Functional specificity in the human brain A windowinto the

Functional specificity in the human brain: A window
into the functional architecture of the mind
Nancy Kanwisher1
McGovern Institute for Brain Research, Massachusetts Institute
of Technology, Cambridge, MA 02139
This contribution is part of the special series of Inaugural
Articles by members of the National Academy of Sciences
elected in 2005.
Contributed by Nancy Kanwisher, April 16, 2010 (sent for
review February 22, 2010)
Is the human mind/brain composed of a set of highly specialized
components, each carrying out a specific aspect of human
cognition,
or is it more of a general-purpose device, in which each
component
participates in a wide variety of cognitive processes? For nearly
two
centuries, proponents of specialized organs or modules of the
mind and brain—from the phrenologists to Broca to Chomsky
and
Fodor—have jousted with the proponents of distributed
cognitive
and neural processing—from Flourens to Lashley to McClelland
and
Rumelhart. I argue here that research using functional MRI i s
begin-
ning to answer this long-standing question with new clarity and
precision by indicating that at least a few specific aspects of

cogni-
tion are implemented in brain regions that are highly specialized
for
that process alone. Cortical regions have been identified that are
specialized not only for basic sensory and motor processes but
also
for the high-level perceptual analysis of faces, places, bodies,
visu-
ally presented words, and even for the very abstract cognitive
func-
tion of thinking about another person’s thoughts. I further
consider
the as-yet unanswered questions of how much of the mind and
brain are made up of these functionally specialized components
and how they arise developmentally.
brain imaging | modularity | functional MRI | fusiform face area
Understanding the nature of the human mind is arguably
thegreatest intellectual quest of all time. It is also one of the
most
challenging, requiring the combined insights not only of
psychol-
ogists, computer scientists, and neuroscientists but of thinkers
in
nearly every intellectual pursuit, from biology and mathematics
to
art and anthropology. Here, I discuss one currently fruitful com-
ponent of this grand enterprise: the effort to infer the
architecture
of the human mind from the functional organization of the
human brain.
The idea that the human mind/brain is made up of highly spe-
cialized components began with the Viennese physician Franz
Joseph Gall (1758–1828). Gall proposed that the brain is the

seat
of the mind, that the mind is composed of distinct mental
faculties,
and that each mental faculty resides in a specific brain organ. A
heated debate on localization of function in the brain raged over
the next century (SI Text), with many of the major figures in the
history of neuroscience weighing in (Broca, Brodmann, and Fer-
rier in favor, and Flourens, Golgi, and Lashley opposed). By the
early 20th century, a consensus emerged that at least basic
sensory
and motor functions reside in specialized brain regions.
The debate did not end there, however. Today, a century later,
two questions are still fiercely contested. First, how
functionally
specialized are regions of the brain? The concept of functional
specialization is not all or none but a matter of degree; a
cortical
region might be only slightly more engaged in one mental
function
than another, or it might be exclusively engaged in a single
mental
function. Many neuroscientists today challenge the strong (ex-
clusive) version of functional specialization. As one visual
neuro-
scientist put it, “each extrastriate visual area, rather than per -
forming a unique, one-function analysis, is engaged, as are most
neurons in the visual system, in many different tasks” (1).
The second ongoing controversy concerns the question of
whether only basic sensory and motor functions are carried out
in functionally specialized regions, or whether the same might
be
true even for higher-level cognitive functions. Although one
might
think that Broca settled this matter with his demonstration that

the
left frontal lobe is specialized for aspects of language, the
current
status of this debate is far from clear. Indeed, a recent
authorita-
tive review of the brain-imaging literature on language
concludes
that “areas of the brain that have been associated wi th language
processing appear to be recruited across other cognitive
domains”
(2). The case of language is not unique. Indeed, a backlash
against
strong functional specialization seems to be in vogue. A recent
neuroimaging textbook argues that “unlike the phrenologists,
who
believed that verycomplextraits wereassociatedwithdiscretebrain
regions, modern researchers recognize that . . . a single brain
region
may participate in more than one function” (3).
In this review, I address these ongoing controversies about the
degree and nature of functional specialization in the human
brain,
arguing that recent neuroimaging studies have demonstrated that
at least a few brain regions are remarkably specialized for
single
high-level cognitive functions. To make my case, I first
describe
three candidates for such functionally specific brain regions
identified in my lab. I then consider how much of the brain is
made
up functionally specialized regions: are they found only for
high-
level perceptual functions or also for components of abstract
thought? I then ask how these regions arise developmentally;
that

is, what are the exact roles of genes and experience in the de-
velopment of these regions? In SI Text, I address a key
challenge to
the specificity of the fusiform face area (FFA) and parahippo-
campal place area (PPA), and I consider the computational
advantages that may be afforded by specialized regions in the
first
place. I conclude by speculating that the cognitive functions im-
plemented in specialized brain regions are strong candidates for
fundamental components of the human mind.
Neuroimaging Evidence for Functional Specialization in the
Ventral Visual Pathway
Ever since Broca, neurologists and cognitive neuroscientists
have
investigated cognitive impairments in people with focal brain
lesions, providing extensive evidence for localization of at least
some functions in the human brain. The study of neurological
disorders is one of the few methods that allows powerful infer -
ences about not just the engagement but also the necessity of
a given brain region for a specific cognitive function in humans.
However, even if a particular functionally specific region
exists,
a lesion is unlikely to affect all and only that region, so clean
functional dissociations in the patient literature are rare. Brain
imaging [and functional MRI (fMRI) in particular] thus
provides
Author contributions: N.K. wrote the paper.
The author declares no conflict of interest.
1E-mail: [email protected]
This article contains supporting information online at
www.pnas.org/lookup/suppl/doi:10.
1073/pnas.1005062107/-/DCSupplemental.

www.pnas.org/cgi/doi/10.1073/pnas.1005062107 PNAS | June
22, 2010 | vol. 107 | no. 25 | 11163–11170
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mailto:[email protected]
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www.pnas.org/cgi/doi/10.1073/pnas.1005062107
a powerful complement to lesion studies, allowing neural
activity in
the normal human brain to be monitored safely and
noninvasively
at resolutions approaching the millimeter range. The principle
underlying fMRI is that blood flow increases locally in active
regions of the brain. Although the precise neural events that
fMRI
reflects are a matter of ongoing research, the general validity of
the
method as an indicator of neural activity is clear from studies
rep-
licating, with fMRI, the properties of visual cortex previously
established by the gold-standard method of single-neuron re-
cording in monkeys. Thousands of papers have used fMRI to
ask
about the relative contributions of different regions in the
human
brain to a wide variety of cognitive functions. My lab has
focused
especially on the question of whether any of these brain regions
are
specifically engaged in a single high-level cognitive function.
Supporting the idea that some brain regions are indeed en-
gaged in specific mental functions, we have identified a number
of cortical regions (Fig. 1) that respond selectively to single
cat-

egories of visually presented objects: most notably, the FFA,
which responds selectively to faces (4, 5), the PPA, which re-
sponds selectively to places (6), and the extrastriate body area
(EBA), which responds selectively to bodies and body parts (7).
These three brain regions are not the only ones that have been
argued to conduct specific perceptual functions (8). Probably
the
strongest other case is visual area MT/V5, shown much earlier
with
neurophysiological methods to play a key causal role in the per -
ception of visual motion in monkeys (9–11), and later,
identified in
humans with brain imaging (12, 13). However, even this classic
example of functional specificity does not process visual-
motion
information exclusively; this area also contains information
about
stereo depth (14). Another strong case of functional specificity
for
a simple visual dimension is color (15), for which recent
evidence
from both fMRI and single-unit recording indicates the
existence
of multiple millimeter-sized color-selective “globs” in posterior
inferotemporal cortex in macaques (16, 17). Other brain regions
have been reported to be selectively engaged in processing in-
formation about biological motion (18), visually guided
reaching
(19), and grasping (20). For most cases in the neuroimaging
liter-
ature, however, the main claim is one of regional specificity
(i.e.,
that the implicated function activates this region more than
other
brain regions) rather than of functional specificity (i.e., that the

implicated region is more engaged for this function than other
functions). In contrast, this article focuses primarily on the
question
of functional specificity, because this is the question that is
critical
for understanding the architecture of the human mind (Fig. 1).
The evidence we and others have collected on the FFA, PPA,
and EBA provides unusually strong support for functional speci -
ficity of these regions for three reasons. First, each of these
regions
has been found consistently in dozens of studies across many
labs;
although their theoretical significance can be debated, their
exis-
tence cannot. Indeed, these regions are found, in more or less
the
same place, in virtually every neurologically intact subject; they
are
part of the basic functional architecture of the human brain.
Sec-
ond, the category selectivity by which each region is defined is
not
merely statistically significant, but also large in effect size:
Each of
these regions responds about twice as strongly to stimuli from
its
preferred category as to any nonpreferred stimuli.* Although ef-
fect size is generally ignored in the brain imaging literature, it
should not be, as it determines the strength of the inference you
can draw: If you know how to double the response of a region,
you
generally have a better handle on its function than if you merely
know how to change its response by a small amount. Third, the
fact

that these regions can be found easily in any normal subject
makes
possible a “region of interest” (ROI) research strategy whereby
the region is first functionally identified in each subject indi -
vidually in a short “localizer” scan, and then the response of
that region is measured in any number of new conditions that
test specific hypotheses about its exact function. It is precisely
the fact that the responses of the FFA, PPA, and EBA have
been quantified in each of now dozens of different stimulus and
task manipulations that enables us to say with confidence that
each of these regions is primarily, if not exclusively, engaged in
processing its preferred stimulus class (faces, places, and
bodies,
respectively). Taken together, these three regions constitute
some of the strongest evidence that at least some cortical
regions
are selectively engaged in processing specific classes of stimuli.
Next I summarize the evidence for the specificity of each of
these regions for a particular class of stimuli.
FFA. The FFA is the region found in the midfusiform gyrus (on
the
bottom surface of the cerebral cortex just above the cerebellum)
that responds significantly more strongly when subjects view
faces
than when they view objects (4, 5, 23). This region responds
sim-
ilarly to a wide variety of different kinds of face images (24),
in-
cluding photos of familiar and unfamiliar faces, schematic
faces,
cartoon faces, and cat faces as well as faces presented in
different
sizes, locations, and viewpoints (25, 26). Crucially, when
relatively
high-resolution imaging methods are used (including

individual–
subject analyses without spatial smoothing), no nonface object
has
been reported to produce more than one-half the response found
for faces in this region. Further, the evidence (27, 28) allows us
to
reject alternative hypotheses proposed earlier that the FFA is
not
specifically responsive to faces but rather is more generally en-
gaged in fine-grained discrimination of exemplars of any
category
or of any category for which the subject has gained substantial
expertise. Importantly, the magnitude of the FFA response is
co-
rrelated trial by trial with success both in detection of the
presence
of faces and in identification of individual faces (29, 30). Thus,
as
discussed further in SI Text, the FFA seems to play a central
role in
the perception of faces but to play little if any role in the per -
ception of nonface objects. This hypothesis is consistent with
evi-
dence that (i) face-selective responses have been observed in
ap-
proximately this location in subdural electrode recordings from
the brains of subjects undergoing presurgical mapping for epi -
lepsy treatment (31–33) and (ii) lesions in approximately this
lo-
cation can produce selective deficits in face perception (34).
Answering the question of what exactly the FFA does with faces
has been more difficult. Current evidence indicates, however,
that
it is sensitive to multiple aspects of face stimuli including face
parts

Fig. 1. This schematic diagram indicates the approximate size
and location
of regions in the human brain that are engaged specifically
during percep-
tion of faces (blue), places (pink), bodies (green), and visually
presented
words (orange), as well as a region that is selectively engaged
when thinking
about another person’s thoughts (yellow). Each of these regions
can be
found in a short functional scan in essentially all normal
subjects.
*fMRI response magnitudes are typically measured as percent
signal increases compared
with a low baseline condition (e.g., fixating on a cross), so a 2-
fold response difference
might correspond to a 2% signal increase from fixation versus a
1% signal increases from
fixation. Crucially, the magnitude of selectivity must be
evaluated using data indepen-
dent of that used to identify the region (21, 22). Selectivity is
underestimated when low-
resolution methods are used (e.g., when voxels are large or
when spatial smoothing or
group analyses are used).
11164 | www.pnas.org/cgi/doi/10.1073/pnas.1005062107
Kanwisher
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(eyes, noses, and mouths), the T-shaped configuration of those
features, and external features of faces like hair (35) and that
representations extracted in the FFA show some invariance
across
changes in stimulus position and less invariance across changes
in
viewpoint (25), mirroring comparable behavioral results. The
FFA
further exhibits neural correlates of long-known behavioral sig-
natures of perception (28), including disproportionate inversion
effects (36) and sensitivity to holistic information in upright but
not
inverted faces (37). Despite these initial insights, important
open
questions about the FFA remain to be addressed, including a
more
precise characterization of the representations that it extracts
and
the computations that it performs, whether it plays some (albeit
lesser) role in the perception of any nonface objects, whether it
is cytoarchitectonically distinct from its neighbors, what other
re-
gions it is connected to, whether and how interactions with
other
regions modulate or participate in the computations conducted
in
the FFA and whether it constitutes a single contiguous region
on
the cortical surface.
PPA. The PPA is defined functionally as the region adjacent to
the collateral sulcus in parahippocampal cortex that responds
significantly more strongly to images of scenes than objects (6).
The PPA responds to a wide variety of scenes, including indoor
and outdoor scenes, familiar and unfamiliar scenes, and even

abstract scenes made of Legos (38, 39). The PPA is primarily
responsive to the spatial layout of one’s surroundings: its re -
sponse is not reduced when all of the objects are removed from
an indoor scene, leaving just the floor and walls (6). This re-
sponse profile is tantalizingly reminiscent of the geometric
mod-
ule (40, 41), inferred from behavioral data in which rats and
human infants (and adults whose language system is tied up by
a concurrent verbal task) rely exclusively on the layout of
space,
not on objects or landmarks, to reorient themselves in an envi -
ronment after they are disoriented. Evidence that the PPA is not
only activated when information about spatial layout is pro-
cessed, but that it is further necessary for this function, comes
from patients with damage in or near the PPA, who have diffi -
culty encoding information about spatial layout and more gen-
erally, in knowing where they are (42, 43). The precise role of
the
PPA in place perception and navigation is a topic of ongoing
investigation (38, 39).
EBA. The EBA is a region on the lateral surface of the brain ad-
jacent to (and sometimes partly overlapping with) visual motion
area MT, which responds significantly more strongly to images
of
bodies and body parts than to images of objects or faces. This
region responds equally to visually very different images of
bodies
and body parts, from a photograph of a hand to a photograph of
a body (human or animal) to a schematic stick figure of a
person.
Evidence that this region is not only activated during but is also
necessary for the perception of bodies comes from studies in
which disruption of the EBA by a brain lesion (44) or
transcranial
magnetic stimulation (TMS) (45, 46) impairs the perception of

body form but not the perception of faces or object shape (45).
Further, current evidence indicates that the EBA is more
involved
in perceiving other people’s bodies than one’s own (47, 48) and
that it is more engaged in the perception of the form/identity of
bodies than in the actions they are carrying out (44, 49–51).
Ovals, Gradients, or Archipelagoes? For simplicity, I have
discussed
functionally specific regions in the cortex as if they are discrete
entities with sharp, well-delineated edges, like the kidney, liver,
and heart. Indeed, some functional divisions in the cortex are
re-
markably sharp, such as the border between retinotopic visual
areas V1 and V2. However, there is no reason to assume all
functional distinctions in the brain have perfectly sharp edges.
Similarly, there should be no requirement that these regions
must
be simple convex shapes. Irregular-shaped regions with long
ten-
drils or even multiple nonadjacent but nearby (and presumably
connected) subregions might be expected. If it becomes clear at
higher resolutions that the FFA is in fact a set of distinct non-
contiguous regions (a “fusiform face archipelago”?), that will
strain the organ analogy but still leave viable a meaningful
sense in
which these noncontiguous patches constitute a functionally dis -
tinct system, much as Maui and Lanai share deep geological, bi -
ological, and cultural similarities in virtue of being part of the
Hawaiian islands, despite the channel of water between them.
However, the more a region turns out to be extensively inter-
digitated with other functionally distinct entities and the more
its
borders resemble an arbitrary cutoff point on a gradual
functional

change across the cortex (52), the less this case will follow the
classic idea of a functionally distinct brain region. Most
questions
about biological systems are matters of degree, and so too is the
question of functional specialization in the cortex. Currently
available evidence suggests an impressive degree of compart-
mentalization in at least a few cortical regions (53). Further ex-
periments using new tasks and higher resolution will provide
more precise quantitative tests of the anatomical distinctness of
these regions.
In sum, evidence is now strong that each of at least three cor -
tical regions in humans are selectively (perhaps even
exclusively)
engaged in specific cognitive functions: the FFA in representing
the appearance of faces, the PPA in representing the appearance
of places, and the EBA in representing the appearance of
bodies.
(See SI Text for my reply to an important challenge to the func-
tional specificity of these regions.) Although I have emphasized
the role of each of these regions in visual perception, their re-
sponse is not determined solely by the stimulus that the subject
is
viewing. The activity of these regions can be strongly
modulated
by visual attention (54), and they can even be activated when no
stimulus is present at all. Simply imagini ng a face (with eyes
closed) selectively activates the FFA and imagining a place
acti-
vates the PPA (55).
Of course, no complex cognitive process is accomplished in
a single brain area, and arguments for the specificity of these
regions by no means imply that other brain regions play no role.
Earlier cortical regions such as primary visual cortex are
obviously

crucial in the perception of faces, places, and bodies, and higher
areas (e.g., in parietal and frontal regions) are also probably
necessary for information in the FFA, PPA, and EBA to be used
by other cognitive systems and to reach awareness (56–58). Fur-
ther, none of these regions is the only one with its defining se-
lectivity. For faces, selective responses are found not only in
the
FFA but also in a nearby but more posterior occipital face area,
as
well as other regions in the superior temporal sulcus (34, 59),
and
anterior temporal pole (60). For bodies, selective responses are
found not only in the EBA but also in the fusiform body area
(FBA). For scenes, selective responses are found not only in the
PPA but also in retrosplenial cortex (RSC) and the transverse
occipital sulcus (TOS). These other selective regions have not
been studied in the same detail as the FFA, PPA, and EBA, so
their functions are less clear. Still, the existence of multiple se-
lective regions for each of these three stimulus classes raises
the
exciting possibility that we may ultimately understand how the
percept of a face, for example, emerges from the joint activity
of
a number of functionally distinct regions, each conducting a dif-
ferent aspect of the analysis of the face stimulus. In the sub-
sequent sections of this article, I discuss four major questions
raised by the work on the FFA, EBA, and PPA concerning their
specificity, generality, origins, and computational significance.
Generality: How Much of the Brain Is Composed of
Functionally Specific Regions?
The evidence for functional specificity within several brain
regions
(FFA, PPA, EBA) invites a return to the broader questions
raised
by Gall, Fourens, and Broca: how much of the brain is

composed of
Kanwisher PNAS | June 22, 2010 | vol. 107 | no. 25 | 11165
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regions that are selectively engaged in specific cognitive

functions?
We consider this question by asking whether other specialized
brain regions exist for (i) other object categories in the ventral
visual pathway and (ii) components of high-level thought.
Other Category-Selective Regions? Do we have cortical regions
selectively involved in the perception of snakes? Weapons?
Vegetables? As Pinker asks in The Language Instinct, does the
brain have a produce section (61)? What about categories of
objects that may not have been crucial to the survival of our
ancestors but that play central roles in modern daily lives, like
cars and cell phones? There hardly seems room in the brain for
all of these categories, or even all of the important ones, and it
is
not clear what would be accomplished computationally by such
extreme compartmentalization anyway. Happily, we are not re-
stricted to mere speculation; we can simply test empirically for
other specialized brain regions. Downing and I did just that
(62),
screening broadly for 20 different categories of objects selected
for their (arguable) evolutionary importance (spiders and
snakes,
predators, prey, tools, food), their experiential frequency in
modern life (cars, chairs), or their implication from prior
studies
of patients with focal brain damage (fruits and vegetables, mu-
sical instruments). Despite replicating the existence of cortical
regions selective for faces, places, and bodies in each subject,
we
found no evidence of cortical specialization for any of the other
object categories tested. The previously reported selectivity for
tools (63) was not evident in our data, and any partial disso-
ciations between responses to living and nonliving things (or
an-
imate versus inanimate objects) were restricted to the already
documented properties of the face, place, and body areas. Al -

though null results can always be trumped by later discoveries
made with higher spatial resolution or greater statistical power,
the resolution and power that was sufficient for robust
replication
of the FFA, PPA, and EBA did not turn up any new category-
specific regions.
A central conceptual puzzle arises, however, in the search for
brain regions selective for new object categories: how do we
decide which categories to test? If we proceed by testing only
the
categories that seem plausible to us, then we risk getting
trapped
within the confines of our own theoretical preconceptions. This
concern is underscored by the fact that the brain specializations
already described for faces, places, and bodies are reminiscent
of
two of the mental faculties proposed by Gall: the sense of peo-
ple, and the sense of place. Given that Gall arrived at these
categories without real evidence, the fact that we have arrived
at
the same categories is worrisome. Are we, like the
phrenologists,
allowing our cultural biases to determine what we find in the
brain? Are specializations we discover in the brain a kind of
high-
tech projective test?
With rigorous experimental methods, we can reduce the chance
that the outcomes of our experiments are determined by our cul -
tural/theoretical predispositions. However, how can we ever
pre-
vent our conceptual baggage from biasing the space of
hypotheses
that we consider? My colleagues and I are developing methods
to

circumvent these biases by searching for structure in the
functional
responses of the ventral visual cortex in a hypothesis-neutral
fashion (64–66). This method searches large datasets composed
of
the response of each voxel to a large number of stimuli and dis -
covers dominant response profiles in that dataset. Importantly,
the
method knows nothing about the location of each voxel, so it
makes no assumption that functionally related voxels are
adjacent.
Even more importantly, the method does not look only for
selec-
tivity for single-object categories but instead, for any profile of
response across the stimuli that best characterizes a large
number
of voxels (e.g., a high response to all categories except one or a
high
response to one-half of the categories and a low response to the
other one-half, etc.).
For our first test of this method, we scanned subjects while
they viewed eight different categories of stimuli. Remarkably,
the
method spontaneously identified face-, place-, and body-
selective
response profiles among the top five most robust profiles (Fig.
S1
and SI Text). Even more impressively, when we split the data in
half to produce 16 different conditions (two per category),
without telling the algorithm which pairs of conditions belonged
to the same category, the algorithm discovered response profiles
characterized by high responses to both face conditions com-
pared with everything else, although these conditions were not
labeled as the same category. We found the same for scenes and
bodies. These results suggest that face, place, and body

selectivity
are not simply our own cultural projections onto the brain but
are actually inherent in the brain’s response to visual stimuli.
Also, they suggest that we do not have similar specificity in the
brain for lots of other categories; face, place, and body
selectivity
are probably special cases. We are now conducting a stronger
test of this hypothesis by generating a larger set of stimuli more
representative of human visual experience and asking whether
face, place, and body selectivity still emerge from the data,
even
when no stimulus categories are presumed in advance and even
when we do not start by constructing a stimulus set that con-
tains a sizable proportion of faces, places, and bodies. It will be
most exciting if this new test not only (re)discovers face, place,
and body selectivity but also discovers new, previously
unknown,
response profiles.
Selective Cortical Regions for Aspects of Thought? Perhaps it is
not
surprising that discrete cortical regions can be found that are
selectively engaged in processing specific aspects of high-level
vision. After all, we are highly visual animals who allocate one-
third of our cortex to various aspects of vision, and some
division
of computational labor within this broad expanse of cortex
would seem to make sense. But what about the rest of
cognition?
Do we have specialized brain machinery for specific
components
of thought?
Indeed, we do. Several years ago, Rebecca Saxe made the as-
tonishing discovery of a region at the junction of the temporal
and

parietal lobes of the right hemisphere that is selectively engaged
when one thinks about what another person is thinking (67, 68).
Using the ROI method, Saxe and colleagues (67, 68) have iden-
tified this region (known as the rTPJ) in hundreds of subjects
and
measured its response to a wide array of tasks. These data show
that the rTPJ responds strongly when people read scenarios that
describe what a person knows or thinks but not when people
read
scenarios describing physical, as opposed to mental, representa -
tions (e.g., in maps or photographs) or vivid descriptions of
a person’s physical appearance that do not refer to the contents
of
the person’s mind. This region is so selective that it does not
even
respond when people think about another person’s bodily sen-
sations (e.g., thirst, hunger, pleasure), which are mental states
but
which do not have propositional content like thoughts and
beliefs.
Most impressively, this region is more strongly activated when
people make decisions about what another person knows than
when they make the identical response to the identical stimuli
but do not construe the task as pertaining to another person’s
thoughts (69). The rTPJ is the most functionally selective high-
level cortical region yet described in humans.
The discovery of the rTPJ, and the characterization of its
functional specificity, serves as an existence proof that
function-
ally specific cortical regions are not restricted to primary
sensory
and motor areas, or high-level perceptual regions, but can be
found for at least one very abstract and high-level aspect of hu-
man cognition. This finding invites the question of whether
other

aspects of high-level cognition may also be computed in
special-
ized cortical regions. Perhaps the most obvious case here is the
one proposed by Gall and Broca: language. Surprisingly, despite
two centuries of investigation, no consensus has emerged on the
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question of whether any brain regions are specialized for lan-
guage (or components thereof). The problem arises in part from
a conflict between the findings from studies of patients with
focal
brain lesions, which suggest considerable functional specificity
of
some cortical regions for some aspects of language, versus the
findings from the large neuroimaging literature on language,
which suggest considerable overlap between linguistic and non-
linguistic processing.
Evelina Fedorenko and I have argued that one possible ex-
planation of the conflict between these two types of studies is
that
the methods that have been used in virtually all prior neuro-
imaging studies of language (group analyses) are not well -
suited

for detecting functional specificity. Group analyses
underestimate
functional specificity, because different individuals’ brains are
anatomically quite different from each other, so alignment
across
brains is necessarily imperfect. As a result, functionally
different
regions will sometimes be aligned to the same location i n the
group space (70, 71). Fedorenko and I are now revisiting the
question of functional specificity of the language system using
the same individual–subject ROI method that has enabled us
to discover the functional specificity of the other regions de -
scribed above.
Note that the failure to discover functionally specific brain re -
gions for a given cognitive process can also be informative.
Sup-
pose, for example, that we discover that no brain region is
selec-
tively engaged in any aspect of language processing but rather
that all regions that support language processing also contribute
substantially to nonlinguistic functions. Such a discovery would
offer powerful clues into what language is all about.
Specifically,
we would want to know: what are those nonlinguistic functions
that overlap with (say) syntactic processing? What would it tell
us about syntax, if it shares neural machinery with (say) music
perception, social cognition, or arithmetic? Such possibilities il -
lustrate the exciting prospect of discovering components of
mind
and brain defined not by the content of the information they
operate on, but rather by the computational structure of the
problems they solve. Indeed, evidence of domains of cognition
that are not computed in cortical tissue selective for that func-
tion would offer clues about the broader questions of which
mental functions get their own private patch of real estate in the

brain, which do not, why some do and others do not, and what
the computational advantages might be of functional specializa-
tion in the first place (discussed further in SI Text).
In some sense, the discovery and characterization of compo-
nents of the mind and brain that are uniquely human are the
most exciting. The fact that our minds and brains have a special
circuit just for figuring out what another person is thinking tells
us something deep about what it means to be a human being. If
we are lucky enough to discover brain machinery specialized for
other uniquely human cognitive abilities, such as synta x or a
component thereof, it will provide a similarly thrilling insight
into human nature. Further, such discoveries might enable us
to trace the evolutionary origins of the function in question. For
example, if we discover cytoarchitectonic or gene-expression
markers for the brain region for understanding other minds, we
could then look for the homologous region in primates and in-
vestigate its function.
Discovering functionally specific components of mind and brain
that are not uniquely human, but that are shared with other ani-
mals, offers different scientific opportunities. Most current
meth-
ods available with humans do not enable us to determine
precisely
the time course of engagement, the causal role, or the
connectivity
of a given cortical area. (Important exceptions are studies using
TMS in normal subjects and electrodes implanted for surgical
purposes in humans.) We cannot study in humans the
development
of a given region under controlled rearing conditions, and we
have
no good tools for studying the actual neural circuits that
implement
the cognitive ability in question. However, methods exist to

answer
all of these questions in nonhuman primates. Therefore, the dis -
covery of functionally specific brain regions that are present in
both
humans and macaques, such as face- and body-selective regions,
opens up fantastic opportunities to address the biological
mecha-
nisms of cognition in a way that is nearly impossible in humans.
The
discoveries (72) of face- and body-selective regions in macaque
cortex and the investigation of these regions using the powerful
tools of systems neuroscience (73–75) provide a stunning
illustra-
tion of the insights that can be gleaned from work in primates
on
the neural machinery of high-level vision.
Origins: How Do Functionally Specific Regions Arise
Developmentally?
Although it is obvious that genes and experience both play
crucial
roles in the development of all brain structures, it is less clear
which of the precise details of the circuitry of each brain region
are specified in the genome and which are derived from experi -
ence. At first glance, the existence of brain regions selective for
faces, places, and bodies would seem to fit nicely with the view
held by many of the most prominent advocates of modularity of
mind and brain—from Gall to Chomsky, Fodor, and Pinker—
that
organs of mind and brain are innate (i.e., the products of natural
selection). Indeed, it seems plausible that the rapid and accurate
recognition of faces, places, and bodies had such survival val ue
to
our ancestors that detailed instructions for wiring up the
specific

neural circuitry of the FFA, PPA, and EBA may have become
specified in the genome. However, alternative accounts are also
plausible. Quite apart from the experience of our ancestors,
each
of us modern-day humans probably looks at (and attends to)
faces, places, and bodies more frequently than almost any other
stimulus class. Given that cortical organization can be affected
by
experience, the existence of regions specialized for proces sing
these visual categories could result from the extensive
experience
each of us has with these categories during our lifetime, without
any specific genetic predilection for these categories per se. Re -
cent evidence, discussed next, suggests that the cortical
machinery
of face perception may be primarily genetically specified,
whereas
the selectivity of another nearby cortical region may be
primarily
determined by the individual’s experience.
Specific Role of Genes in Face Perception. Until very recentl y,
we
had almost no relevant data on the degree to which the
existence,
location, and fine-grained circuit details of the FFA were genet-
ically specified versus derived from experience, leaving the
topic
wide open for passion and polemic. In just the last few years,
however, several new lines of evidence point to a specific role
of
genes in determining the neural machinery of face perception.
First, a congenital disorder in face perception, developmental
prosopagnosia, has been shown to run in families (76, 77). Sec-
ond, face-perception ability is heritable (i.e., more strongly cor -
related for identical than fraternal twins), and this effect is

independent of the heritability of domain-general abilities like
IQ
or global attention (78, 79). Third, the spatial distribution of
fMRI responses across the ventral visual pathway to faces is
more
similar between monozygotic than dizygotic twins; the same is
true for scenes but not for chairs or words (80). Although all
three
findings implicate genes in face-specific processing, they do not
tell us which genes are involved or by what causal pathway they
affect face perception. Perhaps these genes simply increase
social
interest and hence, experience with face perception, enhancing
ability through training. Or perhaps they directly specify the de-
tailed wiring of the neural circuits for face perception. Evidence
that genes may be largely responsible for wiring up much of the
face system, with little or no role of experience with faces,
comes
from recent reports that impressive face discrimination abilities
are present in human newborns (81) and even in baby monkeys
reared for up to 2 years without ever seeing faces (82). These
findings support the hypothesis that the specific instructions for
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constructing the critical circuits for face perception are in the
genome.
Note that despite this recent evidence that the face system can
develop with little or no experience with faces (81, 82), it is
nonetheless clear that experience with faces does affect the
face-
perception system. First, in the other race effect,
psychophysical
studies have demonstrated what most people know from daily
life: we are better able to distinguish individuals from a more
familiar than less familiar race (aka “they all look alike”). Sec-
ond, in perceptual narrowing, face-discrimination abilities that
are initially effective on face stimuli of all races or primate
species become restricted within a few months of life to only
the

race/species that the subject has experienced (82–84). This tun-
ing is entirely consistent with the view that the basic face-per-
ception system can arise with virtually no face experience, even
if
it is subsequently fine tuned by experience, a phenomenon par -
alleled in language development (85, 86).
What do developmental studies in humans tell us about the
origins of the face system? A long-standing view has held that
face perception develops very slowly in humans, not reaching
adult levels until adolescence or later (87, 88). Consistent with
this
view, several imaging papers (89, 90) have argued that the FFA
increases in size through and even beyond adolescence. Some
have suggested that this slow development implies that
experience
plays a critical role in constructing the face-perception system
(89,
90). This conclusion does not follow, however, because some
developmental changes that occur long after birth are primarily
genetically, not experientially, determined (as in the case of pu-
berty). Further, more recent behavioral results show that every
aspect of face-specific perceptual processing tested so far (in-
version effects, measures of holistic processing, etc.) is present
at
the earliest ages ever tested; several signatures of face
processing
are present within the first 3 days of life (91). Ongoing studies
in our lab and others are finding adult-sized FFAs in the
majority
of children scanned at age 5 and 6 years. Thus, despite the
wide-
spread claims to the contrary, current developmental data do
not argue for slow development of face-specific perceptual
mechanisms.
In sum, although the precise roles of genes and experience in

the construction of category-selective regions of cortex are not
yet clear, several studies suggest that the face system may be
largely innate: experience with faces may not be necessary for
the
initial development of the face-perception system, although ex-
perience apparently fine tunes it. Still, if new evidence
strength-
ens this view, it would not necessarily imply that all
functionally
specific regions of cortex are constructed in the same way. In-
deed, the functional selectivity of at least one region of the
brain,
the visual word form area, is derived from the individual’s ex-
perience, not their genes, as discussed next.
At Least One Functionally Specific Cortical Region Derives Its
Specificity from Experience. Visual word recognition provides
a powerful test case of the origins of cortical selectivity.
Everyone
in our study population has extensive experience looking at vi -
sually presented words, so if experience is ever sufficient to
specify
the selectivity of a cortical region for a particular class of
stimuli,
we would expect to find one for visual words. However,
crucially,
human beings have only been reading for a few thousand years,
which is not thought to be long enough for the evolution of
a complex structure. Thus, if a brain region is found that
responds
selectively to visually presented words, that would suggest that
cortical selectivity can be specified by experience (92). What
does
the evidence show?
A number of studies going back almost two decades have ar-

gued for the existence of a visual word form area. However,
many
of these studies contrasted the cortical response to visually pre -
sented words with the response to very simple baseline tasks
(93,
94), leaving unanswered the question of whether the region is
specific to visual word recognition or whether it plays a more
general role in the recognition of any complex visual stimuli.
We
searched for several years for a brain region that responded
more
strongly to visually presented words than to line drawings of fa-
miliar objects. Although we failed initially to find such a region
in
many studies, when technical advances enabled us to scan at
higher resolution, we then found it in the majority of subjects
(95).
This region is tiny, about one-tenth the volume of the FFA,
which
explains why we did not see it with standard imaging
resolutions
(Fig. S2 and SI Text).
To further test the selectivity of this region, we used the same
localize-and-test procedure that was effective in characterizing
the FFA, PPA, and EBA. In independent tests of the response
of the region, we replicated the fact that it responded
severalfold
higher to words than to line drawings (Fig. S2A). Further, we
showed that the response was low, in this region, to stimuli that
shared many of the visual properties of words: strings of digits
and
letters in an orthography unfamiliar to the subject (Hebrew).
The

response to consonant strings was the same as that to words,
which
suggests that meaning and orthographic regularity are not re-
quired to activate this region. In contrast, when we scanned sub-
jects who read both English and Hebrew, we found a high re-
sponse to words written in both languages (and orthographies)
in
this region (Fig. S2B). Thus, the response of this region is de-
termined by the individual’s experience. An even stronger dem-
onstration of the experience dependence of this region comes
from a before-and-after study of Chinese illiterates, who
showed
a character-selective response in this region after being trained
for several months to read but not before (96).
Many important questions about this cortical region remain to
be answered, such as whether it can develop in an alternate lo-
cation if damage to this region occurs in childhood (97) or
adulthood (98, 99) and whether it reflects a discrete,
functionally
homogeneous module or a gradient of selectivity (52). Whatever
the answers to these questions, the current evidence indicates
that the particular selectivity of this region depends on the spe -
cific experience of the individual and not the experience of his
or
her ancestors.
In sum, recent studies are beginning to shed light on the roles
of genes and experience in the origins of cortical regions selec-
tively engaged in specific cognitive functions. Multiple lines of
evidence indicate a specific role for genes in wiring up the face
system, yet at least one other region derives its selectivity from
experience. Much remains to be understood about how exactly
genes and experience shape neural circuits.
Conclusions

What a great privilege it is to have access to technology that
Gall
and Broca never dreamed of, technology that enables us to
discover fundamental components of the human brain. Already,
the evidence is strong for cortical regions that are selectively
en-
gaged in the perception of faces, places, bodies, and words and
another region for thinking about what other people are
thinking.
Possible cortical specializations for other domains, including
aspects of number (100), music (101), andlanguage (70), are
under
active investigation. The possibility is within reach of obtaining
a cognitively precise parts list for the human brain. The most
ex-
citing aspect of this enterprise is not where each component is
found in the brain but which functions get their own brain
region
and ultimately, why some do and others apparently do not. But
even a complete parts list, exciting as it would be, is only a first
step.
A wide landscape of exciting new questions has opened up.
What
are the exact neural circuits that enable each region to conduct
its
signature function? Why do these regions arise so
systematically
where they do in the brain, and are there ever circumstances in
which a region arises in a different locus or moves over after
damage to its original locus? Is there some hardware constraint
(cytoarchitecture, connectivity, proximity to other areas, etc.)
that
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forces these regions to arise where they do? How do these
regions
work with each other—and with more general-purpose brain
regions (102)—to support complex real-world cognition? How
did
these regions evolve, and what functions did they conduct in our
primate ancestors? Can each region be recruited to perform new
tasks? For example, can the neural machinery of social
cognition be
used to think about the mood of a financial market or to
understand
why a computer program fails to understand what we want it to
do,
and can the PPA be used to understand maps, architectural dia-
grams, or graphs depicting 3D landscapes of data?
But what psychologists like me most want to do is discover

fundamental components not just of the brain but also of the
mind. For the discoveries of functionally specific brain regions
to
be useful in this enterprise, we need much richer understandings
of the role of each of these regions in cognition. We need not
just
loose descriptions of the function of a region (e.g., face percep-
tion) but precise characterization of the computations and rep-
resentations conducted in each region. Does the face area
extract
qualitatively different kinds of representations from those ex-
tracted in the place area, as suggested by extensive research on
the perception of faces and spatial layouts? Is it involved only
in
the representation of the physical characteristics of a face, or
does it contain information about the sex, age, race, mood, or
identity of the person? Methods such as fMRI adaptation and
fMRI pattern analysis have started to answer these questions,
although each method has limitations and progress to date has
been modest. Satisfyingly precise characterizations of the
mental
functions implemented in each region will require extensive fur -
ther work using not only fMRI and other brain-based methods
but
also increased efforts to relate these findings to behavioral and
computational work on the representations and algorithms en-
tailed in different aspects of cognition.
ACKNOWLEDGMENTS. Many people provided useful
comments on this
manuscript, especially Bevil Conway, Sue Corkin, Ev
Fedorenko, Charles
Jennings, Eric Kandel, Hans Op de Beeck, John Rubin, Liz
Spelke, and Bobbie
Spellman. The writing of this paper was supported by National

Institutes
of Health Grant EY13455 (to N.K.) and a grant from the Ellison
Medical
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1
Commentary
Neuroimaging as a New Tool in
the Toolbox of Psychological
Science
John T. Cacioppo,1 Gary G. Berntson,2 and Howard C.
Nusbaum1
1
The University of Chicago and
2
Ohio State University
ABSTRACT—During the past quarter century, advances in
imaging technology have helped transform scientific fields.

As important as the data made available by these new
technologies have been, equally important have been the
guides provided by existing theories and the converging
evidence provided by other methodologies. The field of
psychological science is no exception. Neuroimaging is an
important new tool in the toolbox of psychological science,
but it is most productive when its use is guided by psycho-
logical theories and complemented by converging
methodologies including (but not limited to) lesion, electro-
physiological, computational, and behavioral studies.
Based on this approach, the articles in this special issue
specify neural mechanisms involved in perception, atten-
tion, categorization, memory, recognition, attitudes, social
cognition, language, motor coordination, emotional regu-
lation, executive function, decision making, and depression.
Understanding the contributions of individual and func-
tionally connected brain regions to these processes benefits
psychological theory by suggesting functional representa-

tions and processes, constraining these processes, produc-
ing means of falsifying hypotheses, and generating new
hypotheses. From this work, a view is emerging in which
psychological processes represent emergent properties of a
widely distributed set of component processes.
KEYWORDS—functional magnetic resonance imaging; cog-
nitive processes; social processes; clinical processes; develop -
mental processes
New imaging technologies are having a demonstrable impact on
the landscape of scientific research. The most expensive
imaging
instrument, and the most vivid example, is the Hubble Space
Telescope. The Hubble telescope was deployed in April 1990
and has undergone three major repairs and upgrades since that
time. It has also provided data and images at a resolution
Galileo
Galilei could not have imagined when, early in the 17th century,
he discovered the craters on the moon, sunspots, the rings of
Saturn, and the moons of Jupiter by gazing through his first

crude
telescope. The discoveries made possible by the high-resolution
data and images from the Hubble nearly four centuries later
include massive black holes at the center of galaxies, the
existence of precursors to planetary systems like our own, and
a greater quantity and distribution of dark matter than expected.
As important as were the data provided by the Hubble
Telescope,
however, these discoveries were dependent on extant theories
and methodologies. The discovery of stellar black holes at the
centers of galaxies, for instance, was guided by general
relativity
theory and supported by research using several converging
methodologies (e.g., Dolan, 2001).
Developments in neuroimaging during the past quarter
century have increasingly made it possible to investigate the
differential involvement of particular brain regions in normal
and disordered thought in humans. Previously, studies of the
neurophysiological structures and functions associated with

psychological states and processes were limited primarily to
animal models, postmortem examinations, electrophysiological
measures, and observations of the occasional unfortunate indi -
vidual who suffered trauma to or disorders of the brain (e.g.,
Raichle, 2003). The detailed three-dimensional color images
provided by neuroimaging, modeling statistical properties of the
working brain, have captured the imagination of the public and
the
scientific community, shaped funding priorities at federal
funding
agencies and foundations, and produced a dramatic growth in
scientific papers and journals in the area (Cacioppo et al.,
2007).
Address correspondence to John T. Cacioppo, Center for
Cognitive
and Social Neuroscience, The University of Chicago, 5848 S.
Uni-
versity Avenue, Chicago, Illinois 60637; e-mail:
[email protected]
edu.
C U R R E N T D I R E C T I O N S I N P S Y C H O L O G I C
A L S C I E N C E
62 Volume 17—Number 2Copyright r 2008 Association for
Psychological Science

This special issue of Current Directions in Psychological
Science
summarizes recent theoretical advances in various fields of
psychological science that are attributable in part to the use of
neuromaging technology—most prominently, functional mag-
netic resonance imaging (fMRI). Although reading these
reviews
leaves the impression that neuroimaging is an important new
tool
in the toolbox of psychological science, one cannot help but
also
be impressed that neuroimaging—like the Hubble Space Tele-
scope—is most productive scientifically when its use is guided
by
extant theories and complemented by converging
methodologies.
In the typical neuroimaging study, psychological states and
processes are manipulated and activation in different brain
regions is measured. The logic of this design is best suited
for drawing inferences about the differential involvement of

par-
ticular brain regions in specific psychological operations.
For instance, when Poeppel and Monahan (2008, this issue) ask
how speech signals are represented and processed in the brain,
they are using neuroimaging along with converging methods
from psychological science, and guided by the blueprint of
competing theoretical accounts for speech perception, to in-
vestigate the differential involvement of particular brain regions
in psychological states and processes. It is also possible under
certain conditions to draw reasonable inferences about psycho-
logical operations based on regions of brain activation
(Cacioppo
& Berntson, in press; Cacioppo & Tassinary, 1990; Henson,
2006; Poldrack, 2006; Sarter, Berntson, & Cacioppo, 1996).
Across the articles in this special issue, evidence from lesion
studies, animal studies, neuroimaging, single-cell recording,
event-related brain potentials, transcranial magnetic
stimulation,
computational modeling, and behavior is reviewed to investigate

the brain regions involved in perception, attention,
categorization,
memory, recognition, attitudes, social cognition, language,
motor
coordination, emotional regulation, executive function, decision
making, and depression. Together, the evidence converges on
the
view that psychological states and processes are mediated by a
network of distributed, often recursively connected, interacting
brain regions, with the different areas making specific, often
task-
modulated contributions (see Poeppel & Monahan, 2008).
DISTRIBUTED NETWORKS INVOLVED IN COGNITIVE
REPRESENTATIONS AND FUNCTION
Humans are visual creatures. The visual properties of scenes
drive neurons in the lateral geniculate nucleus of the thalamus,
and visual perception has been found to involve a dor sal stream,
or ‘‘where pathway,’’ and a ventral stream, or ‘‘what
pathway.’’
The dorsal (where) stream includes the areas designated V1, V2,
V5/MT, and the inferior parietal lobule and is associated with

motion, representation of object locations, and control of the
eyes and arms when visual information is used to guide
saccades
or reaching. The ventral (what) stream includes the areas V1,
V2, V4, and the inferior temporal lobe (areas that include
the lateral occipital complex and the fusiform gyrus) and is
associated with form recognition, object representation, face
recognition, and long-term memory (Engel, 2008, this issue).
Grill-Spector and Sayres (2008, this issue) provide evidence
that changes in the size, position, orientation, and other aspects
of physical appearance of faces activate the lateral occipital
complex; differences in the identity of individuals are related
to adaptation responses in the fusiform gyrus; and changes
in facial expression and gaze direction involve the superi or
temporal sulcus.
Different theoretical representations and decompositions of
speech perception into processing components are described,
and the neural outcomes associated with each of these theoret-

ical representations are reviewed, by Poeppel and Monahan
(2008). Here, too, the evidence suggests the involvement of a
specialized, interconnected set of neural regions that are widely
distributed across the temporal, parietal, and frontal lobes.
Specifically, the early spectrotemporal analyses involve
bilateral
auditory cortices and the superior temporal cortex, and phono-
logical analyses involve the middle and posterior portions of the
superior temporal sulcus. The processing streams then appear to
divide into a ventral stream—which maps auditory and phono-
logical representations onto lexical conceptual representations
and involves the middle temporal gyrus and inferior temporal
sulcus—and a dorsal stream—which maps auditory and pho-
nological representations onto articulatory and motor represen-
tations and involves the Sylvian parietotemporal area, posterior
frontal gyrus, premotor cortex, and anterior insula (Poeppel &
Monahan, 2008).
The attentional modulation of perceptual processes is influ-
enced by motivational states and goals as well as by stimulus

properties. Visual attentional control can modulate neural
activity in the lateral geniculate nucleus and superior colliculus,
as well as in the posterior parietal cortex (specifically, the re -
gions of the superior parietal lobule and the lateral intraparietal
area within the intraparietal sulcus) and the frontal eye field and
supplementary eye field within the prefrontal cortex (Yantis,
2008, this issue). These perceptual and attentional processes
contribute to the acquisition of knowledge about the world that
is organized categorically. Barsalou (2008, this issue) notes
that the dominant theory in cognitive science posits that this
knowledge is represented in an abstract, amodal fashion and
constitutes semantic memory. He shows in his review, however,
that categorical knowledge includes modal representations
using the same neural mechanisms involved in perception,
affect, and action. In Barsalou’s view, the representation of a
category involves a neural circuit distributed across the relevant
modalities, all of which can become activated during conceptual
processing. Thus, conceptual processing can be viewed as an

embodied rather than purely abstract process.
How does categorical knowledge being represented in this
distributed, modal fashion square with the neuroscientific
evidence for differences in the localization of short- and long-
term memory processes? Nee, Berman, Moore, and Jonides
Volume 17—Number 2 63
John T. Cacioppo, Gary G. Berntson, and Howard C. Nusbaum
(2008, this issue) suggest that the evidence supporting the
qualitative distinction between short- and long-term storage
processes has been misinterpreted, and they suggest that the
data instead support a unitary model of memory in which the
same regions of the brain that represent perception, action, and
affect are involved in both short- and long-term storage pro-
cesses. That is, short- and long-term memories do not differ in
representation but in the activation by attention, which i n turn
involves a frontal biasing (i.e., maintenance) of representational
cortices (e.g., frontal eye fields and intraparietal sulcus for

spatial representations; superior temporal sulcus and Sylvian
parietotemporal area for phonological and articulatory repre-
sentations). For instance, damage in the presylvian region pro-
duces deficits in short- and long-term memory that depends on
phonological material, and the greater prevalence of such ma-
terial in studies of short- than of long-term storage processes
may
inadvertently have led to evidence that this region was involved
uniquely in short-term memory (Nee et al., 2008). Short- and
long-term memory retrieval also activates overlapping regions
of
the left lateral frontal cortex, whereas the monitoring of
retrieved
information, whether from short- or long-term memory, is
associated with the anterior prefrontal activation (cf. Cabeza,
Dulcos, Graham, & Nyberg, 2002).
Neuropsychological research dating back several decades sug-
gested structures in the medial temporal lobe (e.g., the hippo-
campus) were involved in declarative rather than nondeclarative

learning. Unlike the distinction between short- and long-term
memory, the distinction between declarative and nondeclarative
learning is supported by neuroimaging research. For instance,
research by Knowlton and Foerde (2008, this issue) has shown
that
when performance on a probabilistic classification task is based
on declarative memory performance the medial temporal lobe
is activated, whereas when performance on the task is based on
nondeclarative memory performance the striatum is activated.
Knowlton and Foerde (2008) also review evidence showing
that nondeclarative skill learning, at least for simple tasks, is
asso-
ciated with repetition suppression—reductions in the regions of
neural activation associated with the initial performances of a
task
(e.g., the premotor region)—a finding that has been interpreted
as
indicating a greater efficiency of processing in the neural struc-
tures involved in novice performance. Priming-related
reductions,
on the other hand, are found in perceptual and prefrontal

regions,
with only the latter associated with behavioral facilitation.
Knowlton and Foerde (2008) duly note, however, that acti vation
in
the perceptual cortices may appear to be less important in the
extant literature in part because of the type of priming
paradigms
that have been used in fMRI research.
The complexities of social living, such as recognizing indi -
viduals and groups, negotiating nontransitive social hierarchies
and shifting alliances, using language to communicate and
manipulate, and engaging in social exchanges over extended
periods and locales, place special demands on the capacities of
the human brain. Mitchell (2008, this issue) reviews evidence
that thinking about thinking people (e.g., impression formation,
social causality)—in contrast, for instance, to thinking about
physical causality—is associated with activation of the medial
prefrontal cortex, the right temporo-parietal junction, and the
medial parietal region (e.g., the precuneus/posterior cingulate

cortex). Mitchell (2008) suggests that the activation of the
medial prefrontal cortex appears to be involved whenever
people
are obliged to consider the psychological characteristics of
another person, whereas the temporo-parietal junction appears
to be activated when the attentional and perceptual require-
ments of taking the perspective of another are invoked. The
medial parietal region, on the other hand, is activated during
the retrieval of episodic memories and self-knowledge, as well
as during the viewing of two or more interacting people (e.g.,
Iacoboni et al., 2004).
The brain has evolved to guide behavior in contextually
flexible, coordinated, and adaptive ways, and, as with attention,
there are top-down as well as bottom-up influences on the
orchestration of motor processes. Oliveira and Ivry (2008, this
issue) focus on the top-down influences in their discussion of
goals as higher-level action representations that connect sensory
and motor processes to guide response selection and motor
coordination. They review fMRI studies showing that motor

planning and externally guided movements are associated with
activity in the posterior superior parietal region and, at least for
externally guided movements, in premotor regions; internally
generated movements are associated with activity in the basal
ganglia, the anterior cingulate cortex, and inferior frontal and
parietal cortices; and conflicting action goals and effort are
associated with activity in medial frontal areas, including the
anterior cingulate cortex and presupplementary motor areas.
One suggestion that has emerged from this area of research
is that goal representation and action planning are not imple-
mented simply as an abstract code but rather involve embodied
processes. Not unlike how Barsalou (2008) invokes modal
mechanisms, Rizzolati and Arbib (1998) and Skipper, Nusbaum,
and Small (2006) review evidence for the role of embodied
representations in categorization and language.
The fundamental idea that the motor system is important for
cognition and perception, through prior experience and mirror
neurons, has become an important contribution of neuroscience

to bolstering theoretical constructs in the psychology of em-
bodied understanding. However, much of the work on the mirror
system in cognition and understanding has been carried out with
trained nonhuman primates or with adult humans. For any
theory
of adult function to be viable, it is critical to understand the
development of these mechanisms. Diamond and Amso (2008,
this issue) review work on the neural substrates underlying
cognitive development, including the mirror-neuron system
and neonatal imitative behaviors and maternal touch and
gene expression. As the authors note, a major contribution of
neuroscience to theories of cognitive development is ‘‘demon-
strating the remarkable role of experience in shaping the mind,
64 Volume 17—Number 2
Neuroimaging and Psychological Science
brain, and body’’ (p. 136). Such cross-cutting work is necessary
to begin to link biological development with learning and

experience. Moreover, as cognition can no longer be studied
in isolation from the social context of its use, this work
suggests
the importance of understanding development within its social
context of parental interaction. Given the importance of social
context, then, it is important to go beyond the treatment
of specific processes to understand how such processes depend
on the goals they are directed at achieving.
To achieve one’s goals, one has to be able to represent
the likely rewards (and punishments) associated with different
decisions, encode the risk or certitude that the reward will
be obtained, update these representations, and act on the basis
of these representations. O’Doherty and Bossaerts (2008, this
issue) review evidence regarding the brain regions associated
with each of these components of decision making. Specifically,
they report that the encoding of reward expectation is associated
with activation of the orbitofrontal cortex, medial prefrontal
cortex, amygdala, and ventral striatum; recognizing greater risk
or uncertainty associated with obtaining a reward correlates

with
increased activity in the anterior insula and lateral orbitofrontal
regions; updating of reward expectancies is associated with
the ventral striatum and orbitofrontal cortex; and selecting
one of several responses to obtain the greatest reward involves
the striatum, with the ventral striatum more involved in the
prediction of reward across the various options and the dorsal
striatum more involved in the selection among the alternatives
(O’Doherty & Bossaerts, 2008).
The frontal regions have long been thought to be involved
in executive functions such as formulating goals and plans;
selecting among options to achieve these goals; monitoring the
consequences of actions in light of one’s goals; and inhibiting,
switching and regulating one’s behaviors accordingly. Aron
(2008, this issue) reviews evidence that the initiation of a motor
response proceeds from the planning areas of the frontal cortex
to the putamen, globus pallidus, thalamus, primary motor
cortex,
motor nucleus in the spinal cord, and finally to the muscles.

Being able to inhibit a motor response once it has been initiated
has obvious adaptive value, and Aron (2008) shows that this
inhibition involves the right inferior frontal cortex, which pro-
jects to the subthalamic nucleus (a region of the basal ganglia
that may act on the globus pallidus to block the motor
response).
Monitoring for response conflicts, in turn, appears to involve
the
dorsal anterior cingulate and the adjacent presupplementary
motor area, which, in turn, is connected to the right inferior
frontal cortex and subthalamic nucleus. Switching also involves
the presupplementary motor area and the right inferior frontal
cortex (Aron, 2008). This work has led to a model in which
‘‘the
[presupplementary motor area] may monitor for conflict
between
an intended response and a countervailing signal . . . Then,
when
such conflict is detected, the ‘brakes’ could be put on via the
connection between the right [inferior frontal cortex] and the

[subthalamic nucleus] region’’ (Aron, 2008, p. 127).
Emotional regulation is another form of executive function
in which activity of the amygdala and insula cortex, which are
involved in emotional responding, is modulated by activity in
the
prefrontal cortex (e.g., BA10, ventromedial prefrontal cortex,
dorsolateral prefrontal cortex) and anterior cingulate. Ochsner
and Gross (2008, this issue) review evidence that different
components of reappraisal processing correspond to different
areas of prefrontal activation: Selective attention and working
memory components are related to dorsal portions of the pre-
frontal cortex, language or response inhibition are related to
ventral portions of the prefrontal cortex, monitoring or control
processes are related to the dorsal anterior cingulate cortex, and
reflections on one’s emotional state are related to dorsal
portions
of the medial prefrontal cortex. Although the correspondences
proposed by Ochsner and Gross (2008) do not match perfectly
those articulated by Aron (2008), the overlapping role for the

anterior cingulate is noteworthy in light of the notion that the
presupplementary motor area may be especially involved in the
monitoring and control of motor conflicts.
The complexities of daily living are simplified in part by the
formation of preferences and attitudes, which can serve as
behavioral guides and simplify decision making. These attitudes
can be explicit or implicit. Stanley, Phelps, and Banaji (2008,
this issue) review evidence suggesting that the activation
of implicit attitudes toward social groups (e.g., minorities) is
associated with increased activity in the amygdala, dorsolateral
prefrontal cortex, and anterior cingulate cortex. The cumulative
evidence to date suggests that the automatic evaluation of
a stimulus (e.g., social category) is associated with amygdala
activation, the monitoring for response conflicts (e.g., the
extent
to which the stimulus elicits competing impulses) is associated
with anterior cingulate activation, and the regulation of those
impulses is associated with dorsolateral prefrontal activation.
Failures of effective emotional regulation can become costly

in personal, social, and economic terms when these failures
become
systemic. Depression, for instance, has been estimated to cost
more
than $43 billion per year in the United States (Greenberg,
Stiglin,
Finkelstein, & Berndt, 1993). Understanding the variation in
biological systems that leads to individual differences in neural
mechanisms of emotional regulation is critical to understanding
how some systemic failures become chronic and debilitating.
Gotlib and Hamilton (2008, this issue) review evidence that
depressed individuals show less activity in the dorsolateral
prefrontal cortex and greater activation of the amygdala and
subgenual anterior cingulate cortex to emotional stimuli than do
healthy controls. Parallel findings for basal activity levels in
these brain regions are also noted. These findings are consistent
with Gotlib and Hamilton’s notion that depression is in large
part
a disorder of emotion regulation in which the normal inhibitory
influence of limbic structures by the anterior cingulate and

dorsolateral prefrontal cortex is disrupted, although the
subgenual anterior cingulate cortex may play an especially
critical role in this dysregulation (Gotlib & Hamilton, 2008).
Given the importance of the anterior cingulate and dorsolateral
prefrontal cortex in motor control, attention, and emotion,
the individual variation in function in these areas that can lead
to depression may also explain that disorder’s other associated
cognitive symptoms.
Indeed, understanding the relationship between biological
variation in neural mechanisms and psychological processes is
important beyond clinical problems. Kosslyn et al. (2002) and
Vogel and Awh (2008, this issue) have argued that, to bridge
the gap between psychological phenomena and their underlying
biological substrata, such variation should be regarded as
important data in its own right. Kosslyn et al. (2002) describe

how
an idiographic approach can be used to address three types of
issues: the nature of the mechanisms that give rise to a specific
ability, the role of psychological or biological mediators of
envi-
ronmental challenges, and the existence of variables that have
nonadditive effects with other variables. Vogel and Awh (2008)
extend this argument in their discussion of three additional
ways
in which an idiographic approach can contribute to
psychological
theory: validating neurophysiological measures, demonstrating
associations among constructs, and demonstrating dissociations
among similar constructs. Thus, an idiographic approach, which
complements the more typical nomethetic approach, can be
applied in any domain to help elucidate psychological theory.
Together, the theory and data summarized in this special issue
of Current Directions in Psychological Science highlight the
notion that encephalization and the remarkable connectivity
in the human brain provide the substrate for the integration

of inputs from widely distributed neural regions (only some of
which are amenable to current brain-imaging technology) whose
activation and organization can be contextually determined. The
distributed nature of and substantial overlap among the extant
networks calls for a revision in our thinking about basic
psychological constructs. The early reliance on introspection as
a method of identifying elemental psychological processes led
to
a recognition of the category error—the intuitively appealing
but
often erroneous notion that the organization of psychological
phenomena maps in a one-to-one fashion onto the organization
of underlying neural substrates. Perception, memories,
emotions,
and beliefs were each once thought to be localized in distinct
sites in the brain. The contributions to this special issue clearly
indicate that psychological and behavioral concepts do not each
map onto clear and identifiable ‘‘centers,’’ but rather that each
concept is associated with a distributed, interconnected set of

neural regions. What appears at one point in time to be a
singular
theoretical construct (e.g., memory), when examined in con-
junction with evidence from the brain (e.g., lesions, neuroimag-
ing), may reveal a more complex and interesting organization at
both levels (e.g., declarative vs. procedural memory processes).
Conversely, what appeared to be distinct constructs (e.g.,
short- vs. long-term memory) may need to be reconsidered in
light
of new neuroscientific evidence. We suspect we are far from
seeing
the last of such revisions to psychological theories. It is only
through these revisions, and corresponding refinements in our
understanding and conceptions of the underlying neural
functions,
that we can reduce the category error and move toward an
isomorphism between the psychological and biological domains.
Neuroimaging and work in neuroscience more generally are
reshaping the constructs that are being used to build psycho-
logical theories. Psychological research during the 20th century

resulted in many of the basic psychological elements derived
from introspection to be recast as the product of multiple,
more specific component processes. As illustrated by the
articles
in this special issue, many of these component processes in-
volve a network of distributed, often recursively connected,
interacting brain regions, with the different areas making
specific, often task-modulated contributions. Moreover, a single
neural region can often be involved in what have been treated
as very different psychological processes. One implication is
that
what have been considered basic psychological or behavioral
processes are being conceptualized as manifestations of com-
putations performed by networks of widely distributed sets of
neural regions.
How might these neural components be combined to produce
distinct psychological processes? One metaphor is the Lego set,
in which the computations performed in localized neural regions
are fixed (like distinct Lego pieces), but different pieces

and configurations of these building blocks produce different
psychological processes. An alternative metaphor is the periodic
table in chemistry, in which different neural component pro-
cesses may have properties and affinities whose function (com-
putation) depends on the network of areas with which they
are combined. There is no evidence at present to favor either
perspective, but the important point here is that they suggest
very different ways of thinking about neural activity and
psychological function.
In sum, neuroimaging work is leading to a rethinking of how
psychological and neural functions are parcelled. For instance,
the close proximity of motor control, emotional appraisal,
attention, working memory, and behavioral regulation suggests
that these functions may not be as separable as they are
currently
treated and studied. We may well need a new lexicon of
constructs that are neither simply anatomical (e.g., Brodmann
area 6 vs. Brodmann area 44) nor psychological (e.g., attention,
memory), as we usher in a new era of psychological theory

in which what constitutes elemental component processes
(functional elements) are tied to specific neural mechanisms
(structural elements) and in which the properties of interrelated
networks of areas may indeed be more than the sum of the parts.
CONCLUSION
Critics who say neuroimaging is costly and has contributed little
if anything to psychological theory sometime appear to expect
the images of the working brain to come with labels regarding
their cognitive functions. Although an adequate specification of
66 Volume 17—Number 2
Neuroimaging and Psychological Science
neurobiology should contribute to our understanding of cogni -
tive architecture and function, our understanding of the relevant
neurobiology is influenced strongly by our extant theoretical
models regarding cognitive architecture and function (see
Hagoort, 2008, this issue). The contributions to this special
issue

demonstrate that neuroimaging is an important new tool in the
toolbox of psychological science, but one that is most
productive
scientifically when its use is guided by psychological theories
and complemented by converging methodologies. This
approach,
in which theory and converging methods are used hand in hand
to
expand our understanding of the neural mechanisms involved in
cognition and the contributions of individual and functionally
connected brain regions to these processes, promises to advance
psychological theory by suggesting functional representations
and processes, by imposing significant constraints on these pro-
cesses, and by producing not only new behavioral hypotheses
but
also new means of falsifying theoretical hypotheses.
Acknowledgments—Preparation of this paper was supported
by grants from the National Institute of Mental Health (Grant
No.
P50 MH72850) and the John Templeton Foundation.
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