network in chimpanzees

28 Li, L. et al. (2010) Chimpanzee (Pan troglodytes) precentral (Pan troglodytes) is similar to that of humans. Cereb. Cortex http://

corticospinal system asymmetry and handedness: a diffusion dx.doi.org/10.1093/cercor/bht253

magnetic resonance imaging study. PLoS ONE 5, e12886 55 Buckner, R.L. et al. (2008) The brain’s default network: anatomy,

29 Taglialatela, J.P. et al. (2006) Gesture handedness predicts asymmetry function, and relevance to disease. Ann. N. Y. Acad. Sci. 1124, 1–38

in the chimpanzee inferior frontal gyrus. Neuroreport 17, 923–927 56 Hecht, E.E. et al. (2013) Differences in neural activation for object-

30 Hopkins, W.D. et al. (2007) Handedness is associated with directed grasping in chimpanzees and humans. J. Neurosci. 33, 14117–

asymmetries in gyriﬁcation of the cerebral cortex of chimpanzees. 14134

Cereb. Cortex 17, 1750–1756 57 Hecht, E.E. et al. (2013) Process versus product in social learning:

31 Gilissen, E.P. and Hopkins, W.D. (2013) Asymmetries of the parietal comparative diffusion tensor imaging of neural systems for action

operculum in chimpanzees (Pan troglodytes) in relation to handedness execution-observation matching in macaques, chimpanzees, and

for tool use. Cereb. Cortex 23, 411–422 humans. Cereb. Cortex 23, 1014–1024

32 Marchant, L.F. and McGrew, W.C. (2013) Handedness is more than 58 Orban, G.A. et al. (2006) Mapping the parietal cortex of human and

laterality: lessons from chimpanzees. Ann. N. Y. Acad. Sci. 1288, 1–8 non-human primates. Neuropsychologia 44, 2647–2667

33 Fitch, W.T. and Braccini, S.N. (2013) Primate laterality and the biology 59 Orban, G.A. et al. (2004) Comparative mapping of higher visual areas

and evolution of human handedness: a review and synthesis. Ann. N. Y. in monkeys and humans. Trends Cogn. Sci. 8, 315–324

Acad. Sci. 1288, 70–85 60 Vanduffel, W. et al. (2002) Extracting 3D from motion: differences in

34 Yeni-Komshian, G.H. and Benson, D.A. (1976) Anatomical study of human and monkey intraparietal cortex. Science 298, 413–415

cerebral asymmetry in the temporal lobe of humans, chimpanzees, and 61 Peeters, R. et al. (2009) The representation of tool use in humans and

rhesus monkeys. Science 192, 387–389 monkeys: common and uniquely human features. J. Neurosci. 29,

35 Herndon, J.G. et al. (1998) Brain weight does not decrease with age in 11523–11539

adult rhesus monkeys. Neurobiol. Aging 19, 267–272 62 Kolster, H. et al. (2010) The retinotopic organization of the human

36 Martin, R.D. (1990) Primate Origins and Evolution, Princeton middle temporal area MT/V5 and its cortical neighbors. J. Neurosci. 30,

University Press 9801–9820

37 Gould, S.J. (1977) Ontogeny and Phylogeny, Harvard University Press 63 Tsao, D.Y. et al. (2008) Comparing face patch systems in macaques and

38 Sakai, T. et al. (2012) Fetal brain development in chimpanzees versus humans. Proc. Natl. Acad. Sci. U.S.A. 105, 19514–19519

humans. Curr. Biol. 22, R791–R792 64 Ungerleider, L.G. et al. (1998) A neural system for human visual

39 Gibson, K. (1991) Myelination and behavioral development: a working memory. Proc. Natl. Acad. Sci. U.S.A. 95, 883–890

comparative perspective on questions of neotony, altriciality and 65 Joly, O. et al. (2012) Processing of vocalizations in humans and

intelligence. In Brain Maturation and Cognitive Development: monkeys: a comparative fMRI study. Neuroimage 62, 1376–1389

Comparative and Cross-cultural Perspectives (Gibson, K.R. and 66 Mantini, D. et al. (2011) Default mode of brain function in monkeys. J.

Petersen, A.C., eds), pp. 29–63, Aldine de Gruyter Neurosci. 31, 12954–12962

40 Leigh, S.R. (2004) Brain growth, life history, and cognition in primate 67 Mantini, D. et al. (2013) Evolutionarily novel functional networks in

and human evolution. Am. J. Primatol. 62, 139–164 the human brain? J. Neurosci. 33, 3259–3275

41 Sakai, T. et al. (2013) Developmental patterns of chimpanzee 68 Singer, T. and Lamm, C. (2009) The social neuroscience of empathy.

cerebral tissues provide important clues for understanding the Ann. N. Y. Acad. Sci. 1156, 81–96

remarkable enlargement of the human brain. Proc. Biol. Sci. 280, 69 Sallet, J. et al. (2013) The organization of dorsal frontal cortex in

20122398 humans and macaques. J. Neurosci. 33, 12255–12274

42 Allen, J.S. et al. (2005) Normal neuroanatomical variation due to age: 70 Mars, R.B. et al. (2011) Diffusion-weighted imaging tractography-

the major lobes and a parcellation of the temporal region. Neurobiol. based parcellation of the human parietal cortex and comparison

Aging 26, 1245–1260 with human and macaque resting-state functional connectivity. J.

43 Bartzokis, G. et al. (2001) Age-related changes in frontal and temporal Neurosci. 31, 4087–4100

lobe volumes in men: a magnetic resonance imaging study. Arch. Gen. 71 Basser, P.J. et al. (1994) Estimation of the effective self-diffusion tensor

Psychiatry 58, 461–465 from the NMR spin echo. J. Magn. Reson. B 103, 247–254

Review Trends in Cognitive Sciences January 2014, Vol. 18, No. 1

72 Basser, P.J. and Jones, D.K. (2002) Diffusion-tensor MRI: theory, 83 Modha, D.S. and Singh, R. (2010) Network architecture of the long-

experimental design and data analysis – a technical review. NMR distance pathways in the macaque brain. Proc. Natl. Acad. Sci. U.S.A.

Biomed. 15, 456–467 107, 13485–13490

73 Mori, S. and Van Zijl, P.C. (2002) Fiber tracking: principles and 84 Beaulieu, C. (2002) The basis of anisotropic water diffusion in the

strategies – a technical review. NMR Biomed. 15, 468–480 nervous system – a technical review. NMR Biomed. 15, 435–455

74 Rilling, J.K. et al. (2011) Continuity, divergence, and the evolution of 85 Pfefferbaum, A. and Sullivan, E.V. (2003) Increased brain white matter

brain language pathways. Front. Evol. Neurosci. 3, 11 diffusivity in normal adult aging: relationship to anisotropy and partial

75 Rilling, J.K. et al. (2008) The evolution of the arcuate fasciculus voluming. Magn. Reson. Med. 49, 953–961

revealed with comparative DTI. Nat. Neurosci. 11, 426–428 86 Westlye, L.T. et al. (2010) Life-span changes of the human brain white

76 Geschwind, N. (1970) The organization of language and the brain. matter: diffusion tensor imaging (DTI) and volumetry. Cereb. Cortex

Science 170, 940–944 20, 2055–2068

77 Turken, A.U. and Dronkers, N.F. (2011) The neural architecture of the 87 Hawkes, K. (2004) Human longevity: the grandmother effect. Nature

language comprehension network: converging evidence from lesion and 428, 128–129

connectivity analyses. Front. Syst. Neurosci. 5, 1 88 Palomero-Gallagher, N. et al. (2013) Cyto- and receptor architecture of

78 Glasser, M.F. and Rilling, J.K. (2008) DTI tractography of the human area 32 in human and macaque brains. J. Comp. Neurol. 521, 3272–3286

1 13

brain’s language pathways. Cereb. Cortex 18, 2471–2482 89 de Graaf, R.A. et al. (2003) In vivo H-[ C]-NMR spectroscopy of

79 Van Essen, D.C. et al. (2013) The WU–Minn Human Connectome cerebral metabolism. NMR Biomed. 16, 339–357

Project: an overview. Neuroimage 80, 62–79 90 Kaiser, J. (2013) Biomedical research. NIH to phase out most chimp

80 Li, L. et al. (2013) Mapping putative hubs in human, chimpanzee and research. Science 341, 17–18

rhesus macaque connectomes via diffusion tractography. Neuroimage 91 Matsuzawa, T. (2009) The chimpanzee mind: in search of the

80, 462–474 evolutionary roots of the human mind. Anim. Cogn. 12 (Suppl. 1), S1–S9

81 Essen, D.C.V. et al. (2013) Mapping connections in humans and 92 Stephan, H. et al. (1981) New and revised data on volumes of brain

nonhuman primates: aspirations and challenges for diffusion imaging. structures in insectivores and primates. Folia Primatol. (Basel) 35, 1–29

In Diffusion MRI: from Quantitative Measurement to In-Vivo 93 Passingham, R.E. (1973) Anatomical differences between the neocortex

Neuroanatomy (2nd edn) (Johansen-Berg, H. and Behrens, T.E.J., of man and other primates. Brain Behav. Evol. 7, 337–359

eds), Elsevier 94 Deacon, T. (1997) The Symbolic Species, W.W. Norton

82 Harriger, L. et al. (2012) Rich club organization of macaque cerebral 95 Sherwood, C.C. et al. (2005) Is prefrontal white matter enlargement a

cortex and its role in network communication. PLoS ONE 7, e46497 human evolutionary specialization? Nat. Neurosci. 8, 537–538