Binder et al.
Cerebral Cortex, in press
Where is the Semantic System?
A Critical Review and Meta-Analysis of 120 Functional Neuroimaging Studies
Jeffrey R. Binder, Rutvik H. Desai, William W. Graves, Lisa L. Conant
Language Imaging Laboratory, Department of Neurology, Medical College of Wisconsin
Jeffrey R. Binder, MD
Department of Neurology
Medical College of Wisconsin
MEB Room 4550
8701 Watertown Plank Road
Milwaukee, WI, 53226 USA
Semantic memory refers to knowledge about people, objects, actions, relations, self, and culture acquired
through experience. The neural systems that store and retrieve this information have been studied for many
years, but a consensus regarding their identity has not been reached. Using strict inclusion criteria, we
analyzed 120 functional neuroimaging studies focusing on semantic processing. Reliable areas of activation
in these studies were identified using the activation likelihood estimate (ALE) technique. These activations
formed a distinct, left-lateralized network comprised of seven regions: posterior inferior parietal lobe, middle
temporal gyrus, fusiform and parahippocampal gyri, dorsomedial prefrontal cortex, inferior frontal gyrus,
ventromedial prefrontal cortex, and posterior cingulate gyrus. Secondary analyses showed specific
subregions of this network associated with knowledge of actions, manipulable artifacts, abstract concepts,
and concrete concepts. The cortical regions involved in semantic processing can be grouped into three broad
categories: posterior multimodal and heteromodal association cortex, heteromodal prefrontal cortex, and
medial limbic regions. The expansion of these regions in the human relative to the nonhuman primate brain
may explain uniquely human capacities to use language productively, plan, solve problems, and create
cultural and technological artifacts, all of which depend on the fluid and efficient retrieval and manipulation
of semantic knowledge.
Key words: semantics, brain mapping, fMRI, positron emission tomography, meta-analysis
Binder et al.
The human brain has an enormous capacity to acquire knowledge from experience. The characteristic
shapes, colors, textures, movements, sounds, smells, and actions associated with objects in the environment,
for example, must all be learned from experience. Much of this knowledge is represented symbolically in
language and underlies our understanding of word meanings. These relationships between words and the
stores of knowledge they signify are known collectively as the semantics of a language (Bréal, 1897). In this
article, we use the more general term semantic processing to refer to the cognitive act of accessing stored
knowledge about the world.
For most languages, semantic properties of words are readily distinguished from their structural
properties. For example, words can have both spoken (phonological) and written (orthographic) forms, but
these surface forms are typically related to word meanings only through the arbitrary conventions of a
particular vocabulary. There is nothing, for example, about the letter sequences DOG or CHIEN that
inherently links these sequences to a particular concept. Conversely, it is trivial to construct surface forms
(e.g., CHOG) that possess all of the phonological and orthographic properties of words in a particular
language, but which have no meaning in that language. In this article, we hold to a simple, operational
distinction between (a) the processes of analyzing surface form (phonology, orthography), and (b) semantic
processes, which concern access to knowledge not directly represented in the surface form.
Semantic processing is a defining feature of human behavior, central not only to language, but also to our
capacity to access acquired knowledge in reasoning, planning, and problem-solving. Impairments of
semantic processing figure in a variety of brain disorders such as Alzheimer disease, semantic dementia,
fluent aphasia, schizophrenia, and autism. The neural basis of semantic processing has been studied
extensively by analyzing patterns of brain damage in such patients (e.g., Alexander et al., 1989; Chertkow et
al., 1997; Damasio et al., 2004; Dronkers et al., 2004; Gainotti, 2000; Hart and Gordon, 1990; Hillis et al.,
2001; Mummery et al., 2000; Tranel et al., 1997). On the whole, this evidence suggests a broadly distributed
neural representation, with particular reliance on inferotemporal and posterior inferior parietal regions.
Semantic processing has also been addressed in a large number of functional neuroimaging studies
conducted on healthy volunteers, using positron emission tomography (PET) and functional magnetic
resonance imaging (fMRI). The aim of the present study is to conduct a meta-analysis of this functional
neuroimaging research, which now includes over 500 published studies. Several excellent reviews on
neuroimaging studies of semantic processing have been presented previously, which focused mainly on the
evidence for organization of object knowledge by taxonomic categories (Bookheimer, 2002; Damasio et al.,
2004; Gerlach, 2007; Joseph, 2001; Martin and Chao, 2001; Thompson-Schill, 2003). The present analysis
differs from these prior efforts in including a larger number and broader range of studies, in adopting specific
inclusion and exclusion criteria for identifying semantic processing experiments, and in the construction of
probabilistic maps for summarizing the data.
Considered for inclusion were any PET or fMRI studies in which words (either spoken or written) were
used as stimulus materials. Thus, the goal of the current study is to identify brain systems that access
meaning from words. This approach contrasts with several previous reviews that included and even
emphasized studies in which object pictures were used to elicit knowledge retrieval (Damasio et al., 2004;
Gerlach, 2007; Joseph, 2001; Martin and Chao, 2001). Our focus on linguistic materials reflects our present
concern, which is not how objects are recognized, but rather how conceptual knowledge is organized and
accessed. Although the knowledge stores underlying word comprehension may be activated similarly during
word and object recognition tasks, there is also evidence that these two semantic access routes are not
identical. For example, object recognition engages a complex, hierarchical perceptual stream that encodes
progressively more abstract representations of object features and their spatial relationships (Humphreys and
Forde, 2001; Logothetis and Sheinberg, 1996; Marr, 1982; Tanaka et al., 1991). Certainly not all of these
perceptual representations are encoded in language or even available to awareness. At present it is not clear
that comprehension of a word necessarily entails activation of a detailed perceptual representation of the
object to which it refers, at least not to the same degree as that evoked by the object itself. In fact, many
functional neuroimaging studies suggest different patterns of activation during matched word and picture
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Table 1. Example contrasts in which the semantic and control conditions are not matched on ortho-
graphic or phonological processing demands. The "living/nonliving" task is intended to represent a
variety of similar semantic decision tasks. All examples are from the studies reviewed.
Stimulus, e.g. Task
horse Read silently
horse Read aloud
horse Read silently
horse Does it have an ascender?
horse Is it living or nonliving?
horse, zebra Are they related in meaning?
"horse" Is it living or nonliving?
"horse" Is it living or nonliving?
"horse" Is it living or nonliving?
/ / / / /
distorted speech Listen
distorted speech Is it a male or female voice?
"ba" Is it "ba" or "pa"?
Does it have an ascender?
Does it have more 4 letters?
Are they identical?
Is it high or low in pitch?
recognition tasks (Bright et al., 2004; Chee et al., 2000; Gates and Yoon, 2005; Gorno-Tempini et al., 1998;
Hasson et al., 2002; Moore and Price, 1999b; Reinholz and Pollmann, 2005). The existence of patients with
profound visual object recognition disorders but relatively intact word comprehension also argues against a
complete overlap between the knowledge systems underlying word and object recognition (Davidoff and De
Bleser, 1994; Farah, 1990; Lissauer, 1889; Warrington, 1985). In the interest of maintaining a clear focus on
the processing of concepts rather than percepts, we thus elected to include in this analysis only those
experiments that used words as stimuli.
Specific exclusion criteria are a critical feature of the present study. The numerous published
neuroimaging studies concerning semantic processing address a variety of specific topics and employ a wide
range of tasks and task comparisons (here referred to as contrasts). The authors of these studies often began
from very different theoretical perspectives and varied in their interpretation of task demands. One approach
to selecting material for a meta-analysis would have been to include any study considered by the original
authors to have addressed semantic processing, as indicated, for example, by the study title or list of
keywords. We found during initial attempts to review these reports, however, that markedly different, largely
non-overlapping activation patterns were frequently observed across studies. Furthermore, this discordance
was related mainly to variability in task selection and the type of task contrast used. Three problematic
features of this literature were of particular interest and were found with some regularity. First, many studies
employed contrasting tasks that differed on phonological or orthographic processing demands in addition to
semantic processing demands (see examples in Table 1). It is a general principle of functional neuroimaging
studies, and one that warrants strong emphasis, that the "activations" measured using these methods are in
fact representations of the relative differences in neural activity between two or more brain states. Thus, the
pattern of activated brain regions observed in a study putatively targeting semantic processes depends not
only on the cognitive processes elicited by the semantic task, but also on the processes elicited, or not
elicited, by the comparison task. If the comparison task does not make demands on phonological and
orthographic processes that approximate those made by the semantic task (as is the case, for example, with
any control task involving unpronounceable or un-nameable stimuli), then the resulting activation is as likely
to reflect phonological or orthographic processes as semantic processes. Such contrasts were excluded from
the present analysis.
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Table 2. Examples for which the contrasted conditions are not matched on general task difficulty due to
task set, word frequency, ambiguity, or priming effects. All examples are from the studies reviewed.
Hard Word Condition
Stimulus, e.g. Task
horse Generate associated word
- Generate names of animals
horse Is it living or nonliving?
impala Is it living or nonliving?
horse Is it living or nonliving?
horse Is it living or nonliving?
horse, zebra Are they related in meaning?
house, zebra Are they related in meaning?
house, zebra Are they related in meaning?
bank, river Are they related in meaning?
house, zebra Is the second item a word?
Easy Word Condition
horse (repeated) Is it living or nonliving?
zebra Does it contain the letter 'a'?
horse, horse Are they identical?
horse, horse Are they the same font size?
horse, ZEBRA Are they the same case?
lake, river Are they related in meaning?
horse, zebra Is the second item a word?
Generate months of the year
Is it living or nonliving?
Functional neuroimaging measurements are very sensitive to differences in response time, accuracy, and
level of effort between tasks (see, e.g., Adler et al., 2001; Binder et al., 2004; Binder et al., 2005a; Braver et
al., 2001; Braver et al., 1997; Desai et al., 2006; Gould et al., 2003; Honey et al., 2000; Jonides et al., 1997;
Lehmann et al., 2006; Mitchell, 2005; Sabsevitz et al., 2005; Tregallas et al., 2006; Ullsperger and von
Cramon, 2001). Such differences pose a problem if there are cognitive systems supporting general task
performance functions that are modulated by task difficulty. Likely examples of such domain-general
systems include a sustained attention network for maintaining arousal, a selective attention system for
focusing neural resources on a particular modality or sensory object in the environment (e.g., a visual
display), a working memory system for keeping task instructions and task-relevant sensory representations
accessible, a response selection mechanism for mapping the contents of working memory to a response, a
response inhibition system for preventing premature or prepotent responses from being made in error, and an
error monitoring system for adjusting response criteria and response time deadlines to minimize such errors.
These systems, located mainly in frontal, anterior cingulate, and dorsal parietal cortices (Carter et al., 1999;
Corbetta et al., 1998; Duncan and Owen, 2000; Grosbras et al., 2005; Owen et al., 2005), are necessary for
completing any task. If this is the case, and if the level of activation in these systems depends on general task
demands, then it follows that activation can never be attributed with certainty to semantic processing when
this activation has resulted from a contrast in which general task demands differ. Such contrasts (see
examples in Table 2) were therefore excluded from the present analysis.
A second, more prevalent problem concerns contrasts in which the conditions differed in task difficulty.
studies used states described as "passive" or "resting" in which subjects are given either no task, a minimally
demanding task such as fixating a point in the visual field, or a nominal task for which compliance is
uncertain and unknowable (e.g., "clear your mind", "focus on the scanner sounds"). Although such
conditions can be useful as a low-level baseline, particularly for sensory stimulation studies, their use in
semantic studies is problematic. Most people report experiencing vivid and memorable thoughts and mental
images during such conscious, attentive states (Antrobus et al., 1966; Binder et al., 1999; Giambra, 1995;
James, 1890; McKiernan et al., 2006; Pope and Singer, 1976; Singer, 1993). We argued previously that the
processes supporting such "task-unrelated thoughts" are essentially semantic, since they depend on activation
and manipulation of acquired knowledge about the world (Binder et al., 1999; McKiernan et al., 2006). If
A final issue concerns the interpretation of states in which no overt task is required. Many neuroimaging
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such states involve semantic processing, their use as a baseline runs the risk of subtracting away any
semantic processing elicited by an overt semantic task. Such a contrast (an active semantic task compared to
no task) also violates the stipulations, discussed above, that task conditions be matched on low-level
processing demands and on overall difficulty, and would thus be expected to produce "false positive"
activation of surface form processing and general executive systems. Such contrasts were therefore excluded
from the present analysis. Also excluded were contrasts in which two conditions that both involve passive
stimulation were compared, such as passively listening to words versus pseudowords. In these cases, the
processes underlying generation of task-unrelated thoughts, which we consider to be largely semantic in
nature, would predominate in both of the conditions being contrasted, resulting in little or no relative
activation of semantic systems.
In summary, the present meta-analysis represents a critical review in which selection criteria are based on
specific theoretical distinctions between semantic and surface form processing, and between semantic
processes and more general processes required for task execution. Our aim is thus to identify brain regions
that contribute specifically to the semantic component of word recognition, i.e., the activation of stored
conceptual knowledge, apart from the accompanying analysis of surface form or generation of an overt task
Materials and Methods
Study Identification. Procedures for identifying candidate studies were designed to be as inclusive as
possible. Candidate studies were identified through searches of the PubMed, Medline, and PsychINFO
online databases for the years 1980 through 2007. This search was conducted using the following Boolean
operation applied to title, abstract, and keyword fields: <'brain mapping' OR 'functional magnetic resonance
imaging' OR 'fMRI' OR 'positron emission tomography' OR 'PET' OR 'neuroimaging'> AND <'semantics'
OR 'semantic memory' OR 'category' OR 'conceptual knowledge'>. This step yielded 2832 unique items.
Abstracts from these studies were then initially screened to identify those that used either fMRI or PET and
included healthy human participants, yielding 790 articles. Abstracts from these articles were then evaluated
in more depth to identify experiments that used word stimuli and included either a general or specific
semantic contrast. If this information could not be determined from the abstract, the article was also
included. This second screening step yielded 431 articles. Online tables of contents and abstracts for selected
journals focusing on cognition and neuroimaging, including Brain and Language, Human Brain Mapping,
Journal of Cognitive Neuroscience, and NeuroImage, and previously published reviews of semantic
neuroimaging studies (Bookheimer, 2002; Cabeza and Nyberg, 2000; Damasio et al., 2004; Devlin et al.,
2002b; Gerlach, 2007; Joseph, 2001; Martin and Caramazza, 2003; Martin and Chao, 2001; Price and
Friston, 2002; Thompson-Schill, 2003; Vigneau et al., 2006) were then manually searched back to 1995 for
relevant articles, yielding an additional 72 items. Finally, any additional relevant articles known to the
authors, cited in the initial set of articles, or encountered during the review process were added to the list,
resulting in a total of 520 articles that underwent full review.
The full review process included a complete reading of each article by one of the four authors, followed
by application of the following inclusion criteria:
1. fMRI or PET study involving healthy adult human participants
2. use of spoken or written word stimuli
3. use of one or more semantic contrasts (see definition below)
4. incorporation of controls for sensory and word-form (orthographic and phonological) processes
5. incorporation of controls for general executive and response processes
6. use of a control task with overall difficulty at least as great as the semantic task
7. image data acquired over all or most of the supratentorial brain
8. availability of peak activation coordinates from a group activation map
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In an effort to be as inclusive as possible, criteria 6 and 7 were not applied in a rigid manner. For example,
studies that did not include adequate documentation of task performance were included if the reviewer
judged the tasks to be approximately equal in difficulty. Studies were also included if the control task was
more difficult than the semantic task, following the logic that relative activation during the easier semantic
task could not in such cases be due to greater demands on general executive processes. Criterion 7 was
applied to avoid sampling bias for particular brain regions, but studies were included if nearly all of the
cerebrum was imaged. Cases in which adherence to criteria was ambiguous were reviewed by a second
author to reach a consensus view.
All studies included after full review by one of the authors were then reviewed by a second author to
confirm eligibility. Rare disagreements were resolved by further discussion among the authors.
Types of Semantic Contrasts. Two types of contrasts are relevant to the goal of identifying activation due to
semantic processing. The first, which we refer to as a general semantics contrast, follows from the
operational distinction between word structure and meaning discussed above. A general contrast is one
between a condition that elicits high levels of access to word meaning and a condition that elicits lower
levels of access to word meaning. The contrast must include controls for processing word structure
(phonology and orthography) as well as for general executive and response processes. The three most
common general contrasts were:
(i) Words vs. Pseudowords. Pseudowords are spoken or written stimuli with structural properties similar to
real words. The task performed on the words and pseudowords is nominally equivalent (for example, an
orthographic or phonological matching task, reading aloud, or lexical decision), such that the main
difference emphasized by the contrast is the additional access to meaning in the word condition.
(ii) Semantic Task vs. Phonological Task. This contrast involves a comparison between different tasks, one
of which focuses attention on semantic aspects of the stimuli (e.g., a semantic decision task) and the
other on structural (usually phonological) attributes of the stimuli (e.g., a rhyme decision or phoneme
detection task). Typically, all the stimuli are words, thus the contrast emphasizes the additional access to
word meaning elicited by the task in the semantic condition. Combinations of contrasts (i) and (ii) also
occur, in which a semantic task involving words is compared to a phonological task involving
pseudowords (e.g., Binder et al., 1999; Cappa et al., 1998; Démonet et al., 1992).
(iii) High vs. Low Meaningfulness. This contrast is a variation on (i), in which the contrasting stimuli differ
in meaningfulness but are not words and pseudowords. Some examples include names of famous vs.
unknown people, related vs. unrelated word pairs, and meaningful vs. nonsensical sentences.
The other type of semantic contrast, which we designate specific, entails a comparison between
hypothetically distinct types of conceptual knowledge. The aim of such studies is not to delineate the entire
semantic processing system, but rather to identify putative functional subdivisions within the semantic
system. Many such studies, for example, involve comparisons between concrete objects from different
categories (e.g., animals vs. tools). Such studies are relevant to our aims because they contribute to the
identification of brain regions involved specifically in semantic processing. Because we are not concerned
here with particular functional subdivisions within the semantic system, activation data from both sides of
the contrast (e.g., activation for animals > tools and for tools > animals) were included. As with the general
contrasts, several variations can be distinguished based on whether the contrast pertains to stimulus or task
manipulations. For example, in experiments involving a stimulus manipulation, a constant task is used
(usually a semantic decision) with two (or more) contrasting categories of stimuli. In experiments involving
a task manipulation, the attentional focus of the participant is switched to different semantic attributes (e.g.,
color, action, size) of the same concepts using changes in task set.
We report here results obtained from separate analyses of the general and specific contrasts as well as a
global analysis combining all studies. The specific foci were classified according to type of semantic
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Figure 1. Distribution of the included
studies by year published.
knowledge represented by each contrast, and separate analyses were conducted for each specific knowledge
type for which sufficient data were available.
Data Analysis. For each study reviewed, all reported contrasts that met inclusion criteria were included in
the analysis. For each such contrast, the reviewer recorded the number of participants contributing to the
activation map, the imaging modality used, the type of contrast, a brief description of the stimuli and tasks
used in the contrast, the standard space to which the data were normalized, all reported coordinate locations
for activation peaks, the Z values associated with each peak (if available), and the published table from
which the coordinates were copied.
All coordinates were converted to a single common stereotaxic space. The studies were evenly divided
between those that reported coordinates in the standard space of Talairach & Tournoux (1988) and those that
used a variation of MNI space (Evans et al., 1993). We converted all MNI coordinates to the Talairach &
Tournoux (1988) system using the "icbm2tal" transform (Lancaster et al., 2007). This transform reduces the
bias associated with reference frame and scale in MNI/Talairach conversion.
Probabilistic maps of the resulting sets of coordinates were constructed using the "Activation Likelihood
Estimate" (ALE) method (Turkeltaub et al., 2002), implemented in the GingerALE software package (Laird
et al., 2005) (available at www.brainmap.org), using an 8 mm FWHM 3D Gaussian point spread function
and a spatial grid composed of 2 x 2 x 2 mm voxels. This method treats each reported focus as the center of a
Gaussian probability distribution. The 3D Gaussian distributions corresponding to all foci included in a given
analysis are summed to create a whole-brain map that represents the overlap of activation peaks at each
voxel, referred to as the ALE statistic. Subsequent analysis is restricted to a brain volume mask (Kochunov et
al., 2002) distributed with the GingerALE software. To determine the null distribution of the ALE statistic
for each analysis, a Monte Carlo simulation with 10,000 iterations was performed, in which each iteration
consisted of a set of foci equal in number to the observed data, placed at random locations within the analysis
volume and convolved with the same point spread function (Laird et al., 2005). Based on these null
distributions, the ALE statistic maps for each analysis are converted to voxel-wise probability maps.
The probability of chance formation of supra-threshold clusters was then determined by Monte Carlo
simulation using in-house software, with 1000 iterations. Each iteration contained randomly located foci
equal in number to the observed data and convolved with the same point spread function. The ALE map was
then computed for each iteration, and the number and size of voxel clusters were recorded after thresholding
each simulated data set at various voxelwise ALE thresholds. ALE maps from each of the observed data sets
were then thresholded at an ALE value that yielded a corrected mapwise α < 0.05 after removing clusters
smaller than 1000 µl. For visualization of probability values at each voxel, these corrected ALE maps were
applied as masks on the probability maps generated by the GingerALE software. These thresholded
probability maps are shown in Figures 3 through 6.
The initial search and screening procedures identified 520
articles, which were subsequently reviewed in detail. A
total of 120 articles met inclusion criteria and provided 187
semantic contrasts. Figure 1 shows a breakdown of these
studies by year published. A list of the included studies is
provided in Appendix 1. Six of the included studies (Devlin
et al., 2002b; Giraud and Price, 2001; Liu et al., 2006;
Paulesu et al., 2000; Pilgrim et al., 2002; Tyler et al., 2001)
met all criteria, but no activation was observed for the
semantic contrasts of interest. Among the 400 excluded
studies, 10 used techniques other than fMRI or PET, or
studied special subject populations. Six were reviews or re-
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analyses of previously published data. About 20% (82) of the excluded studies did not include any semantic
contrasts, 13% (52) did not use word stimuli, 9% (37) used a resting or passive condition as the only control,
31% (127) used active control tasks that were less difficult than the semantic task, and 16% (66) used active
control tasks that did not control for word-form (orthographic or phonological) processing. In 17% (69) of
the excluded studies no group activation data were reported for the semantic contrast of interest, or foci were
reported only for a priori regions of interest.
Of the 187 contrasts that met all inclusion criteria, 87 were of the general type and 100 of the specific
type; 126 used fMRI and 61 used PET. These studies collectively involved 1642 participants1 and yielded
1145 activation foci (691 general and 454 specific).
All Semantic Contrasts. Figure 2 shows activation foci from all of the included studies projected onto an
inflated surface model of the cerebral cortex (see Figures 1 and 2 in the Supplemental Material for similar
images color-coded by type of contrast). Of the 1145 published foci, 10 were located in the cerebellum and
are therefore not shown. About 68% (771) of the foci were in the left cerebral hemisphere (x < 0) and 32%
(362) in the right hemisphere (x > 0), indicating moderate left hemisphere lateralization. Foci were located
throughout the brain, but with strong clustering in some regions, particularly the left inferior parietal lobe.
Areas with notably few foci included the precentral and postcentral gyri bilaterally, primary and secondary
visual cortices, superior parietal lobules, frontal eye fields, and dorsal anterior cingulate gyri. There was a
clear line of demarcation along the lateral bank of the left intraparietal sulcus, separating a large and dense
cluster of foci in the inferior parietal lobe from uninvolved cortex in the intraparietal sulcus and superior
lateralized to the left hemisphere and widely distributed in frontal, temporal, parietal, and paralimbic areas.
Seven principal regions showed a high likelihood of activation across studies: (i) the angular gyrus (AG) and
adjacent supramarginal gyrus (SMG); (ii) the lateral temporal lobe, including the entire length of the middle
temporal gyrus (MTG) and posterior portions of the inferior temporal gyrus (ITG); (iii) a ventromedial
region of the temporal lobe centered on the mid-fusiform gyrus and adjacent parahippocampus; (iv)
dorsomedial prefrontal cortex in the superior frontal gyrus (SFG) and adjacent middle frontal gyrus (MFG);
(v) the inferior frontal gyrus (IFG), especially the pars orbitalis; (vi) ventromedial and orbital prefrontal
The thresholded ALE probability map based on all 1145 foci is shown in Figure 3. Activations were
Figure 2. 1135 published activation foci from the included studies projected onto an inflated cortical
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cortex; and (vii) the posterior cingulate gyrus and adjacent ventral precuneus. Weaker activations occurred at
homologous locations in the right hemisphere, principally the AG, posterior MTG, and posterior cingulate
gyrus. See Appendix 2 for details regarding activation of each of these regions in each of the included
Figure 3. ALE map of all semantic foci, thresholded at whole-brain corrected p < 0.05. Activations are
displayed on serial sagittal sections through the stereotaxic space of Talairach and Tournoux (1988) at 4-
mm intervals, with slice locations given at the lower left of each image. Green lines indicate the stereotaxic
y and z axes. Tick marks indicate 10-mm intervals. The color scale indicates voxel-wise probability values
of p < 0.01 (red), p < 0.001 (orange), and p < 0.0001 (yellow).
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General Contrasts. Figure 4 shows the thresholded ALE map for the 691 general semantic foci. This map is
very similar to the one derived from all foci, though with generally smaller clusters. Activation in the IFG is
more clearly localized to the pars orbitalis. Activation in the left fusiform gyrus extends somewhat farther
anteriorly, and there is more extensive involvement of the left ventromedial prefrontal region.
Specific Contrasts. The specific contrasts were further categorized as to the putative type of semantic
knowledge examined by each. Many of these types (e.g., auditory, gustatory, olfactory, tactile, visual motion,
characteristic object location, emotion, causation, self knowledge, etc.) were examined in only a few studies
and thus had too few activation foci to examine separately by meta-analysis. There were 10 studies that
Figure 4. ALE map of 691 foci resulting from general semantic contrasts (see Methods for details).
Formatting and thresholding as in Figure 3.
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examined contrasts between living things (usually animals) and manipulable artifacts (usually tools) (Cappa
et al., 1998; Goldberg et al., 2006; Grossman et al., 2002a; Kounios et al., 2003; Laine et al., 2002;
Mummery et al., 1998; Mummery et al., 1996; Perani et al., 1999; Thioux et al., 2005; Wheatley et al.,
2005), providing 41 "living" and 29 "artifact" foci. "Living" foci showed no significant overlap in the ALE
analysis. As shown in Figure 5, "artifact" foci showed significant overlap at the left lateral temporal-occipital
junction, where posterior MTG and ITG meet anterior occipital cortex (roughly BA 37), and in the ventral
left SMG (BA 40) near the junction with STG.
There were 10 studies that examined action knowledge relative to other types (Baumgaertner et al., 2007;
Boronat et al., 2005; Davis et al., 2004; Eschen et al., 2007; Martin et al., 1995; Noppeney et al., 2005;
Noppeney and Price, 2003; Ruschmeyer et al., 2007; Tomasino et al., 2007; Tyler et al., 2003b), providing
40 "action" foci. Significant overlap for these foci occurred in the ventral left SMG and posterior left MTG
(BA 37). As shown in Figure 5, the SMG focus overlaps the SMG region observed in the "artifact" studies.
The posterior MTG cluster associated with action knowledge was slightly dorsal and lateral to the temporal-
occipital cluster of "artifact" foci.
knowledge of concrete objects derived from sensory-motor experience) and verbally-encoded knowledge
(i.e., knowledge acquired through language) (Paivio, 1986). The majority of these studies used contrasts
between concrete and abstract concepts (Bedny and Thompson-Schill, 2006; Binder et al., 2005a; Binder et
al., 2005b; Fiebach and Friederici, 2003; Fliessbach et al., 2006; Giesbrecht et al., 2004; Grossman et al.,
2002b; Jessen et al., 2000; Noppeney and Price, 2004; Sabsevitz et al., 2005; Wallentin et al., 2005b;
Whatmough et al., 2004; Wise et al., 2000), while a few others examined this distinction using tasks that
required explicit knowledge of perceptual vs. verbal facts (Ebisch et al., 2007; Fletcher et al., 1995; Lee and
Dapretto, 2006; Noppeney and Price, 2003). Significant overlap for the 113 "perceptual" foci occurred in the
AG bilaterally, left mid-fusiform gyrus, left dorsomedial prefrontal cortex, and left posterior cingulate
(Figure 6). Significant overlap for the 34 "verbal" foci occurred in the left IFG (mainly pars orbitalis) and left
anterior superior temporal sulcus.
There were 17 studies that examined the distinction between perceptually-encoded knowledge (i.e.,
Figure 5. ALE map of 29 foci resulting from contrasts targeting knowledge of manipulable artifacts (top)
and ALE map of 40 foci from contrasts targeting knowledge of actions (bottom). Formatting and
thresholding as in previous figures.
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PET and fMRI activation studies are based, directly or indirectly, on differences between two or more brain
activity states. The "activation maps" produced by these methods represent relative changes in brain activity,
not absolute activity levels. Interpretation of such activations, therefore, cannot be based solely on the
processing demands of one of the task states, but rather requires a joint analysis of the processing demands
elicited by each of the task states and the degree to which they differ. The goal of the present meta-analysis
Figure 6. ALE maps derived from contrasts comparing perceptual (i.e., pertaining to sensory attributes of
concrete objects) to verbal (i.e., abstract or encyclopedic) knowledge. The 113 foci representing perceptual
knowledge are shown in warm colors, and the 34 foci representing verbal knowledge are shown in cool
colors. Formatting and thresholding as in previous figures.
Binder et al.
was to clarify the brain regions specifically involved in semantic processing, a topic that has been the source
of much debate (for a sample of conflicting views, see Démonet et al., 1993; Head, 1926; Hillis et al., 2001;
Martin and Caramazza, 2003; Patterson et al., 2007; Petersen et al., 1988; Thompson-Schill et al., 1997;
Tranel et al., 1997; Wernicke, 1874). In contrast to previous meta-analyses on this topic, we used explicit
criteria to define activation representing semantic processing; these criteria referred to differences between
the stimuli and tasks used to generate each activation map. To be considered for inclusion, a contrast had to
involve a difference in either the degree to which stored knowledge was accessed ("general" contrast) or the
specific type of knowledge accessed ("specific" contrast). These differences in stored knowledge access
could be elicited through manipulation of stimulus characteristics (e.g., words vs. pseudowords, meaningful
vs. meaningless sentences, famous vs. unfamiliar names, animals vs. tools), through manipulation of the
subject's attention via task instructions (e.g., semantic vs. phonological decisions, color vs. action decisions),
Another central feature of the present study that distinguishes it from previous reviews was the
application of strict exclusion criteria. To minimize contamination of the results by non-semantic processes,
studies were excluded if the semantic condition of interest also made greater demands on low-level sensory,
orthographic, phonological, syntactic, working memory, attentional, response selection, or motor processes.
(Note that studies were excluded only when the semantic condition of interest made greater demands on
these processes, not when the comparison condition made greater demands.) The two most common reasons
for exclusion were inadequate controls for phonological processing due to use of unpronounceable or
nonlinguistic stimuli in the comparison condition, and inadequate controls for general task performance
processes. The latter type of exclusion was the most common and warrants further discussion, since in our
view many prior studies have not clearly distinguished knowledge access processes from more general
cognitive processes that are not specific to semantic tasks. The critical point we wish to make is that all
consciously executed, goal-directed tasks require at minimum a set of domain-general processes that include
maintenance of attention, direction of attention to relevant information (external or internal), maintenance of
this relevant information in a short-term memory store, maintenance of the task goal and task procedures in
working memory, decision, response selection, and error monitoring. These processes are necessary for all
goal-directed cognitive tasks, including semantic tasks, however our aim here was to identify brain regions
engaged specifically in semantic processes. Thus it was critical to exclude activation contrasts in which the
semantic condition of interest engaged these processes to a greater degree than the comparison condition,
including all contrasts in which the semantic task was more difficult than the comparison task. In addition to
the examples given in the introduction, another illustrative case are the many studies involving either
semantic priming or repetition suppression, in which unprimed or new words are compared to primed or
repeated words (e.g., Copland et al., 2003; Matsumoto et al., 2005; Mummery et al., 1999; Rossell et al.,
2001; Rossell et al., 2003; Wagner et al., 2000; Wible et al., 2006; Yasuno et al., 2000). One underlying
hypothesis of these studies is that unprimed or new words require more semantic processing than primed or
repeated words that have already been processed, and behavioral data uniformly support this hypothesis by
showing longer response times for the unprimed/new items. Though it is likely that unprimed/new items
elicit more extensive semantic processing, it is also an inescapable fact, in our view, that they also require
greater attentional and executive resources. Exclusion of these studies from the present meta-analysis was
therefore necessary to isolate the semantic processes of interest, even though the activation maps from these
contrasts probably do reflect, at least in part, semantic processes.
The semantic system of the human brain
The meta-analysis links the following seven brain regions with semantic processes: (i) posterior inferior
parietal lobe (AG and portions of SMG); (ii) lateral temporal cortex (MTG and portions of ITG); (iii) ventral
temporal cortex (mid-fusiform and adjacent parahippocampal gyrus); (iv) dorsomedial prefrontal cortex; (v)
inferior frontal gyrus; (vi) ventromedial prefrontal cortex; and (vii) posterior cingulate gyrus. One common
attribute of these regions is their likely role in high-level integrative processes. All are known to receive
Binder et al.
extensively processed, multimodal and supramodal input. Recent studies show that even cortical regions
formerly considered "unimodal" receive multisensory inputs (Cappe and Barone, 2005; Schroeder and Foxe,
2004), blurring the traditional distinction between unimodal and heteromodal cortex (Mesulam, 1985). A
useful qualitative distinction can still be drawn, however, between modal cortex, where processing reflects a
dominant sensory or motor modality, and amodal cortex, where input from multiple modalities is more
nearly balanced and highly convergent. For continuity with previous work, we refer to these latter regions as
heteromodal, though alternative terms such as supramodal or amodal are perhaps equally valid. The human
semantic system thus corresponds in large measure to the network of parietal, temporal, and prefrontal
heteromodal association areas, which are greatly expanded in the human relative to the nonhuman primate
brain (Brodmann, 1994/1909; Geschwind, 1965; von Bonin, 1962). Evidence supports the subdivision of this
network into posterior (temporal/parietal) and frontal components corresponding to storage and retrieval
aspects of semantic processing (see discussion below). A second general feature of the semantic system is
that it is lateralized to the left hemisphere, though with some bilateral representation (particularly in the AG
and posterior cingulate gyrus). The following discussion reviews each of the nodes in this network in greater
detail, examining their anatomical characteristics and likely functional roles based on imaging and
Angular gyrus. The most dense concentration of activation foci was in the posterior aspect of the left
inferior parietal lobule, a region known historically as the angular gyrus or pli courbe (French: "curved
gyrus") (Déjerine, 1895). The AG consists of cortex surrounding the parietal extension of the superior
temporal sulcus; it is formed essentially by the continuation of the superior and middle temporal gyri into the
inferior parietal lobe. Its medial boundary is the intraparietal sulcus, which separates it from the superior
parietal lobule. The anterior boundary with the SMG is defined by the first intermediate sulcus of Jensen,
though this landmark is not always present. Its posterior boundary with the occipital lobe is not well defined.
The AG corresponds approximately to BA 39 and in recent cytoarchitectonic studies to PGa and PGp
(Caspers et al., 2006). This region is practically non-existent in lower primates (Brodmann, 1994/1909) and
is greatly expanded in the human brain relative to its probable homolog in the macaque monkey, area PG/7a
(Hyvarinen, 1982; von Bonin and Bailey, 1947). It is anatomically connected almost entirely with other
association regions and receives little or no direct input from primary sensory areas (Andersen et al., 1990;
Cavada and Goldman-Rakic, 1989a, 1989b; Hyvarinen, 1982; Mesulam et al., 1977; Seltzer and Pandya,
Though we use the term angular gyrus, a variety of other labels for activations in this region were
encountered in the studies reviewed. Despite its location in the parietal lobe, many refer to it erroneously as
the middle temporal gyrus. Others use the terms temporoparietal junction or temporal-parietal-occipital
cortex. These concatenated terms strike us as unnecessarily imprecise in this context and should probably be
reserved for describing large activations that straddle the boundaries between lobes or extend beyond the
parietal lobe. AG activations were also not infrequently mislabeled with BA numbers 40 and 19.2
On the other hand, some of the activation foci in this large cluster probably lie outside the AG. Several
are just posterior, in what is likely BA 19. Given this evidence from functional imaging, it is possible that at
least some cortex in the anterior occipital lobe classically identified as BA 19 may serve a semantic rather
than a modal visual associative function. Alternatively, BA 39 may extend farther posteriorly than is
typically portrayed. Several other foci in this large cluster were in the SMG (BA 40) just anterior to the AG.
Lesions of the left AG produce a variety of cognitive deficits, including alexia and agraphia (Benson,
1979; Cipolotti et al., 1991; Déjerine, 1892), anomia (Benson, 1979), transcortical sensory aphasia (Berthier,
1999; Damasio, 1981; Kertesz et al., 1982; Rapcsak and Rubens, 1994), sentence comprehension impairment
(Dronkers et al., 2004), acalculia (Benton, 1961; Cipolotti et al., 1991; Dehaene and Cohen, 1997;
Gerstmann, 1940), visual-spatial and body schema disorders (Critchley, 1953; Gerstmann, 1940), ideomotor
apraxia (Buxbaum et al., 2005; Haaland et al., 2000; Jax et al., 2006), and dementia (Benson et al., 1982).
Perhaps the main conclusion to be drawn from this evidence is that the AG likely plays a role in complex
information integration and knowledge retrieval. Given its anatomical location adjoining visual, spatial,
Binder et al.
auditory, and somatosensory association areas, the AG may be the single best candidate for a high-level,
supramodal integration area in the human brain (Geschwind, 1965). Several functional imaging studies have
shown that the AG is activated in response to semantically anomalous words embedded in sentences,
suggesting that it plays a role in integrating individual concepts into a larger whole (Friederici et al., 2003;
Newman et al., 2003; Ni et al., 2000). One recent fMRI study found that during auditory sentence
comprehension, the AG, alone among the regions activated, showed a late activation relative to baseline that
began at the end of the sentence and occurred only when the constituent words could be integrated into a
coherent meaning (Humphries et al., 2007). Three studies comparing processing of connected discourse to
processing of unrelated sentences or phrases have also shown activation of the AG (Fletcher et al., 1995;
Homae et al., 2003; Xu et al., 2005) Considering these various lines of evidence, we propose that the AG
occupies a position at the top of a processing hierarchy underlying concept retrieval and conceptual
integration. Though it is involved in all aspects of semantic processing, it may play a particular role in
behaviors requiring fluent conceptual combination, such as sentence comprehension, discourse, problem
solving, and planning.
Lateral and ventral temporal cortex. The meta-analysis identified several regions in the lateral and
ventral left temporal lobe, including most of the MTG and portions of the ITG, fusiform gyrus, and
parahippocampus. MTG, ITG, and ventral temporal lobe have often been considered modal visual
association cortex by analogy with lateral and ventral temporal cortex in the macaque monkey (Mesulam,
1985; von Bonin and Bailey, 1947), however the present analysis argues against such an interpretation in the
human brain. In fact, many functional imaging studies have demonstrated activation of these regions by
auditory stimuli, particularly during language tasks (e.g., Baumgaertner et al., 2007; Binder et al., 1997;
Démonet et al., 1992; Humphries et al., 2006; Noppeney et al., 2003; Orfanidou et al., 2006; Rissman et al.,
2003; Spitsyna et al., 2006; von Kriegstein et al., 2003; Wise et al., 2000; Xiao et al., 2005). Thus, these
regions in the human brain are likely heteromodal cortex involved in supramodal integration and concept
retrieval. As in the inferior parietal lobe, the relative expansion of this high-level integrative cortex in the
temporal lobe has resulted in modal visual cortex being "pushed" posteriorly and reduced in relative surface
area (Orban et al., 2004).
Focal damage to the MTG, though somewhat rare, is strongly associated with language comprehension
and semantic deficits (e.g., Chertkow et al., 1997; Dronkers et al., 2004; Hart and Gordon, 1990; Hillis and
Caramazza, 1991; Kertesz et al., 1993). The anterior ventral temporal lobe, including anterior MTG, ITG,
and fusiform gyrus, is frequently damaged (usually bilaterally) in herpes simplex encephalitis, often resulting
in profound semantic deficits (Gitelman et al., 2001; Kapur et al., 1994a; Lambon Ralph et al., 2007;
Noppeney et al., 2007; Warrington and Shallice, 1984). Semantic dementia, the temporal lobe variant of
frontotemporal dementia, is characterized by progressive degeneration of the anterior ventrolateral temporal
lobes and gradual loss of semantic knowledge (Hodges et al., 1995; Hodges et al., 1992; Jefferies and
Lambon Ralph, 2006; Lambon Ralph et al., 2007; Mummery et al., 2000; Noppeney et al., 2007; Snowden et
al., 1989; Warrington, 1975). Large lesions of the ventral left temporal lobe have been associated with
transcortical sensory aphasia (Alexander et al., 1989; Berthier, 1999; Damasio, 1981; Kertesz et al., 1982). A
striking aspect of many of these temporal lobe injuries is a dissociation in performance across object
categories. Patients with anterior temporal damage, for example, occasionally show greater impairment in
processing concepts related to living things compared to artifacts (Forde and Humphreys, 1999; Gainotti,
2000; Lambon Ralph et al., 2007; Warrington and McCarthy, 1987; Warrington and Shallice, 1984), and the
opposite pattern has been reported in patients with posterior temporal and parietal lesions (Gainotti, 2000;
Hillis and Caramazza, 1991; Warrington and McCarthy, 1987, 1994). These category-related deficits suggest
that the temporal lobe may be a principal site for storage of perceptual information about objects and their
attributes. A large number of functional imaging studies provide support for this hypothesis by showing
selective activation of the posterior lateral temporal lobe by tool and action concepts (Cappa et al., 1998;
Chao et al., 1999; Chao et al., 2002; Davis et al., 2004; Grossman et al., 2002a; Kable et al., 2005; Kable et
al., 2002; Martin et al., 1995; Martin et al., 1996; Moore and Price, 1999a; Mummery et al., 1996; Noppeney
Binder et al.
et al., 2003; Noppeney et al., 2005; Perani et al., 1999; Phillips et al., 2002; Tyler et al., 2003b; Wallentin et
Semantic foci in the fusiform and parahippocampal gyri were concentrated in a relatively focal region
near the mid-point of these gyri, centered at y = -35 in the Talairach-Tournoux system. The specific role of
this region is unknown. It may correspond to the "basal temporal language area" described in electrocortical
stimulation mapping studies (Lüders et al., 1991). It is anterior to activation sites observed in functional
imaging studies comparing different categories of object pictures (e.g., Chao et al., 1999; Chao et al., 2002;
Epstein and Kanwisher, 1998; Gerlach, 2007; Gerlach et al., 2004; Gorno-Tempini et al., 2000; Haxby et al.,
2001; Ishai et al., 1999; Kanwisher et al., 1997; Martin et al., 1996; Moore and Price, 1999a; Okada et al.,
2000; Perani et al., 1995; Tyler et al., 2003a; Whatmough et al., 2002). These more posterior activations
(typically y < -50) are rarely observed in studies using words, suggesting that they arise from systematic
differences between object categories in their constituent visual attributes, which are in turn processed by
somewhat different visual perceptual mechanisms (Hasson et al., 2002; Humphreys and Forde, 2001). Given
its close proximity to these object perception areas, however, several authors have proposed that the mid-
fusiform gyrus plays a particular role in retrieving knowledge about the visual attributes of concrete objects
(Chao and Martin, 1999; D'Esposito et al., 1997; Kan et al., 2003; Simmons et al., 2007; Thompson-Schill et
al., 1999a; Vandenbulcke et al., 2006; Wise et al., 2000). This region is also near the hippocampus and
massive cortical afferent pathways to the hippocampal formation via parahippocampal and entorhinal cortex
(Insausti et al., 1987; Suzuki and Amaral, 1994; Van Hoesen, 1982). It is thus possible that the
parahippocampal component of this cluster acts an interface between lateral semantic memory and medial
episodic memory encoding networks (Levy et al., 2004).
The present analysis provides little evidence for involvement of the STG in semantic processing. The
STG has long been considered to play a central role in language comprehension (e.g., Bogen and Bogen,
1976; Geschwind, 1971; Hillis et al., 2001; Wernicke, 1874), but anatomical and functional data suggest that
it contains mainly modal auditory cortex (Baylis et al., 1987; Galaburda and Sanides, 1980; Kaas and
Hackett, 2000; Poremba et al., 2003; von Economo and Koskinas, 1925). Its role in language relates
primarily to speech perception and phonological processing rather than to retrieval of word meaning (Binder,
2002; Binder et al., 2000; Buchsbaum and D'Esposito, 2008; Graves et al., 2008; Henschen, 1918-1919;
Hickok et al., 2003; Indefrey and Levelt, 2004; Liebenthal et al., 2005; Scott and Johnsrude, 2003; Wise et
al., 2001). Several studies, however, suggest that portions of the left STS, which includes ventral STG, plays
a role in processing abstract concepts (see below).
Left dorsomedial prefrontal cortex (DMPFC). We draw particular attention to this region, which has
been largely overlooked in reviews on semantic processing despite its consistent activation. It forms a
distinctive, diagonally-oriented band extending from the posterior-medial aspect of the MFG, across the
superior frontal sulcus and dorsal SFG, and onto the medial surface of the SFG. It corresponds roughly to
BA 8, extending into BA 9 medially. We use the term "dorsomedial" to distinguish this region from
"dorsolateral prefrontal cortex" located lateral and ventral to it in the lateral MFG and inferior frontal sulcus.
Lesions of the left dorsal and medial frontal lobe cause transcortical motor aphasia, a syndrome
characterized by sparse speech output but otherwise normal phonological abilities (Alexander and Benson,
1993; Freedman et al., 1984; Luria and Tsvetkova, 1968). There is typically a striking disparity between
cued and uncued speech production in this syndrome. Patients can repeat words and name objects relatively
normally, but are unable to generate lists of words within a category or invent non-formulaic responses in
conversation. In other words, patients perform well when a simple response is fully specified by the stimulus
(a word to be repeated or object to be named) but poorly when a large set of responses are possible
(Robinson et al., 1998). This pattern suggests a deficit specifically affecting self-guided, goal-directed
retrieval of semantic information. The location of the DMPFC, adjacent to motivation and sustained attention
networks in the anterior cingulate gyrus and just anterior to premotor cortex, makes this region a likely
candidate for this semantic retrieval role.
Binder et al.
retrieval processes. Analysis of medial frontal lesions in transcortical motor aphasia has usually centered on
the supplementary motor area (SMA), a region of medial premotor cortex (BA 6) posterior to the DMPFC,
perhaps because of the attention drawn to this region in earlier stimulation mapping studies (Penfield and
Roberts, 1959). Some authors, citing the involvement of SMA and anterior cingulate cortex in motor
planning, attention, and motivation processes, dismissed the deficits in patients with left medial frontal
lesions as nonlinguistic in nature (Damasio, 1981). Others have recognized the linguistic nature of the
retrieval deficit while attributing this to SMA damage (Freedman et al., 1984; Goldberg, 1985; Masdeu et al.,
1978). The DMPFC and SMA have a common arterial supply (the callosomarginal branch of the anterior
cerebral artery) and for this reason are usually damaged together in ischemic lesions. While we agree that
focal SMA damage is unlikely to produce a linguistic deficit, we propose that the specific linguistic deficit
affecting fluent semantic retrieval in many of these patients is due to DMPFC damage anterior to the SMA.
Left inferior frontal gyrus (IFG). The left IFG was implicated in several early imaging studies of
semantic processing (Frith et al., 1991; Kapur et al., 1994b; Petersen et al., 1988), and much subsequent
discussion has focused on this region (e.g., Bookheimer, 2002; Buckner et al., 1995; Chee et al., 2002;
Démonet et al., 1993; Devlin et al., 2003; Fiez, 1997; Gabrieli et al., 1998; Gold and Buckner, 2002;
Goldberg et al., 2007; Nyberg et al., 2003; Poldrack et al., 1999; Roskies et al., 2001; Simmons et al., 2005;
Thompson-Schill et al., 1997; Thompson-Schill et al., 1999b; Wagner et al., 2000; Wagner et al., 2001).
Consistent with prior reviews (Bookheimer, 2002; Fiez, 1997), the meta-analysis shows clear involvement of
the anterior-ventral left IFG in semantic processing. This region corresponds to the pars orbitalis (BA 47).
More posterior and dorsal parts of the IFG were also activated, though less consistently.
Imaging studies have also frequently implicated the left IFG in phonological, working memory, and
syntactic processes (e.g., Buckner et al., 1995; Burton et al., 2000; Davis et al., 2004; Démonet et al., 1992;
Embick et al., 2000; Fiebach et al., 2005; Fiez, 1997; Fiez et al., 1999; Friederici et al., 2003; Gold and
Buckner, 2002; Grodzinsky and Friederici, 2006; Indefrey and Levelt, 2004; Nyberg et al., 2003; Owen et
al., 2005; Paulesu et al., 1993; Poldrack et al., 2001; Poldrack et al., 1999; Smith et al., 1998; Tan et al.,
2005; Zatorre et al., 1992). Many studies have also shown increased BOLD responses in the IFG as task
difficulty increases, possibly due to increased working memory or phonological processing demands (e.g.,
Adler et al., 2001; Binder et al., 2005a; Braver et al., 2001; Braver et al., 1997; Desai et al., 2006; Gould et
al., 2003; Honey et al., 2000; Jonides et al., 1997; Lehmann et al., 2006; Mitchell, 2005; Sabsevitz et al.,
2005; Tregallas et al., 2006; Ullsperger and von Cramon, 2001). Though we attempted to remove contrasts in
which semantic processing was confounded with phonological processing or overall difficulty, these
screening efforts were likely imperfect due to the absence of appropriate behavioral data in many published
studies. It is thus possible that some of the IFG activation foci, particularly those outside the pars orbitalis,
are the result of residual phonological or working memory confounds.
As is well known, IFG lesions typically impair phonological, articulatory planning, and syntactic rather
than semantic processes (Alexander and Benson, 1993; Broca, 1861; Caramazza et al., 1981; Mohr, 1976),
though a few cases of transcortical sensory aphasia have been reported (Maeshima et al., 1999; Maeshima et
al., 2004; Otsuki et al., 1998; Sethi et al., 2007). Strokes affect the posterior aspect of the IFG more
commonly than the anterior region; isolated lesions of the pars orbitalis are practically unknown. Devlin et
al. (Devlin et al., 2003) applied transcranial magnetic stimulation (TMS) to the anterior IFG in 8 healthy
participants during performance of semantic decision and perceptual (size) decision tasks. TMS slowed
participants' reaction time on the semantic but not on the control task, supporting a role for this region in
semantic processing. Accuracy on the semantic task, however, was not affected by TMS. It may be that the
anterior-ventral IFG contributes to semantic processing in the healthy brain but is not absolutely necessary
for task completion (Price et al., 1999). Damage to this region thus impairs processing efficiency, resulting in
slowing of responses without actual errors.
Left ventromedial prefrontal cortex (VMPFC). This group of foci occupy cortex in the cingulate gyrus
and medial SFG anterior to the genu of the corpus callosum, the subgenual cingulate gyrus, gyrus rectus, and
The left DMPFC has not been delineated in previous discussions of the prefrontal cortex and semantic
Binder et al.
medial orbital frontal cortex. The involved region of anterior cingulate cortex is anterior and ventral to the
more dorsal region of anterior cingulate cortex implicated in many studies of working memory, response
conflict, error detection, and executive control functions (e.g., Barch et al., 2001; Carter et al., 1999; Duncan
and Owen, 2000; Owen et al., 2005; van Veen and Carter, 2002). We use the term rostral cingulate gyrus to
emphasize this distinction. The VMPFC corresponds to portions of BA 10, 11, 24, 25, and 32. This region
has been linked with motivation, emotion, and reward processing, and probably plays a central role in
processing the affective significance of concepts (Bechara et al., 2000; Damasio, 1994; Drevets et al., 1997;
Mayberg et al., 1999; Phillips et al., 2003). It has also been activated in many general semantic contrasts,
however, possibly due to incidental processing of the emotional attributes of words (Kuchinke et al., 2005).
Posterior cingulate gyrus. This region, which corresponds to BA 23, BA 31, and the retrosplenial region
(BA 26, 29, and 30), was one of the most consistently activated. Activation peaks occurred in both
hemispheres but more often on the left. A few foci in this cluster were located in the ventral aspect of the
precuneus just dorsal to the posterior cingulate, in the region of the subparietal sulcus separating these gyri,
or in the ventral parieto-occipital sulcus, which separates the posterior cingulate gyrus from the occipital
This general region has been linked with episodic and visuospatial memory functions (Aggleton and
Pearce, 2001; Epstein et al., 2007; Gainotti et al., 1998; Rudge and Warrington, 1991; Valenstein et al.,
1987; Vincent et al., 2006), emotion processing (Maddock, 1999), spatial attention (Mesulam, 1990; Small et
al., 2003), visual imagery (Burgess, 2008; Hassabis et al., 2007; Johnson et al., 2007), and other processes
(Vogt et al., 2006). Of these, the association with episodic memory may be most likely. Posterior cingulate
and adjacent retrosplenial cortex have strong reciprocal connections with the hippocampal complex via the
cingulum bundle (Kobayashi and Amaral, 2003, 2007; Morris et al., 1999). A number of patients with focal
lesions to this region have presented with amnestic syndromes (Gainotti et al., 1998; Heilman et al., 1990;
Katai et al., 1992; McDonald et al., 2001; Rudge and Warrington, 1991; Takayama et al., 1991; Valenstein et
al., 1987). Retrosplenial and surrounding posterior cingulate cortex are affected early in the course of
Alzheimer disease, which typically presents as an episodic memory encoding deficit (Desgranges et al.,
2002; Nestor et al., 2003).
If posterior cingulate cortex is involved primarily in encoding episodic memories, why is it consistently
activated in contrasts that emphasize semantic processing? The likely answer has to do with the nature of
episodic memory, the presumed evolutionary purpose of which is to form a record of past experience for use
in guiding future behavior. Not all experiences are equally useful in this regard, thus the brain has evolved a
strategy of preferentially recording highly meaningful experiences, i.e., experiences that evoke associations
and concepts. Familiar examples of this phenomenon include the enhanced learning of words encoded during
semantic relative to perceptual tasks, imageable relative to abstract words, and emotional relative to neutral
words (Bock, 1986; Paivio, 1968, Craik and Lockhart, 1972). In each case, the enhanced retrieval of
conceptual information (semantic retrieval) leads to enhanced episodic encoding. Several related theories of
this phenomenon have been proposed (Cohen and Eichenbaum, 1993; McClelland et al., 1995; O'Reilly and
Rudy, 2001), all of which postulate that episodic memory encoding involves the formation of large-scale
representations through interactions between neocortex and the hippocampal system. The role of the
neocortex is to compute ongoing perceptual, semantic, affective, and motor representations during the
episode, while the hippocampal system binds these spatiotemporal cortical events into a unique event
configuration. The important point is that the amount of episodic encoding that occurs is highly correlated
with the degree of semantic processing evoked by the episode. We propose that the posterior cingulate gyrus,
by virtue of its strong connections with the hippocampus, acts as an interface between the semantic retrieval
and episodic encoding systems, similar to the role postulated above for the parahippocampal gyrus.
Homologues of the human semantic system in the macaque monkey brain
The posterior inferior parietal lobe of the macaque monkey, variously designated 7a (Vogt and Vogt, 1919)
or PG (von Bonin and Bailey, 1947), and more recently subdivided into two subregions, PG and Opt
Binder et al.
Figure 7. Summary diagrams comparing (A) the large-scale semantic network of the human brain, and (B)
a probable homologous network in the macaque monkey brain, comprised of posterior inferior parietal
cortex (PG/7a), STS, parahippocampal cortex (TF, TH), dorsolateral prefrontal cortex, posterior cingulate
and retrosplenial cortex, lateral orbital frontal cortex, and ventromedial prefrontal cortex. Green lines
indicate the principal cortical connections of these regions in the monkey, based on studies using
anterograde and retrograde tracer techniques (Andersen et al., 1990; Baleydier and Mauguiere, 1980;
Barbas, 1993; Blatt et al., 2003; Cavada, 2000; Cavada and Goldman-Rakic, 1989a, 1989b; Jones and
Powell, 1970; Kobayashi and Amaral, 2003, 2007; Leichnitz, 1980; Mesulam et al., 1977; Morris et al.,
1999; Padberg et al., 2003; Parvizi et al., 2006; Petrides and Pandya, 1984; Saleem et al., 2007; Selemon
and Goldman-Rakic, 1988; Seltzer and Pandya, 1976, 1978, 1984, 1989, 1994; Vogt and Pandya, 1987).
All connections indicated are monosynaptic and reciprocal.
Binder et al.
(Gregoriou et al., 2006; Pandya and Seltzer, 1982), is a likely homologue of the human AG with similar
heteromodal functional characteristics (Hyvarinen, 1982). Its principal connections are with visual and
"polysensory" regions in the upper bank and fundus of the superior temporal sulcus (areas TPO, STP, MST,
IPa), the parahippocampal gyrus (areas TF and TH), dorsolateral prefrontal cortex (mainly area 46),
rostrolateral orbitofrontal cortex (area 11), and posterior cingulate gyrus (Andersen et al., 1990; Cavada and
Goldman-Rakic, 1989a, 1989b; Jones and Powell, 1970; Leichnitz, 1980; Mesulam et al., 1977; Petrides and
Pandya, 1984; Selemon and Goldman-Rakic, 1988; Seltzer and Pandya, 1984, 1994). Notably, the same STS,
parahippocampal, prefrontal, and posterior cingulate regions with which PG/7a is connected are themselves
all strongly interconnected (Baleydier and Mauguiere, 1980; Blatt et al., 2003; Jones and Powell, 1970;
Kobayashi and Amaral, 2003, 2007; Morris et al., 1999; Padberg et al., 2003; Parvizi et al., 2006; Selemon
and Goldman-Rakic, 1988; Seltzer and Pandya, 1976, 1978, 1989, 1994; Vogt and Pandya, 1987). These six
regions thus form a distinct, large-scale cortical network that is strikingly similar in location and function to
the human semantic system (Figure 7). The other chief component of the human system, VMPFC, is roughly
homologous to the medial orbitofrontal (BA 10, 14, 25, 32) region of the macaque. While this region has no
connection with PG/7a, it is strongly connected to middle and anterior STS, posterior cingulate and
retrosplenial cortex, parahippocampus, and hippocampus (Barbas, 1993; Blatt et al., 2003; Cavada, 2000;
Kobayashi and Amaral, 2003; Saleem et al., 2007; Seltzer and Pandya, 1989). Thus the macaque brain
contains a well-defined network of polysensory, heteromodal, and paralimbic areas that are several
processing stages removed from primary sensory and motor regions and likely to be involved in computation
of complex, non-perceptual information. We propose that this network is a nonhuman primate homologue of
the human semantic system, responsible for storage of abstract knowledge about conspecifics, food sources,
objects, actions, and emotions. Anatomical differences between the human and macaque systems are
consistent with the known expansion of prefrontal, parietal, and temporal heteromodal cortex in the human
brain, which has enabled in humans further abstraction of knowledge from perceptual events, ultimately
culminating in the development of formal symbol systems to represent and communicate this knowledge.
The macaque parietal/frontal/STS network illustrated in Figure 7 has often been interpreted as playing a
central role in visuospatial processing and spatial allocation of attention (Hyvarinen, 1982; Mesulam, 1981;
Selemon and Goldman-Rakic, 1988; Seltzer and Pandya, 1984). This view is supported by a large number of
studies showing cells in the posterior inferior parietal lobe of the macaque that respond to oculomotor, limb
movement, and spatial attention tasks (Andersen et al., 1997; Hyvarinen, 1982; Mountcastle et al., 1975).
This model is clearly at odds, however, with our proposal that these regions are involved in long-term
storage and retrieval of object and action knowledge. In our view, the characterization of this network as
visuospatial/attentional does not account for the prominent connections of these frontoparietal areas with
polysensory and paralimbic areas. We believe these models can be reconciled by a consideration of known
subdivisions of the macaque posterior parietal lobe. Research over the past 20 years has clarified the
connectivity and functional properties of several areas immediately anteromedial to PG/7a in the macaque
intraparietal sulcus (LIP, VIP, MIP), which appear to play a greater role in visuospatial and attention
processes than PG/7a (Andersen et al., 1990; Andersen et al., 1997; Chafee and Goldman-Rakic, 1998;
Duhamel et al., 1998; Rushworth et al., 1997). Unlike PG/7a, these IPS regions have little or no connectivity
with the temporal lobe or paralimbic regions (Cavada and Goldman-Rakic, 1989a; Seltzer and Pandya, 1984;
Suzuki and Amaral, 1994). They are connected strongly to the frontal eye fields and premotor cortex,
whereas PG/7a is connected to more anterior and dorsal prefrontal regions (area 46) (Andersen et al., 1990;
Cavada and Goldman-Rakic, 1989b). Numerous functional imaging studies have also clearly linked the IPS
and frontal eye fields in humans with visuospatial and attention functions (Corbetta et al., 1998; Grefkes and
Fink, 2005; Grosbras et al., 2005). Thus, we propose that the posterior parietal spatial attention system in
both the human and macaque is confined mainly to cortex in the IPS and superior parietal lobule, and that
there is a distinct functional and anatomical boundary between this IPS system and adjacent inferior parietal
cortex involved in semantic knowledge representation. This boundary line appears to correspond in both
species to the superior margin of the lateral (posterior) bank of the IPS (see Figure 2).
Binder et al.
Evidence for distinct semantic subsystems
In addition to brain networks supporting semantic processing in general, particular regions may be relatively
specialized for processing specific object categories, attributes, or types of knowledge. Prior reviews on this
topic have included studies that used object pictures as stimuli, whereas the present meta-analysis was
confined to studies using words. The number of such studies that examined specific types of semantic
knowledge was relatively small, and activation peaks from these studies showed little overlap. The clearest
pattern emerged from the 10 studies examining action knowledge (Figure 5). Two distinct activation clusters
were observed in left SMG and posterior MTG. Lesions in these areas have been associated with
impairments of action knowledge and ideomotor apraxia in many neuropsychological studies (Buxbaum et
al., 2005; Haaland et al., 2000; Jax et al., 2006; Tranel et al., 1997; Tranel et al., 2003). The SMG focus lies
just posterior to somatosensory association cortex, thus it seems likely that this region stores abstract
somatosensory (e.g., proprioceptive) knowledge acquired during learning and performance of complex motor
sequences. The likely homologue of this region in the macaque monkey is area PF in the anterior inferior
parietal lobe, a region known to contain mirror neurons responsive to both action observation and
performance (Rizzolatti and Craighero, 2004). Activation of this region in humans by words, which merely
refer conceptually to actions, lends support to the idea that the information stored there is semantic in nature,
coding complex actions performed on objects for a specific purpose (Buxbaum, 2001; Buxbaum et al., 2005;
Buxbaum et al., 2006; Fogassi et al., 2005; Rothi et al., 1991). The posterior MTG focus is just anterior to
visual motion processing areas in the MT complex (Tootell et al., 1995), suggesting that this region stores
knowledge about the visual attributes of actions. As previously suggested (Martin et al., 2000), this
specialization of posterior MTG for processing action knowledge may explain the frequently observed
preferential activation of this region by pictures of tools (Cappa et al., 1998; Chao et al., 1999; Chao et al.,
2002; Damasio et al., 2004; Devlin et al., 2002a; Martin et al., 1996; Moore and Price, 1999a; Mummery et
al., 1996; Perani et al., 1999; Phillips et al., 2002). Indeed, the studies examining knowledge of manipulable
artifacts (relative to living things) produced areas of overlap at very similar sites in the SMG and near the
junction of posterior MTG, ITG, and lateral occipital lobe. In contrast, the studies examining knowledge of
living things (usually animals) relative to other categories produced no significant areas of overlap,
consistent with several prior reviews (Devlin et al., 2002b; Gerlach, 2007).
Given the presence of mirror neurons in premotor cortex (Rizzolatti and Craighero, 2004) and prior
imaging evidence that the inferior frontal region responds to pictures of manipulable objects (Binkofski et
al., 1999; Buxbaum et al., 2006; Chao and Martin, 2000; Gerlach et al., 2002; Kellenbach et al., 2003; Martin
et al., 1996; Perani et al., 1999), it is somewhat surprising that frontal cortex did not show consistent
activation in studies of action or artifact words. Several of the included action and artifact studies did report
activation in this general region (Kounios et al., 2003; Martin et al., 1995; Ruschmeyer et al., 2007; Tyler et
al., 2003b; Wheatley et al., 2005), yet these foci did not cluster sufficiently to produce an activation in the
ALE analysis. Evidence suggests that inferior frontal and inferior parietal cortices play somewhat different
roles in action processing, with the parietal system more closely associated with knowledge of specific
object-related actions (Buxbaum, 2001; Buxbaum et al., 2005; Creem-Regehr and Lee, 2005; Fogassi et al.,
2005). Consistent with this distinction, patients with inferior parietal lesions may have impaired recognition
of object-related pantomimes performed by others ("representational ideomotor apraxia"), while patients
with inferior frontal lesions apparently do not (Buxbaum et al., 2005; Rothi et al., 1991; Varney and
Damasio, 1987). Thus, it is possible that action and artifact words, which in any case do not seem to activate
motor representations as readily as pictures do (Rumiati and Humphreys, 1998), engage inferior frontal
systems only weakly compared to inferior parietal areas concerned with object-related action knowledge.
Some theorists have emphasized a distinction between perceptual ("image-based") and verbal
representations in semantic memory (Paivio, 1986), exemplified by the contrast between concrete and
abstract words. A number of functional imaging studies have examined this distinction (see (Binder, 2007)
for a review). Thirteen studies included in the present meta-analysis showed areas of stronger activation for
concrete compared to abstract words, with overlap in bilateral AG, left mid-fusiform gyrus, left DMPFC, and
Binder et al.
left posterior cingulate cortex (Figure 6). This pattern is very similar to the network observed in the general
semantic meta-analysis (Figure 4). Eight studies showed areas of stronger activation for verbal compared to
perceptual knowledge. These included comparisons between abstract and concrete words, abstract and
concrete stories, and encyclopedic (i.e., verbal factual) vs. perceptual knowledge. Abstract concepts are
generally more difficult to process than concrete concepts, and several other studies had to be excluded from
the meta-analysis because of this confound. Areas associated with verbal semantic processing included the
left IFG (mainly pars orbitalis) and left anterior STS. These dissociations support a distinction between
perceptually-based knowledge, stored in heteromodal association areas such as the AG and ventral temporal
lobe, and verbally-encoded knowledge, which places greater demands on left anterior perisylvian regions.
This dissociation is supported by a range of neuropsychological studies showing relative impairment of
abstract word processing in patients with perisylvian lesions (Coltheart et al., 1980; Franklin et al., 1995;
Goodglass et al., 1969; Katz and Goodglass, 1990; Roeltgen et al., 1983) and relative impairment of concrete
word processing in patients with extra-sylvian (mainly ventral temporal lobe) lesions (Breedin et al., 1995;
Marshall et al., 1998; Warrington, 1975, 1981; Warrington and Shallice, 1984).
Semantic processing and autobiographical memory retrieval
The semantic system identified here is virtually identical to the large-scale network identified in recent
studies of autobiographical memory retrieval (Maguire, 2001; Svoboda et al., 2006).3 There are cogent
theoretical and empirical reasons to distinguish general semantic from autobiographical memory (De Renzi
et al., 1987; Tulving, 1972; Yasuda et al., 1997), yet this nearly complete overlap observed in functional
imaging studies is striking. Autobiographical memory refers to knowledge about one's own past, including
both remembered events, known as episodic autobiographical memory (e.g., "I remember playing tennis last
weekend"), and static facts about the self, known as semantic autobiographical memory (e.g., "I like to play
tennis"). Most autobiographical memory begins as detailed knowledge about recently experienced events
(i.e., episodic memories). With time, these specific memories lose their perceptual detail and come to more
closely resemble semantic knowledge (Addis et al., 2004; Johnson et al., 1988; Levine et al., 2002).
There are several reasons to expect overlap between the general semantic and autobiographical memory
retrieval systems. First, semantic autobiographical memories, though they differ from general semantic
knowledge in referring to the self, are essentially learned facts and therefore might be supported by the same
system that stores and retrieves other learned facts. Second, several theorists have proposed that retrieval of
general concepts, such as particular temporal and spatial locations, people, objects, and emotions, is an early
processing stage in the retrieval of autobiographical memories and serves to cue the retrieval of these more
personal memories (Barsalou, 1998; Conway and Pleydell-Pearce, 2000). Finally, it is worth emphasizing the
perhaps obvious point that autobiographical memories are necessarily composed of concepts, and that there
could be no retrieval of an autobiographical memory without retrieval of concepts. To recall, for example,
that "I played tennis last weekend" logically entails retrieval of the concepts "tennis", "play", and "weekend".
Thus, the essential distinction between general semantic retrieval and autobiographical memory retrieval lies
in the self-referential aspect of the latter, which may be a relatively minor component of the overall process,
at least from a neural standpoint.
A few neuroimaging studies have directly compared autobiographical and general semantic retrieval and
reported greater activation in the semantic network during the autobiographical condition, particularly in the
medial prefrontal cortex, AG, and posterior cingulate region (Addis et al., 2004; Graham et al., 2003; Levine
et al., 2004; Maguire and Frith, 2003). Rather than indicating a specialization for autobiographical memory
processing in these regions, we believe these data reflect the fact that semantic autobiographical memories
are typically more perceptually vivid, detailed, contextualized, and emotionally meaningful than general
semantic memories. Thus, we propose that semantic autobiographical and general semantic memory
processing are supported by largely identical neural networks, but that retrieval of richer and more detailed
memories (such as autobiographical memories) engages this network to a greater degree than retrieval of less
Binder et al.
Semantic processing and the "default network"
As illustrated in Figure 8, the semantic system identified here is also strikingly similar to the human brain
"default network" thought to be active during the conscious resting state (Binder et al., 1999; Raichle et al.,
2001). This network was originally defined as a set of brain areas that consistently show "task-induced
deactivation" in functional imaging studies (Binder et al., 1999; Mazoyer et al., 2001; McKiernan et al.,
2003; Raichle et al., 2001; Shulman et al., 1997). Task-induced deactivation refers to decreases in blood
flow or BOLD signal during effortful tasks compared to more passive states such as resting, fixation, and
passive sensory stimulation.
processes active during passive states are "interrupted" when subjects are engaged in effortful tasks (Binder
et al., 1999; Raichle, 2006), though the precise nature of these default neural processes remains a topic of
debate. Evidence suggests that high levels of ongoing "spontaneous" neural activity are necessary for
maximizing responsiveness of the cortex to changes in input (Chance et al., 2002; Ho and Destexhe, 2000;
Salinas and Sejnowski, 2001), and this ongoing activity seems to account for much of the high resting
metabolic needs of the cortex (Attwell and Laughlin, 2001). The mere fact that there are high levels of neural
activity in the resting state does not explain, however, why this activity decreases in particular brain regions
during active task states. Such an explanation would seem to depend on an account of resting state activity in
terms of the cognitive and affective processes in which subjects preferentially engage during passive states,
such as episodic memory encoding and retrieval, monitoring and evaluating the internal and external
environment, visual imagery, emotion processing, and working memory (Andreasen et al., 1995; Mazoyer et
al., 2001; Raichle et al., 2001; Shulman et al., 1997; Simpson et al., 2001; Stark and Squire, 2001).
There is now a general consensus that task-induced deactivation occurs because certain types of neural
Figure 8. Comparison of the left hemisphere general semantic network indicated in the present ALE meta-
analysis (top) and the "default network" (bottom). The latter map represents brain areas that showed task-
induced deactivation during performance of a tone discrimination task, i.e. higher BOLD signal during a
conscious resting baseline compared to the tone task (see Binder et al., 2008 for details). In both types of
studies, effects are observed in the angular gyrus, posterior cingulate gyrus, dorsomedial prefrontal cortex,
ventromedial prefrontal cortex, ventral temporal lobe, anterior MTG, and ventral IFG. Although effects are
stronger in the left hemisphere for both kinds of studies, task-induced deactivation is typically more
symmetrical in posterior cingulate and medial prefrontal regions (Binder et al., 1999; Mazoyer et al., 2001;
McKiernan et al., 2003; Raichle et al., 2001; Shulman et al., 1997).
Binder et al.
activity occurring during passive states. This proposal was based first on phenomenological considerations.
The everyday experience of spontaneous thoughts, mental narratives, and imagery that James referred to as
the "stream of consciousness" (James, 1890) is ubiquitous and undeniable. Participants in controlled
laboratory conditions reliably report such "task-unrelated thinking", the content of which includes concepts,
emotions, and images (Antrobus, 1968; Antrobus et al., 1966; Giambra, 1995; Horowitz, 1975; McKiernan
et al., 2003; Pope and Singer, 1976; Teasdale et al., 1995; Teasdale et al., 1993). Performance of effortful
perceptual and short-term memory tasks reliably suppresses task-unrelated thoughts, suggesting a direct
competition between exogenous and endogenous signals for attentional and executive resources.
"Interrupting the stream of consciousness" thus provides a straightforward explanation for task-induced
The second consideration emphasized by Binder et al. was the potential adaptive advantage of systems
that allow "ongoing" retrieval of conceptual knowledge. In contrast to the sensory, spatial attention, and
motor processes engaged when an external stimulus requires a response, ongoing conceptual processes
operate primarily on internal stores of knowledge built from past experience. They are not random or
"spontaneous" but rather play a profoundly important role in human behavior. Their purpose is to "make
sense" of prior experience, solve problems that require computation over long periods of time, and create
effective plans governing behavior in the future. This uniquely human capability to perform high-level
computations "off-line" is surely the principal explanation for our ability to adapt, create culture, and invent
The final evidence offered by Binder et al. was an fMRI study in which participants were scanned while
resting, while performing a perceptual task with no semantic content, and while making semantic decisions
about words. Relative to the resting state, the perceptual task produced deactivation in the usual default
network (AG, posterior cingulate gyrus, VMPFC, DMPFC). Critically, however, the semantic decision task
did not deactivate these regions. Finally, the same regions were activated when contrasting the semantic
decision task with a phonological task that controlled for sensory and executive processes. These results
show not only that the semantic network (as defined by the semantic-phonological task contrast) is virtually
identical to the default state network, but also that task-induced deactivation in these regions can be
modulated by task content. Deactivation occurs when the task or stimuli make little or no demands on
semantic processing. When the task itself engages the semantic system, however, deactivation does not
occur. This pattern indicates that the default network itself is engaged in semantic processing, both during
passive states and when presented with a semantic task. This pattern has since been replicated in a number of
studies comparing word tasks, pseudoword tasks, and passive or resting conditions. Pseudowords reliably
deactivate the default network relative to the resting state, whereas words do not (Baumgaertner et al., 2002;
Binder et al., 2005a; Henson et al., 2002; Humphries et al., 2007; Ischebeck et al., 2004; Mechelli et al.,
2003; Rissman et al., 2003; Xiao et al., 2005). This result is fully consistent with the model just proposed,
since pseudowords have little meaning and thus do not engage the semantic system.
Conceptual vs. perceptual processing
The observation that semantic processing engages a network of heteromodal association areas distinct from
modal sensory and motor systems provides support for the traditional distinction between conceptual and
perceptual processes (Fodor, 1983). Under this view, conceptual processes operate on "internal" sources of
information, such as semantic and episodic memory, which can be retrieved and manipulated at any time,
independent of ongoing external events. In contrast, perceptual processes operate on "external" information
derived from immediate, ongoing sensory and motor processes that coordinate interactions with the external
environment. Many tasks, of course, require simultaneous processing of both internal and external
information, including, for example, any behavior involving recognition of a familiar stimulus such as a
word or picture. In such instances, external sensory information is given meaning by activation of associated
internal information (Aurell, 1979; Neisser, 1967).
Binder et al. (1999) proposed that semantic processing constitutes a large component of the cognitive
Binder et al.
areas identified with semantic processing in the present meta-analysis in red. Yellow areas in the figure were
activated during a task in which subjects read pseudowords aloud, thereby engaging ventral visual form
perception, dorsal visual and spatial attention, motor articulation, and auditory perceptual systems bilaterally
(Binder et al., 2005a). Apart from a few areas of overlap in the anterior ventral visual stream, STS, and IFG,
these large-scale networks are largely distinct and complementary, together covering much of the cortical
surface. Similar imaging evidence supporting a general distinction between large-scale "intrinsic" and
"extrinsic" networks has been reported recently by other researchers (Fox et al., 2005; Fransson, 2005;
Golland et al., 2007).
Functional imaging evidence for such a distinction is illustrated dramatically in Figure 9, which shows
the brain, other evidence suggests that this distinction is not absolute (Gallese and Lakoff, 2005). For
example, several studies have shown involvement of primary motor and premotor cortex in the
comprehension of action verbs (Hauk et al., 2004; Pulvermuller et al., 2005; Tettamanti et al., 2005).
Similarly, there is evidence that high-level visual cortex participates in the processing of object nouns (James
and Gauthier, 2003; Kan et al., 2003; Martin et al., 1995; Simmons et al., 2007). Word-related activation of
these motor and sensory areas is likely to be somewhat subtle compared to activation of heteromodal
conceptual regions and to depend to a greater extent on the specific sensorimotor attributes of the word
concept. Furthermore, there are as yet few published studies that have focused on such specific attributes.
Thus the present meta-analysis may under-represent the involvement of sensory and motor systems in
comprehension of word stimuli. Defining the extent of this involvement is an important topic for future
Although these observations confirm a general distinction between conceptual and perceptual systems in
Figure 9. Composite map of complementary human brain networks for processing internal and external
sources of information. Red areas indicate the general semantic network identified in the current meta-
analysis. Yellow indicates areas activated in 24 healthy adults during oral reading of visually presented
pseudowords (pronounceable but meaningless letter strings) compared to a resting baseline (Binder et al.,
2005a). The latter task activates unimodal visual and auditory areas bilaterally, dorsal attention systems in
the IPS and FEF bilaterally, and bilateral motor, premotor, dorsal anterior cingulate, and dorsolateral
prefrontal systems involved in response production. Overlap between these two major networks is
Binder et al.
Comparison with previous large-scale reviews of semantic processing
The current results differ somewhat from conclusions reached in previous reviews. Cabeza and Nyberg
(2000) reviewed functional imaging studies published prior to 1999. From an initial sample of 275 studies in
a range of cognitive domains, they found 31 involving semantic memory retrieval tasks. Activation foci from
these studies clustered mainly in the left IFG, with a few additional foci in the left MTG. The authors
provided a brief description of the task contrasts used in each study and drew attention to the importance of
control tasks, but made no attempt to exclude studies with word-form or task difficulty confounds. Of these
31 studies, only 4 passed our criteria for inclusion, with the remainder excluded mainly for phonological or
task difficulty confounds.
Vigneau et al. (2006) collected 65 studies published prior to 2005 that concerned semantic processing.
The authors did not report how the studies were identified but indicated that they excluded contrasts that
used visual fixation or resting controls. Both object and word studies were included. No attempt was made to
identify phonological or task difficulty confounds. Only activation peaks in the lateral temporal, lateral
frontal, and inferior parietal lobes were included in the analysis. Foci were found throughout these regions,
including the STG, MTG, IFG, and premotor cortex. The findings of Vigneau et al. thus differ from the
current results in showing numerous foci in the STG (due to inclusion of studies comparing speech to non-
speech sounds) and in the posterior IFG and premotor cortex (likely due to phonological and working
memory confounds), and in the a priori exclusion of data from ventral temporal, dorsomedial prefrontal,
posterior cingulate, and ventromedial frontal areas. Of the 65 studies selected by Vigneau et al., only 17
passed our criteria for inclusion; most were excluded because of task confounds or use of object stimuli.
Another 53 studies that passed our criteria and were published prior to 2005 were not identified by Vigneau
Future meta-analyses of cognitive imaging studies would benefit from the establishment of a more
formal ontological system for defining the cognitive processes represented by an "activation". The aim of
such meta-analyses is to identify the neural correlates of a specific cognitive process or related set of
processes, but this enterprise cannot logically succeed without an objective means of defining the cognitive
components represented by an activation. The "objects" in such an ontology would correspond to particular
experimental conditions (i.e., cognitive processing states), specified by sets of operationally-defined stimulus
and task attributes. Contrasts between experimental conditions would constitute "relations" defining the
cognitive processes that differ between conditions. The system would rest on a set of agreed-upon axioms
concerning stimuli, tasks, and their attributes (e.g., "words are familiar symbols", "familiar symbols have
associations", "associations are stored in semantic memory", etc.). The interpretive power of such an
ontology would be invaluable not only for retrospective meta-analysis but also for designing and interpreting
future studies within a common theoretical framework.
The neural systems specialized for storage and retrieval of semantic knowledge are widespread and occupy a
large proportion of the cortex in the human brain. The areas implicated in these processes can be grouped
into three broad categories: posterior heteromodal association cortex (AG, MTG, fusiform gyrus), specific
subregions of heteromodal prefrontal cortex (dorsal, ventromedial, and inferior prefrontal cortex), and medial
paralimbic regions with strong connections to the hippocampal formation (parahippocampus and posterior
cingulate gyrus). The widespread involvement of heteromodal cortex is notable in that these regions are
greatly expanded in the human relative to the nonhuman primate brain. This evolutionary expansion of
neural systems supporting conceptual processing probably accounts for uniquely human capacities to use
language productively, plan the future, solve problems, and create cultural and technological artifacts, all of
which depend on the fluid and efficient retrieval and manipulation of conceptual knowledge.
Binder et al.
This work was supported by the National Institutes of Health (grants R01 NS33576, R01 NS35929, R01
DC006287, R03 DC008416, T32 MH019992, F32 DC007024, and F32 HD056767).
The authors thank B. Douglas Ward for invaluable technical assistance.
1. The number of unique individuals involved in these studies could be smaller than 1642. We did not count
participants more than once if they were involved in more than one contrast from the same publication.
However, the same individual could have been included in more than one publication.
2. Some of this confusion may be an historical accident stemming from Brodmann's famous illustration,
which shows area 39 shrunken to a fraction of its true size relative to surrounding structures (Brodmann,
1994/1909). Other cytoarchitectonic studies have portrayed this region as much more extensive (Sarkissov et
al., 1955; von Economo and Koskinas, 1925). Brodmann's intent seems to have been to show both lateral and
dorsal brain regions in a single lateral view. This required that the inferior parietal lobule on the lateral
surface be reduced in size to accommodate areas on the superior parietal lobule, which are normally not well
seen from a lateral view.
3. In their comprehensive review of the autobiographical memory literature, Svoboda et al. (Svoboda et al.,
2006) refer to the AG as "temporoparietal junction", though all of the foci they report in this region are in the
inferior parietal lobe.
Binder et al.
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Appendix 2. Individual study details.
Activation in Brain Regions of Interest
No. 1st Author
N Method Type
MTG FG/PH DMPFC IFG VMPFC
Binder et al.
Gorno-Tempini 6 PET
Binder et al.
Binder et al.
111 Vandenberghe 10 PET
112 von Kriegstein 14 fMRI
Binder et al.
The Contrast column provides a code indicating the contrast used, with tasks indicated in parentheses after stimuli. The terms Action, Animal,
Artifact, Association, Auditory, Category, Causation, Color, Emotion, Figurative, Function, General, Literal, Location, Motion, Natural, Number,
Perceptual, Self, Size, Specific, Taste, Tool, Verbal, and Visual refer to the object category or knowledge domain emphasized by the stimulus or
task. 'Other' indicates a miscellaneous combination of categories or domains. Abbreviations used for stimuli: Abst = abstract words, Conc =
concrete words, Fam = familiar concepts, Unfam = unfamiliar concepts, N = nonwords (i.e., pseudowords), W = words, HighM = sentences or
words with high meaningfulness, LowM = sentences or words with low meaningfulness, HighA = highly associated word pairs, LowA = weakly
associated word pairs, Rel = semantically related words, Unrel = semantically unrelated words, Sent = sentences, Story = connected narrative or
discourse, UnrelSent = unrelated sentences, SemSP = semantically distinct sentence pairs, SynSP = syntactically distinct sentence pairs, ThM =
theory-of-mind narrative, VTarg = detect a target word or phrase, NVTarg = detect a target nonverbal feature, Verb1 = single-argument verb,
Verb2 = two-argument verb. Abbreviations for tasks: GJ = grammaticality judgment, LD = lexical decision, Match = identity matching, Mem =
memorization, OD = orthographic decision, PD = phonological decision, cRead = covert reading, Read = oral reading, Rep = oral repetition, Rec
= recognition, SD = semantic decision, PWG = phonological word generation, SWG = semantic word generation, cSWG = covert semantic word
generation. Examples: W(SD)-N(PD) indicates a semantic decision task on words contrasted with a phonological decision on pseudowords; Conc-
Abst(LD) indicates a contrast between concrete and abstract words presented during a lexical decision task. Specific contrasts were almost always
performed in both directions (e.g., Animal-Tool and Tool-Animal); for simplicity such complementary contrasts are collapsed into a single row in
Other abbreviations: N = number of subjects in study; Gen = general contrast; Spec = specific contrast; IPL = inferior parietal lobe (angular
and supramarginal gyri); MTG = middle temporal gyrus; FG/PH = fusiform and parahippocampal gyri; DMPFC = dorsomedial prefrontal cortex;
IFG = inferior frontal gyrus; VMPFC = ventromedial prefrontal cortex; PC = posterior cingulate gyrus
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