Neural representations of faces and limbs neighbor in human high-level visual cortex: evidence for a new organization principle

In the early 1960s, little was known about how the visual system combines information to process complex shapes. At the time, Hubel and Wiesel (1965) proposed a hierarchy of sensory processing in the geniculo-striate system of the cat where visual processing became more complex as one ascended these stages. Up to that point, this processing stream ended at area 19 (visual area III; V3), which Hubel and Wiesel admitted could not account for the processing needed for the complex computations involved in object perception. Ablation studies provided some insight into the processing beyond V3, where removal of macaque IT, which was considered ‘association cortex’ at the time, generated specific deficits in visual recognition (Mishkin, 1966). Aware of these two findings, and due to his own clinical experience observing a variety of visual agnosias (an inability to recognize visually presented objects) resulting from cortical lesions in humans, neurophysiologist and neuropsychologist Jerzy Konorski suggested the existence of a face-selective ‘field’ lateral to V3 in visual cortex. Konorski further theorized regions selective for other ‘special’ classes of stimuli such as limbs, words, and places. He referred to these regions as gnostic fields and the neurons within them gnostic units (Konorski, 1967). Around the same time period, Charlie Gross was using single unit electrophysiology methods to examine the visual properties of neurons within IT cortex of the macaque monkey (Gross, Schiller, Wells, & Gerstein, 1967; Fig. 2a). Because of his expertise, Gross was asked to write a book review of Konorski’s theorized organization. A year after publishing this review of Konorski’s book in Science magazine (Gross, 1968), Gross et al., (1969) reported the first hand-selective neuron while measuring properties of IT cells. In this original study, a hand-selective neuron was defined as a cell responding more vigorously to silhouettes of hands relative to a variety of other images of 2D shapes, such as circles, rectangles, and flower-like configurations. In a subsequent study, Gross et al., (1972) extended these findings by measuring additional hand-selective neurons in unison with face-selective neurons (defined in a comparable fashion) in the posterior portion of macaque TE (Fig. 2a), which is a cytoarchitechtonic subdivision of the temporal lobe (von Bonin & Bailey, 1947).

These findings of hand- and face-selective units were not received with much fervor because the definition of macaque IT cortex as a visual area was controversial in and of itself (Gross, 2008 for review). In fact, even though Gross and colleagues were the first to systematically measure the visual properties of IT cortex (Gross et al., 1969, 1972, 1967), it was more than a decade before any group replicated the receptive field properties of IT neurons (Richmond, Wurtz, & Sato, 1983), let alone the finding of hand- and face-selective neurons within this cortical expanse. Contributing to the controversy was the perceived sparsity of hand- and face-selective neurons. For example, Gross et al., (1969) reported only one hand-selective unit (of 51 recorded) in the original study, and then three hand- and three face-selective neurons (out of 205 that were visually responsive in TE) in the second study (Gross et al., 1972). Such small samples suggested that these cells were randomly scattered throughout IT cortex without any general organization principle, in stark contrast to the systematic organization of striate cortex (Hubel & Wiesel, 1962, 1968).

Throughout the 1980s, the study of face-selective cells became more widely accepted and researchers began documenting functional properties of these cells related to different aspects of face processing. It was unknown (and still is presently) what an appropriate control stimulus is to compare to complex stimuli, such as faces and hands. Many of these studies defined face-selective units as those cells that fired more vigorously to the presentation of face images relative to both the spontaneous activity of the cell, as well as to a variety of control images, which could span from brushes (Gross et al., 1972) to ‘3D junk objects’ (Perrett, Rolls, & Caan, 1982; Rolls, 1984). Cells were also typically tested for additional selectivity features, such as responses to oriented bars, 2D shapes of various colors, aversive stimuli (such as images of snakes), as well as to tactile and auditory stimuli (Desimone, Albright, Gross, & Bruce, 1984). Finally, in order to be considered a face-selective neuron, a further criterion was added where a given cell needed to respond at least two times higher to faces than to the most effective control stimulus (e.g. Perrett et al., 1982). Once face-selective neurons were identified in this manner, they were reported to respond comparably across image formats (photograph, drawing) and across face species (human and monkey; Bruce, Desimone, & Gross, 1981; Desimone et al., 1984). Studies also showed that responses of face-selective cells decreased when parts of the face were removed or scrambled (Bruce et al., 1981; Desimone et al., 1984; Perrett et al., 1982), were modulated by the relative distance between internal facial features (Yamane, Kaji, & Kawano, 1988), and were tuned to specific face viewpoints (Perrett et al., 1982; Desimone et al., 1984). Importantly, these properties were maintained across changes in size and position suggesting a high-level representation (Desimone et al., 1984). It is critical to note that some cells illustrated selectivity for features, not the composite face, where these neurons illustrated comparable (and sometimes higher) responses to particular face features, such as the eyes or hair alone (Bruce et al., 1981; Perrett et al., 1982) compared to responses to the whole face (Perrett et al., 1982).

In addition to new insights regarding the functional properties of face-selective neurons, researchers began reporting larger populations of face-selective cells than the initial measurements, as well as documenting a correspondence between a particular anatomical location and a resulting cluster of face-selective cells. For example, in 1972, Gross and colleagues reported only 3 face-selective neurons out of 205 measured (~1.5%) in posterior TE. 15 years later, recording from a more anterior location, this number increased to 34% (17/50 neurons; Desimone et al., 1984). Shortly thereafter, Baylis, Rolls, and Leonard (1987) showed that more face-selective neurons were clustered on the upper and lower banks of the STS than in ventral IT by measuring functional properties of neurons within different cytoarchitechtonic subdivisions of the STS (see Fig. 2b for this anatomical distinction adapted from Saleem, Suzuki, Tanaka, & Hashikawa, 2000). Specifically, Baylis and colleagues showed that area TPO in the upper bank of the STS (44/244; 18% face-selective) and areas TEa (53/250; 21%) and TEm (51/232; 22%) in the lower bank of the STS contained higher concentrations of face cells than other neighboring areas in the upper and lower banks of the STS (Baylis et al., 1987; parcellation terminology from Seltzer & Pandya, 1978; Fig. 2b).

Taken together, by the end of the eighties, several research groups replicated the localization of face-selective neurons in both macaque IT and STS and began documenting that these cells were clustered. Still, neurons selective for static images of hands and limbs evaded researchers with the methods available at the time. For example, in an early study, Perrett et al., (1982) reported five units responding to images of hands, but responses to hands were lower than those to faces (i.e. these neurons were actually face-selective). Thus, if these limb-selective neurons existed, and how they were spatially organized in cortex relative to face-selective neurons was still unknown.

In addition to the reports of clustered face-selective cells in particular anatomical locations (Baylis et al., 1987), Perrett et al., (1984) also illustrated evidence for a potential columnar organization within the STS for face-selective cells, as well as additional neurons selective for moving bodies (Perrett et al., 1985a, b). We interpret their proposal of IT organization to have three general features. First, selective cells are clustered in small patches (0.5–2 mm in diameter) on the cortical surface (Perrett et al., 1984, 1985a). Second, within each of these patches, columns extend as much as 2 mm downward with cells illustrating similar stimulus selectivities on a given vertical electrode penetration. Third, nearby columns illustrate associated selectivities—for example, for different rotations of the head (Perrett et al., 1985b). Tanaka and colleagues extended Perrett’s findings in a series of influential studies demonstrating a general columnar organization of IT cortex, whereby cells preferring similar features tended to cluster in vertical columns perpendicular to the cortical surface about 0.4 mm in diameter (Fujita, Tanaka, Ito, & Cheng, 1992; Tanaka, 1996; Tanaka, Saito, Fukada, & Moriya, 1991; Wang, Tanaka, & Tanifuji, 1996). Tanaka’s group showed this columnar organization for hand-selective cells (Tanaka et al., 1991), moderately complex features (Fujita et al., 1992; Tanaka et al., 1991), and face viewpoint (Wang et al., 1996). In addition to this fine-scale organization, Harries and Perrett (1991) also reported a larger scale organization in macaque STS. They reported clusters of face cells approximately 3–4 mm in diameter along the STS, with a periodic organization in which dense clusters of face-selective cells alternated with clusters of cells that were not face-selective generating an ‘inter-cluster distance’ on the order of 3 mm (Fig. 2c adapted from Perrett, Hietanen, Oram, & Benson, 1992).

There are two key differences in findings across groups. First, Perrett’s sets of recordings were performed on the upper banks of the STS (Harries & Perrett, 1991; Perrett et al., 1985a; Perrett et al., 1984; Fig. 2b, c), while Tanaka’s recordings were in anterior TE (Fujita et al., 1992; Tanaka et al., 1991; Wang et al., 1996; Fig. 2b, c). Second, though both sets of findings conclude with a columnar organization, the definition of column and the associated theory with each definition is different. In Perrett’s definition, many columns make-up one cluster with a particular stimulus-selectivity which then produces a large-scale periodic organization of multiple face patches in the STS. Tanaka’s columns represent a general organization principle in IT cortex for the representation of object features with no additional macroscopic structure. Nevertheless, Tanaka and colleagues suggested that faces may have separate representations which represent facial features and configurations that are not shared by other objects (Tanaka, 1996). Though both the theory and definition of columnar organization are different across groups, converging results across these studies indicate a fine-scale (Fujita et al., 1992; Perrett et al., 1984, 1985a; Tanaka et al., 1991; Wang et al., 1996) and a potentially larger-scale structure (Harries & Perrett, 1991; Fig. 2c) in the organization of cells selective for faces, hands, and moving bodies in different portions of the temporal lobe that had not been documented before.

When Gross and colleagues began to study IT cortex in the late 1960s and early 1970s (see Timeline), they presented data from hand- and face-selective neurons together. Though hand-selective neurons were discovered first, the study of face-selective neurons solidified a niche in visual neuroscience 20 years later, while the study of hand- and other limb-selective neurons evaded researchers. In the late 1980s, there seemed to be a general correspondence between anatomical location and clustering of face-selective cells with a potential columnar organization. By the mid 1990s, the pairing of neurophysiological recording and optical imaging enabled the observation of a columnar structure in monkey IT. Furthermore, there was a reappearance of reports of neurons selective for static hands (Tanaka et al., 1991), the entire body (Wachsmuth, Oram, & Perrett, 1994) and moving hands (Perrett, Mistlin, Harries, & Chitty, 1990). During the same time period, Perrett and collaborators also reported larger clusters of face-selective cells in macaque STS that were 3–4 mm wide with an inter-cluster distance of 3 mm, illustrating a putative periodicity of face-selective cells along the STS (Harries & Perrett, 1991). Though the organization of macaque face- and hand-selective cells vastly evolved from randomly scattered, to clustered, to periodically clustered with a columnar organization, how this organization related to human cortex was still largely unknown.

Visualizing face- and limb-selective activations on the cortical surface reveals multiple face- and limb-selective clusters throughout occipitotemporal cortex, which generate a continuous topographic representation from lateral occipitotemporal cortex extending into ventral temporal cortex. Figure 6 illustrates this organization on the inflated cortical surface of three individual subjects with four notable findings. First, there are multiple face- and limb-selective regions with a periodic organization throughout occipitotemporal cortex. Second, face- and limb-selective regions complement one another where the ‘inter-cluster distance’ between two face-selective regions is commonly filled with a limb-selective region and vice versa. Third, this organization is consistent across individual subjects (see also Weiner & Grill-Spector, 2010, 2011; Weiner, Sayres, Vinberg, & Grill-Spector, 2010), and is reliable across experimental paradigms, tasks, and time (Fig. 7 ). Fourth, several face- and limb-selective regions radiate in a ring-like organization surrounding a well-known functional region—the human motion-selective complex (hMT+; dotted black line in Fig. 6). As the location of hMT+ has been widely examined and is associated with a particular anatomical landmark of the posterior inferotemporal sulcus (Dumoulin et al., 2000; Fig. 1), this suggests that each of these face- and body part-selective regions can be associated with anatomical landmarks. We explain reliable anatomical and functional boundaries that divide this map of face- and limb-selective regions in turn below, first in VTC and then in LOTC.

In VTC, we find alternating face- and limb-selective regions along the posterior 30 mm of the fusiform gyrus extending laterally into the occipitotemporal sulcus (OTS; inferior activations in Fig. 6). Each of these functional regions exhibits two features that have gone undocumented in prior studies. First, there are two anatomically distinct face-selective regions on the fusiform gyrus: one on the posterior fusiform gyrus that we refer to as pFus-faces and one on the mid-fusiform sulcus that we refer to as mFus-faces (Weiner & Grill-Spector, 2010; Weiner et al., 2010). The centers of these face-selective regions are spatially dissociable as mFus-faces is 15 mm anterior to pFus-faces (Talairach coordinates in Table 1). Further, these two face-selective regions are separated by regions with different selectivity: a limb-selective region (Fig. 7b) located laterally on the occipitotemporal sulcus (OTS), which we refer to as OTS-limbs rather than the FBA because it seldomly extends to the fusiform (even in the original reports; see Peelen & Downing, 2005; Schwarzlose et al., 2005), and a more medial fusiform activation that responds more strongly to many categories compared to scrambled versions of these images (Fig. 7c, previously referred to as mFus-objects see Grill-Spector, 2003). Second, each face- and limb-selective region has a preserved spatial relationship relative to one another across subjects and hemispheres: mFus-faces is anterior and medial to a more posterior and lateral OTS-limbs, and pFus-faces is consistently posterior and medial to a more anterior and lateral OTS-limbs (Fig. 6). The locations of activations are also spatially reliable relative to nearby visual field maps hV4, VO-1, and VO-2 (see Weiner & Grill-Spector, 2010). Importantly, these activations are reproducible over a span of 3 years, across imaging resolutions, and different contrasts used for localization (Supplementary Figs. 1, 2 and Supplementary Materials). These reliable anatomical and functional boundaries are indicative of a topographic relationship among face- and limb-selective regions in VTC that has gone undocumented.

Finding a consistent anatomical location and spatial relation among functional activations is important because these two criteria reflect fundamental cortical organization principles. Importantly, these two principles have been used to parcellate cortex in the macaque (Felleman & Van Essen, 1991) and are evident among early retinotopic areas across primate species. For example, in humans, there are a series of retinotopic maps in each hemisphere extending from V1 dorsally in a specific order with particular characteristics: a hemi-field representation (V1), two mirror-reversed quarter-fields (V2d, V3d), and a second hemi-field representation (V3a). Since this mapping is consistent across subjects, researchers are able to define these regions identically in individual subjects. Our data extend these principles of consistent anatomical location and spatial relation among activations to high-level regions and provide strong evidence for a parsimonious organization principle applicable to the entire visual system. In contrast, domain-specificity (which is the principle used to derive the FFA and EBA) proposes separate organization principles across visual cortex: retinotopy in early and intermediate visual areas and functionally specialized modules for a select number of categories in high-level visual cortex (Kanwisher, 2010). As an outcome, the visual system is dichotomized where it is highly organized across early visual areas and rather disorganized across high-level visual areas. However, this disorganized principle of high-level visual cortex is problematic as we have shown that prior definitions of the FFA violate these two principles of anatomical location and spatial relationship, where both the anatomical location of the FFA and the spatial relationship between the FFA and FBA change from subject to subject (Peelen & Downing, 2005; Peelen et al., 2006; Pinsk et al., 2009; Schwarzlose et al., 2005). The present data clarify this discrepancy by showing that there are actually two face-selective regions 15 mm apart on the fusiform instead of a single FFA, where these regions are reliably separable by the limb-selective OTS.

These findings in VTC lead to an important question: Does this consistent topographic relationship among face- and limb-selective regions extend to LOTC? If so, this would suggest that the parsimonious organization principle discovered in VTC is generalizable throughout high-level visual cortex. We recently addressed this question empirically (Weiner & Grill-Spector, 2011) and summarize our results below.

To address if the consistent topographic relationship among face- and limb-selective regions observed in VTC extends to other portions of the brain, we measured face- and limb-selective responses in each subject’s LOTC using the same analyses described in the prior section. In addition, we also localized hMT+ in each subject because it is adjacent to these activations and is associated with a specific anatomical location on the ascending limb of the posterior inferotemporal sulcus (Amano et al., 2009; DeYoe et al., 1996; Dumoulin et al., 2000; Tootell et al., 1995; light blue outlined in black in Fig. 1). Thus, it serves as a reliable anchor from which to generate functional boundaries that are closely linked to the underlying anatomy (see Weiner & Grill-Spector, 2011 for details). Similar to the analysis of VTC organization, we examined the spatial organization of limb- and face-selective regions relative to each other in LOTC, as well as relative to (1) anatomical landmarks, (2) hMT+, and (3) known visual field maps.

As in VTC, we illustrate three important findings regarding the functional organization of LOTC (Fig. 6; Supplementary Figs. 3, 4): (1) there are several face- and limb-selective activations in LOTC in distinct anatomical locations, (2) they have a consistent spatial organization relative to each other, as well as (3) relative to hMT+. Specifically, we do not find evidence for one EBA in LOTC, as is commonly reported, but rather a series of limb-selective activations located around the perimeter of hMT+ (illustrated by a dotted black line in Fig. 6) where each is associated with a distinct anatomical landmark and consistent spatial relation to hMT+ (Table 1 for Talairach coordinates). The first activation is located on the lateral occipital sulcus/inferior portion of the middle occipital gyrus (LOS/MOG) and is posterior to hMT+. The second activation is located on the inferior temporal gyrus (ITG) and inferior to hMT+. The third activation is located on the middle temporal gyrus (MTG) and anterior to hMT+. The crescent organization surrounding hMT+ is reproducible over a span of 3 years (Supplementary Fig. 3) and a variety of contrasts using different body part and control stimuli (Supplementary Fig. 4). Furthermore, using anatomical landmarks and the spatial relationship to hMT+ to define the original limb-selective ROIs accurately predicts functional differences across these ROIs 3 years later (Supplementary Fig. 4).

Notably, there is also a consistent organization of LOTC limb-selective regions relative to face-selective regions as illustrated in Fig. 6 (see also Supplemental Fig. 1 from Weiner & Grill-Spector, 2010). In particular, there is a ring organization of alternating face- and limb-selective regions surrounding, but largely not encroaching into, hMT+. Specifically, the face-selective pSTS is superior to hMT+ and located between the limb-selective LOS/MOG and limb-selective MTG. Likewise, the face-selective IOG is located between the limb-selective LOS/MOG and the limb-selective ITG, as well as located on the inferior corner of hMT+.

Taken together, the alternating series of face- and limb-selective regions in VTC extends to LOTC, indicating that the topographic relationship between face- and limb-selective regions generalizes across high-level visual cortex. Furthermore, our data illustrate there is not one EBA in LOTC and not one FFA in VTC, but rather a fine-scale spatial organization of these activations relative to one another and specific anatomical landmarks. It is possible that this organization has previously been missed because of methodological reasons such as scanning with larger voxels (>3 mm) and the use of inplane visualizations. We directly relate the stability of our higher-resolution measurements to measurements with larger voxels and different visualizations below.

Theoretical interpretations resulting from functional organization measured with fMRI depend on a variety of factors, such as the way in which data is acquired, analyzed, and visualized. In Table 2, we summarize a variety of methodological recommendations to improve the mapping of functional activations in high-level visual cortex. When possible, scanning with smaller functional voxels (1–2 mm) is encouraged because the higher spatial resolution reduces the effects of partial voluming and susceptibility artifacts (Supplementary Fig. 5; Winawer, Horiguchi, Sayres, Amano, & Wandell, 2010) compared to larger voxels, which in turn increases the spatial specificity of measurements. In particular, detecting functional activations in the posterior fusiform, inferior occipital, and inferotemporal gyri can be affected by artifacts produced by the transverse sinus (Supplementary Fig. 5; Winawer et al., 2010). Furthermore, when restricting data to gray matter, the organization with small (~1.5 mm) and large (~3-4 mm) voxels is similar, but the combination of spatial smoothing and not segmenting gray from white matter produces spatially inaccurate measurements (Fig. 8; Supplementary Fig. 6). In addition, 3D surface visualizations in single subjects enable a bird’s eye view of the global organization of high-level visual cortex without being restricted to a particular slice orientation as is the case with inplane or volume visualizations.

Taken together, the exploration of these methodological issues (Supplementary Materials) indicate that the factor most detrimental to accurately examining spatial organization of functional activations is spatial smoothing. Even researchers using large voxels and inplane visualizations can implement the parcellation methods used here as long as spatial smoothing is not used (Fig. 8). Importantly, precisely defining functional regions at the correct spatial scale and anatomical location identifies functional distinctions among activations that are lost when data are spatially smoothed or inaccurately combined (e.g. Figs. 3, 4). For example, in VTC, mFus-faces shows more fMRI-adaptation to repeated images than pFus-faces, illustrating a potential hierarchical organization extending from V1 into VTC based on adaptation characteristics (Fig. 9a; adapted from Weiner et al., 2010). Similarly, functional differences are found in LOTC, whereby LOS-, ITG- and MTG-limbs illustrate different retinotopic properties. There is a strong contralateral bias in LOS-limbs, which decreases progressively to MTG-limbs, with a concomitant increase in foveal bias (Fig. 9b; adapted from Weiner & Grill-Spector, 2011).

Faces and limbs are ecologically and socially relevant classes of visual stimuli with a statistical regularity in their visual appearance: heads are most often above bodies and limbs are often just offset from the body. The present data show that this consistent topography of faces and limbs in stimulus space is reflected in cortical space where there is a consistent topographic nature of face- and limb-selective regions. A well-known example illustrating a correspondence between stimulus space and neural representation is a retinotopic map, where two adjacent points in visual space are projected to two adjacent points on the retina. This retinotopic relationship then extends to visual cortex where adjacent points on the retina map to adjacent locations on the cortical surface (Wandell & Winawer, 2011 for review). Unlike retinotopic mapping methods, our stimuli are not presented in a way that smoothly varies the relative positions of faces and limbs. Instead, all our stimuli are presented in the center of the visual field, in line with the early studies from Kanwisher and colleagues. However, when one sees an image of a face, it is understood that the body (limbs included) are underneath it (and vice versa). We propose that the regularity in which faces, limbs, and bodies are presented relative to one another in everyday life has been incorporated into the visual system resulting in a map of alternating face- and limb-selective regions throughout high-level visual cortex. A recent paper supports this proposal illustrating a topographic organization for body part representation (upper/lower half of the face, arms, legs, and torso) in human LOTC (Orlov et al., 2010). However, Orlov and colleagues did not propose a parcellation scheme or report the regularity of face- and limb-selective organization relative to anatomical landmarks. Thus, our data introduce a new set of principles, and in turn an unconsidered organization, of high-level visual cortex where there is a systematic and alternating representation of faces and limbs in predictable anatomical locations.

We label these face- and limb-selective activations as ‘regions’ rather than ‘areas’ and preface the type of stimulus selectivity with the anatomical loci of these regions most consistently found across subjects (e.g. pFus-faces or OTS-limbs). Such a labeling reflects the preserved spatial relationship of anatomical landmarks, as well as the alternating stimulus selectivity. Since large-scale neuroanatomy is stable, the spatial relationship of anatomical landmarks will be preserved, as will the relationship among the associated functional regions. For example, anatomically, the ITG will always be anterior to the IOG. Functionally, then, ITG-limbs will always be anterior to IOG-faces. This principle is also applicable within a given anatomical structure such as the fusiform gyrus where mFus-faces will always be anterior to pFus-faces. Consequently, using these labels will increase the generalizability within a subject across time (Supplementary Figs. 1–4), across subjects, and across research groups examining either typical or atypical subject populations.

The present data indicate the correspondence between gross anatomical landmarks and a given functional region in high-level visual cortex, which allows the potential integration of identified regions with underlying anatomical structure (such as cytoarchitecture) in future studies of typical and clinical populations. The utility of this prospect is illustrated in a recent study examining cytoarchitechtonic differences of the fusiform gyrus in post-mortem brains of autistics and typical subjects (van Kooten et al., 2008). Specifically, van Kooten et al., (2008) write: ‘The fusiform face area (FFA) within the (fusiform gyrus) could not be identified separately because neither gross anatomical landmarks nor cytoarchitectonic criteria have been established in the literature to identify the FFA within the (fusiform gyrus) in human post-mortem brains’ (p. 989). Thus, the present findings now make it possible for future studies to link known functional properties with underlying neuroanatomical structures in high-level visual cortex of either typical or atypical populations. While the present mapping methods are conducted in individual subjects with high-resolution fMRI to assure precise functional localization that respects the nuances of each subject’s anatomy that group analyses do not allow, there is promise to combine the multiple mapping methods used here from individual subjects into an average functional brain that respects the macro-anatomical structure of each respective subject as recently illustrated using a probabilistic atlas approach across subjects (Frost & Goebel, 2011).

In addition to gross anatomical landmarks, we also provide a precise model of high-level visual cortex documenting a preserved spatial relationship among regions (Fig. 10), which can be used to compare to cortical organization in clinical populations. Present fMRI work examining the cortical consequence of perceptual deficits in face perception examines the presence, size, connections, or functional properties of a specific activation in patient populations (Golarai et al., 2010; Rossion et al., 2003; Schiltz et al., 2006; Thomas et al., 2009). But, how category-selective regions are organized relative to other high-level visual regions is also critical. For example, it may be possible that some clinical conditions may be associated with spatial reorganization of these regions. If so, the measurements proposed here and the comparison to the standard model (Fig. 10) could be used as diagnostics for identifying the condition in an individual subject.

Technological advancements enabling fMRI of awake, behaving non-human primates (Logothetis, Guggenberger, Peled, & Pauls, 1999), reveal as many as six face-selective patches in specific anatomical locations in the macaque temporal lobe (Freiwald & Tsao, 2010; Freiwald, Tsao, & Livingstone, 2009; Hadj-Bouziane, Bell, Knusten, Ungerleider, & Tootell, 2008; Hoffman, Gothard, Schmid, & Logothetis, 2007; Ku, Tolias, Logothetis, & Goense, 2011; Pinsk et al., 2009; Pinsk, DeSimone, Moore, Gross, & Kastner, 2005; Tsao, Freiwald, Knutsen, Mandeville, & Tootell, 2003; Tsao, Freiwald, Tootell, & Livingstone, 2006; Tsao et al., 2008). These patches contain a large proportion of face-selective neurons ranging between 52% and 97% of visually-responsive neurons (Freiwald & Tsao, 2010; Freiwald et al., 2009; Moeller, Freiwald, & Tsao, 2008; Tsao et al., 2006), which is much higher than 20–35% reported by early neurophysiology studies (Baylis et al., 1987; Desimone et al., 1984). Microstimulation methods further demonstrate that these face-selective patches are interconnected, creating an extended face-selective network (Moeller et al., 2008). But, what about limbs?

Just as the study of face-selective neurons gained popularity before the study of body part-selective neurons (see History section), there have been more fMRI studies examining face-selective regions in the monkey than regions selective for images of limbs or bodies. However, a few studies using either fMRI or optical imaging in monkeys report body part-selective patches cortically proximate to face-selective clusters (Borra, Ichinohe, Sato, Tanifuji, & Rockland, 2010; Pinsk et al., 2005, 2009; Sato, Uchida, & Tanifuji, 2008; Tsao et al., 2003), suggesting that the adjacent and alternating relationship among face- and limb-selective activations reported here may extend to monkeys. Most recently, using fMRI-guided neurophysiology, Bell et al., (2011) examined the relationship between the distribution of neurons within and outside face- and limb-selective regions localized with fMRI reporting three relevant findings. First, the concentration of selective neurons within face- and limb-selective regions was higher than for object- and place-selective regions. This supports our present stance that face- and limb-selective neural responses are good comparator systems for one another. Second, there were higher percentages of selective neurons within a given region than just outside (1–4 mm) or far outside (>4 mm) it, with the highest proportions in the center of a region. This indicates that the ‘inter-cluster’ distance between regions selective for faces and limbs contain selective neurons, but in smaller concentrations than within regions. Third, the proportions of recorded cells outside a region corresponded nicely to those percentages reported from the early studies of face-selective cells reviewed here (Perrett et al., 1982; Baylis et al., 1987; Desimone et al., 1984). These results indicate the utility of studying face- and limb-selective regions together, as well as the benefit of using high-resolution fMRI in humans (without spatial smoothing) to target the regions of interest since the highest concentration of selective neurons are likely to be in the center of fMRI activations. Further, these data support both modular and distributed elements in the organization of face- and body part-selective responses, which is consistent with other recent studies that used anatomical tracers in monkeys (Borra et al., 2010), as well as our results of a sparsely-distributed organization in humans revealed by high-resolution fMRI measurements (Weiner & Grill-Spector, 2010).

An important question remaining for future studies is: What are the mechanisms that generate the cortical correspondence among face- and limb-selective regions? One possibility is that neural responses to face and limb stimuli develop over time due to their joint frequency in the environment. This suggests that the selectivity of face and limb regions results from the ecological relevance of faces and limbs, as well as their high frequency in the natural world. However, reports of face-selective neurons in monkeys as young as five and a half weeks (Rodman, Scalaidhe, & Gross, 1993; Rodman, Skelly, & Gross, 1991) raise the possibility of an early maturation of these activations or even an innate bias for these stimuli. A related question is whether adjacent face- and limb-selective patches reflect two neighboring but separate cortical systems for face and limb processing, or a single system of alternating (but interconnected) face- and limb-selective regions that share connections at their boundaries. Some clues regarding this question come from microstimulation experiments, where microstimulating face-selective clusters in monkeys yields activation in other face-selective sites, but also extends outside their boundaries (Moeller et al., 2008)—where the present data would suggest a limb-selective region. Future work using a combination of methods such as fMRI, microstimulation, and single unit recording may address the transition between each stage of organization from single neurons to columns, to functional regions, to adjacent and alternating networks in IT cortex. These future studies will shed light on the organizational mechanisms across micro- and macro-level scales.

The ventral stream extends from early visual areas to ventral aspects of the occipital and temporal lobe (Fig. 1). It is well known that VTC is involved in visual recognition from lesion studies in monkeys and neuropsychological studies in humans documenting that damage to different portions of the temporal lobe produces specific deficits in object and/or face recognition (Damasio et al., 1982; Farah, 1990; Goodale, Milner, Jakobson, & Carey, 1991; Rossion et al., 2003; Sergent & Signoret, 1992; Ungerleider & Mishkin, 1982). Consistent with these reports, functional neuroimaging studies show that activations in VTC are correlated with successful recognition (Bar et al., 2001; Grill-Spector, Kushnir, Hendler, & Malach, 2000; Moutoussis & Zeki, 2002). For example, face-selective regions in lateral VTC show higher responses for the successful perception of faces during illusory and ambiguous stimuli (Andrews, Schluppeck, Homfray, Matthews, & Blakemore, 2002; Hasson, Hendler, Ben Bashat, & Malach, 2001; Tong, Nakayama, Vaughan, & Kanwisher, 1998), as well as for detection and identification of faces (Grill-Spector, Knouf, & Kanwisher, 2004). Given this role of VTC in visual recognition, and the adjacency of limb-selective regions relative to face-selective regions, we predict that the limb-selective OTS is involved in recognition of body parts, which can be tested in future research. In addition to the fine-grained parcellation of face- and limb-selective regions based on both anatomical and functional boundaries in VTC, there are also functional differences between more general anatomical subdivisions of VTC. Specifically, lateral VTC (from the occipitotemporal sulcus to mid-fusiform sulcus) illustrates qualitatively different temporal dynamics than medial VTC (from the mid-fusiform sulcus to parahippocampal gyrus) during prolonged presentations of various visual stimuli (Gilaie-Dotan, Nir, & Malach, 2008) and repetitions of visual stimuli across different timescales (Weiner et al., 2010). Based on these results, we have recently proposed that lateral VTC is involved in perception, whereas medial VTC is a gateway between perception and memory (Weiner et al., 2010). Future studies will help elucidate behavioral consequences of these organizational differences and how they affect aspects of perception and memory.

The dorsal stream extends from early visual areas to the dorsal aspects of the occipital lobe extending into the parietal lobe. Prevailing views implicate the dorsal stream in different aspects of spatial vision (Ungerleider & Mishkin, 1982), visually guided actions toward objects (Goodale et al., 1991), and even time (Battelli, Pascual-Leone, & Cavanagh, 2007). Here, we focus only on the posterior aspect of the parietal lobe, as the processes within this cortical region are largely visual in nature. We recently reported a limb-selective region (limb-selective IPS) consistently overlapping visual field map V7 (also referred to as IPS-0; Swisher et al., 2007), where this limb-selective IPS is sensitive to the position of the limb in the visual field (Weiner & Grill-Spector, 2011). In addition to selectivity for static limb images, posterior parietal cortex in and around V7 has also been implicated in different aspects of spatial working memory, attention, and motion (Konen & Kastner, 2008; Orban et al., 2006; Silver et al., 2005; Tootell et al., 1998; Xu & Chun, 2006), indicating the integration of several computational processes within this cortical region. Indeed, a series of studies examining the neural processing of limb actions have documented a clear anatomical and functional dissociation of parietal cortex where posterior IPS regions are involved in the observation and visual guidance of limb movements (a combination of position, motion, and limb form), while the anterior IPS regions are more involved in the execution of limb movements themselves (Filimon, Nelson, Huang, & Sereno, 2009; Levy, Schluppeck, Heeger, & Glimcher, 2007). Such results are in line with patient studies reporting that focal damage to posterior parietal cortex produces specific deficits in identifying and pointing to body parts—either their own (autotopagnosia; De Renzi, 1982; Ogden, 1985) or others (heterotopagnosia; Auclair, Noulhiane, Raibaut, & Amarenco, 2009; Cleret de Langavant, Trinkler, Cesaro, & Bachoud-Levi, 2009). Whether this perceptual deficit is a direct result of local cortical damage or reflects a disruption of connections within the extended cortical network of limb-selective regions in the ventral or lateral pathways is an open question. We propose that the posterior parietal cortex (in the vicinity of V7) is a transitional stage in the dorsal pathway functioning to convert visual inputs into action outputs, whereas the anterior IPS is more involved in the actions themselves. Relevant to the topics in this Special Issue, future research will elucidate whether the limb-selective IPS reflects visual processing associated with the form of the limb itself, or reflects a visual representation embodied in the context of an action representation.

Traditionally, the visual system is divided into ventral and dorsal pathways, where area MT is typically assigned to the dorsal stream consistent with its anatomical location in the monkey (Ungerleider & Mishkin, 1982). However, in humans, MT is farther from parietal cortex, located more inferiorly in the posterior inferior temporal sulcus (Dumoulin et al., 2000; Tootell & Taylor, 1995). This difference in the anatomical location of MT, as well as the more inferior positioning of the ventral stream and more superior location of the dorsal stream in humans compared to monkeys, has been proposed to reflect the cortical expansion accommodating emergent language properties in humans (Orban, Van Essen, & Vanduffel, 2004; Ungerleider, Courtney, & Haxby, 1998). Expanding on these proposals, we suggest that this difference reflects a lateral pathway in the human brain incorporating different aspects of vision, action, and language. For example, our present measurements document face- and limb-selective regions radiating around both MT and MST (Weiner & Grill-Spector, 2011; Fig. 10 for schematic). This organization seems to be specific to humans as fMRI studies in non-human primates illustrate face- and body part-selective regions cortically distant from MT, located more ventrally in portions of TEO and TE (Fig. 2; Tsao et al., 2003; Pinsk et al., 2009). We propose that the organization of face and limb-selective regions around hMT+ is a unique feature of the human lateral surface and expand on recent results from neuropsychology and neuroimaging studies providing evidence that LOTC is functionally distinct from the dorsal and ventral streams.

Neuropsychology studies examining face and body part processing suggest that damage to LOTC results in perceptual deficits separate from processing associated with dorsal or ventral high-level visual cortex. Damage to the lateral surface near the limb-selective LOS results in a general body agnosia with impairments in body part, but not object or face part, discrimination (Moro et al., 2008). Compared with deficits in body part localization and ownership associated with damage to posterior parietal cortex discussed above (Auclair et al., 2009; Cleret de Langavant et al., 2009; De Renzi, 1982; Ogden, 1985), these results illustrate a dissociation between the dorsal and lateral streams within the domain of body part processing. Within the domain of face processing, a variety of cortical lesions spanning different aspects of the ventral and lateral streams can each produce impairments in holistic face processing (Busigny, Joubert, Felician, Ceccaldi, & Rossion, 2010; Van Belle et al., 2011). However, lesions to the IOG are associated with selective impairments in discriminating face parts, but not object or body parts (Moro et al., 2008), which suggests functional differences between the ventral and lateral streams. These findings from neuropsychological studies implicate the cortical expanse posterior to MT (LOS for body parts and the IOG for faces; Fig. 10) with processing the visual form of the face and body. Paired with the fact that this portion of lateral occipital cortex also selectively responds to images of objects and shapes across multiple visual cues (Grill-Spector, 2003; Grill-Spector et al., 1998; Mendola, Dale, Fischl, Liu, & Tootell, 1999; Vinberg & Grill-Spector, 2008), suggests that regions posterior to MT are responsible for coding visual form more generally (Fig. 11).

Comparatively, the MTG, which is anterior to hMT+, is not strictly visual in nature, but shows polymodal response properties involved in different aspects of vision, action, and language—a feature that further distinguishes LOTC from the other processing streams. Based on our measurements, we refer to the MTG as limb-selective. However, prior studies also implicate the MTG and nearby ITG in executing hand movements (Astafiev, Stanley, Shulman, & Corbetta, 2004; Orlov et al., 2010), haptically exploring objects (Amedi, Malach, Hendler, Peled, & Zohary, 2001), and responding to tactile stimulations of the hand relative to the foot (Beauchamp, Laconte, & Yasar, 2009; Beauchamp, Yasar, Kishan, & Ro, 2007). The MTG has also been shown to code the rationality of movements (e.g. the mapping of action to meaning; Jastorff, Clavagnier, Gergely, & Orban, 2010), as well as the mapping of sounds to meaning (Glasser & Rilling, 2008; Wong, Chandrasekaran, Garibaldi, & Wong, 2011), suggesting that it may be an anatomical locus for the integration of gesture and language processing (Nelissen et al., 2010). Taken together, these studies indicate that the MTG may be a convergence zone of action representation embodying information across visual, tactile, haptic, and motor domains with potential roles also in language processing and social communication, which is in line with previous proposals (Beauchamp & Martin, 2007; Martin, 2007). Overall, these data suggest that LOTC is organized differently than ventral or dorsal high-level visual cortex with distinct functions that separate it from either pathway. Future research using multiple functional and anatomical methods will support or refute our proposal of the lateral pathway as a distinct processing stream.