| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
REPORT
School of Psychology, University of Wales, Bangor, United Kingdom
Submitted 17 May 2004; accepted in final form 3 August 2004
 |
ABSTRACT |
|---|
 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONACKNOWLEDGMENTSREFERENCES |
|---|
|
INTRODUCTION |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONACKNOWLEDGMENTSREFERENCES |
|---|
; Kanwisher et al. 1997; Puce et al. 1995). FFA activity closely tracks awareness of the presence of a face (Andrews and Schluppeck 2004; Andrews et al. 2002; Hasson et al. 2001; Tong et al. 1998) as well as trial-by-trial psychophysical performance on face detection and identification tasks (Grill-Spector et al. 2004). One interpretation of these findings is that the FFA represents a cortical "module" for face processing.
Strong selectivity for a stimulus class, however, does not necessarily imply a dedicated system for processing that class. One alternative proposal is that the FFA may instead be better conceived as a mechanism for distinguishing visually similar exemplars of any object class for which the viewer has substantial expertise (Tarr and Gauthier 2000). This is supported, for example, by the finding that bird and car experts show increased FFA activity when viewing birds and cars, respectively (Gauthier et al. 2000). Others have gone further to suggest that the FFA, and highly-selective activation "peaks" in general, have no special functional role, but instead form part of a broad neural network that represents objects by a distributed collection of feature analyzers (Haxby et al. 2001; but see Spiridon and Kanwisher 2002). Thus the FFA has been at the center of a broader debate about the organization of ventral stream object representations (Cohen and Tong 2001; Kanwisher 2000; Levy et al. 2001).
The face, however, is not the only source of socially relevant cues; the rest of the body also conveys such information. Although human bodies and faces are visually dissimilar, they have other features in common. Both provide cues to identity, emotion, intention, age, and gender. For both bodies and faces, the differences between exemplars are metric rather than qualitative, and for both, most adults will have developed substantial perceptual expertise. Moreover, recent studies have shown behavioral effects for bodies that were generally thought to be specific for faces, such as a "body-inversion" effect (Reed et al. 2003) and an advantage for bodies in attentional capture (Downing et al. 2004).
There is some evidence that this conceptual and behavioral similarity between faces and bodies may be reflected in neural activity in the fusiform gyrus. One fMRI study found a significantly higher response in the FFA to bodies than to other object categories, although the response to bodies was significantly lower than to faces (Kanwisher et al. 1999). In this study, however, analysis of body-related activity was limited to a region functionally defined by contrasting faces versus houses. Another fMRI study, in which subjects were scanned while viewing segments of a James Bond movie, showed that bodies activate the fusiform gyrus near the FFA (Bartels and Zeki 2004). The stimuli in this study were not controlled, so it is not clear whether bodies, faces, or both were responsible for this activation. A recent event-related potential (ERP) study showed that the face-selective N170 is also elicited by bodies (with faces blurred), suggestive of shared underlying neural processes (Stekelenburg and de Gelder 2004). Note, however, that the relationship of the N170 to the FFA is unclear. Furthermore, the response to bodies in this study could also reflect contextual enhancement of the blurred faces (Cox et al. 2004). Finally, there is mixed evidence on whether the FFA response to the bodies of non-human animals is higher than the response to inanimate objects (Chao et al. 1999; Kanwisher et al. 1999; Grill-Spector et al. 2004).
Investigations of the macaque visual system also provide relevant findings. Single-unit recordings have revealed neurons distributed throughout the macaque temporal lobe, particularly in the superior temporal sulcus (STS), that respond to views of the face and body and to actions involving them (Jellema and Perrett 2003; Perrett et al. 1982; Wachsmuth et al. 1994). More recently, fMRI in the macaque has shown face- and body-selective activations in adjacent regions of the lower bank of the STS (Tsao et al. 2003). A homology between this region and human FFA has been proposed (Gauthier and Logothetis 2000; Tsao et al. 2003) although conclusive evidence is still lacking. Thus in the macaque the representations of faces and bodies appear to be intertwined in a region that may map to the fusiform gyrus in humans.
The preceding evidence leads to the prediction that human bodies, even without faces, may be represented in the human mid-fusiform gyrus. This possibility has not been tested rigorously to date. Therefore the three objectives of the present study were to use fMRI to measure the selectivity of neural responses to headless bodies in the fusiform gyrus, to compare the locations of body- and face-related activity in this region, and to test whether body selectivity in the fusiform gyrus generalizes to more abstract depictions of the human form.
|
METHODS |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONACKNOWLEDGMENTSREFERENCES |
|---|
Twenty-two healthy adult volunteers (12 female) were recruited from the University of Wales, Bangor community for the first experiment. Eight subjects (4 female; 1 of whom participated in the 1st experiment) participated in the second experiment. Participants satisfied all requirements in volunteer screening and gave informed consent. Ethics approval was obtained from the School of Psychology at the University of Wales, Bangor, United Kingdom, and the North-West Wales Health Trust. Participation was compensated at £20 per session.
Experimental paradigm
The first experiment consisted of images of faces, human bodies without heads, outdoor scenes, and handheld tools presented in a blocked design (see Fig. 1A). There were 40 exemplars of each category, divided into two sets (A and B).
|
The second experiment tested 15 stick figures and 15 scrambled control items (see Fig. 1B). Fifteen-second blocks from each condition were alternated with intervening fixation baseline blocks as in the preceding text. Two orders of each design were tested between subjects to counterbalance for order effects. In each block, 15 images were presented (300 ms on, 700 ms off for each item).
In both experiments, subjects performed a "one-back" repetition-detection task, in which they were asked to press a button whenever an image occurred twice in immediate succession. Two image repetitions occurred at randomly selected points in each block.
Functional imaging and analysis
DATA ACQUISITION.
A 1.5 T Philips MRI scanner with a SENSE (Pruessmann et al. 1999) parallel head coil was used. For functional imaging, an EPI sequence was used (TR = 3,000 ms, TE 50 ms, flip angle 90°, FOV = 240, 30 axial slices, 64 x 64 in-plane matrix, 5 mm slice thickness). The scanned area covered the whole cortex and most of the cerebellum.
DATA ANALYSIS.
Preprocessing and statistical analysis of MRI data were performed using BrainVoyager 4.9 (Brain Innovation, Maastricht, The Netherlands). The first three volumes of each run were discarded to avoid differences in T1 saturation. Functional data were motion-corrected, and low-frequency drifts were removed with a temporal high-pass filter (0.006 Hz). Functional data were manually co-registered with three-dimensional (3D) anatomical T1 scans (1 x 1 x 1.3-mm resolution), and then resampled to isometric 3 x 3 x 3-mm voxels with trilinear interpolation. The 3D scans were transformed into Talairach space (Talairach and Tournoux 1988), and the parameters for this transformation were subsequently applied to the co-registered functional data.
To generate predictors for the multiple-regression analyses, the event time series for each condition were convolved with a delayed gamma function (delta = 2.5 s; tau = 1.25 s) to model the hemodynamic response (Boynton et al. 1996). Voxel time series were z-normalized for each run, and additional predictors accounting for baseline differences between runs were included in the design matrix.
ROI DEFINITION AND PEAK-VOXEL COMPARISON. For each subject, we located the most significantly activated voxel for the contrast faces versus tools and the contrast bodies versus tools, within a restricted part of ventral cortex (Talairach coordinates: 30 < x < 50, –60 < y < –30, –30 < z < –5). Regions of interest (ROIs) for the first experiment were defined as the set of contiguous voxels that were significantly (P < 0.05, uncorrected for multiple comparisons) activated within 8 mm in the anterior/posterior, superior/inferior, and medial/lateral direction of the most significantly activated voxel. For the first experiment, runs 1 and 3 were combined to define the ROIs for runs 2 and 4, and vice versa. Thus the data used for ROI definition were independent from the data reported. For the second experiment, face- and body-selective ROIs were identified based on an independent set of localizer data.
To further examine the spatial relationship between ROIs, the locations of the most significantly activated voxels for faces and bodies (vs. tools) were compared within subjects. We calculated three measures of the linear distance between the most significant voxels. Measure 1 was the distance between peaks within a category and stimulus set. The locations of the most significant voxels of runs 1 + 3 and runs 2 + 4 were compared for faces and bodies separately. Thus in this comparison, each set of data contained one run for each of the two stimulus sets. This measure serves as a baseline estimate of how the peak location for identical stimuli varies between scans. Measure 2 was the distance between peaks within a category but across stimulus sets. The locations of the most significant voxels of runs 1 + 2 and runs 3 + 4 were compared, again for faces and bodies separately. This tests how spatially consistent responses are to different exemplars of the same category. Measure 3 was the distance between peaks across categories. The locations of the most significant voxels of runs 1 + 3 (e.g., for faces) and runs 2 + 4 (e.g., for bodies) were compared. Likewise, peak voxels from runs 1 + 2 and runs 3 + 4 were compared, again across categories. This measure tests whether the face- and body-selective foci occupied different locations.
Note that in these measures, the mean distance between peak voxels can be smaller than the distance between two adjacent voxels in a single scan. These distance measures are conservative in the sense that they could fail to detect differences in the location of peaks that are smaller than the scanned resolution but could not artifactually create such a difference where one did not exist at a finer scale.
|
RESULTS |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONACKNOWLEDGMENTSREFERENCES |
|---|
). The body contrast, but not the face contrast, activated an occipito-temporal region bilaterally, corresponding to the "extrastriate body area" (EBA) (Downing et al. 2001).
|
|
|
). In contrast, the BSR did not distinguish faces and bodies (t21 = 0.5, P = 0.60) and responded more to faces and bodies than tools (t21 = 6.9, P < 0.001 and t21 = 7.4, P < 0.001) and scenes (t21 = 5.9, P < 0.001 and t21 = 7.8, P < 0.001). No differences were observed in the response to tools and scenes in either region (both P's > 0.35). The interaction between category and ROI indicates that the two ROIs occupied at least partially different locations. To compare the location of fusiform BSR and FSR activity within subjects, we calculated the distance between the most significant voxels: within-category, within-stimulus set; within-category, between-stimulus set; and between-categories (see METHODS). No effect of stimulus set (measure 1 vs. measure 2) was observed [F(1,21) = 0.02, P = 0.9] nor did this depend on category [F(1,21) = 0.4, P = 0.54], showing that different exemplars of the same category produce similar activation peaks. In contrast, we found a significantly larger distance across categories [measure 3; 7.5 ± 0.7 (SE) mm] than within categories (measure 2; 5.7 ± 0.6), t21 = 3.0, P < 0.01, indicating distinct peaks of activation for bodies and faces. We also tested whether there was a consistent spatial relationship between the FSR and BSR within subjects. The difference in locations between ROIs did not significantly differ from zero in the x, y, and z directions, all P > 0.20, indicating that there was no consistent relationship between the two ROIs, at least in 3D space.
In a second experiment, we compared headless stick figure depictions of bodies and scrambled control figures (Fig. 1B). Abstract stimuli such as these minimize the differences in image features between body and nonbody stimuli. A significant interaction, F(1,7) = 7.6, P < 0.05, showed that the difference between stick figures and controls differed between the BSR and the FSR. The response to stick figures was significantly higher than to controls in the BSR (t7 = 2.6, P < 0.05), but not in the FSR (t7 = 0.5, P = 0.62). The OFA likewise showed no significant difference, (t7 = 1.1, P = 0.33). There was a significant effect in both the right EBA (t7 = 3.4, P < 0.05) and the left EBA (t7 = 3.5, P < 0.05), replicating previous findings (Downing et al. 2001). Response magnitudes in all of these regions are given in Fig. 3B. The selective response to stick figures as compared with scrambled controls was strong enough to show up in a whole-brain, group-averaged, fixed-effects multiple regression analysis. Significant activation (P < 0.0005 uncorrected) was found in the right fusiform gyrus (peak Talairach coordinates: 41, –38, –21) and bilaterally in the vicinity of the EBA (left: –49, –74, 9; right: 47, –62, 6).
|
DISCUSSION |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONACKNOWLEDGMENTSREFERENCES |
|---|
One account of our findings could be that perceiving bodies leads observers to mentally image the missing faces, which in turn activates face-selective neurons. This is unlikely to explain our results for several reasons. The body stimuli were unfamiliar and not associated to a particular face; it may not be possible to mentally image a "generic" face in this situation. Second, a previous study has compared the FFA response to front, side, and back views of heads (Tong et al. 2000). The back of the head, particularly when viewed in context with frontal views of the same individuals, would be expected to induce mental imagery for the missing face at least as strongly as bodies, yet FFA responses to this condition were comparable to inanimate objects. Finally, even explicit instruction to image specific faces produces relatively weak FFA activation that is not sufficient to explain the strong body selectivity seen here (O'Craven and Kanwisher 2000).
A related proposal is that bodies provide a context that causes ambiguous perceptual input to be perceived as a face. Cox et al. (2004) showed that the mid-fusiform activity produced by a Gaussian blur was increased when it was shown in a face-like contextual relationship to a body (i.e., atop the neck). (The selectivity of this region for faces:scenes, however, was low, raising the possibility that it did not correspond perfectly to the FFA as defined in previous reports.) Here, however, we showed only headless bodies without any stimulus that could be contextually enhanced.
Another possible account of the present findings relates to retinal eccentricity (Levy et al. 2001). Lateral visual areas, including the fusiform gyrus, are thought to be important for center-biased visual field representations, whereas more medial areas are thought to be important for periphery-biased field representations. Bodies and faces are likely to be represented more centrally than scenes; this could account for the higher response to bodies and faces relative to scenes. Tools, however, often contain fine details that need central processing to discriminate, and the response in this region to tools was relatively low. Moreover, we found no significant difference in either fusiform ROI between the response to tools and scenes, arguing against a central visual field bias in this part of the fusiform gyrus.
How do the present findings improve our understanding of the ventral temporal lobe? The mid-fusiform gyrus is part of a nonretinotopic, high-level object representation system. Our results show that some neurons in this region distinguish bodies, as well as faces, from other object kinds. Other object categories (such as cars, birds, and "greebles") have also been shown to produce an enhanced, although much less selective, response in this region, particularly in subjects who are experts at distinguishing among exemplars of these categories (Gauthier et al. 2000). One possibility is that the same population of neurons is engaged by all of these categories. Activity in these neurons could thus reflect cognitive processes that are independent of the stimulus categories involved, such as distinguishing among visually similar exemplars. This seems improbable, at least for the case of faces and bodies, however, in light of our finding that selective foci for these categories occupy distinct locations. We suggest instead that different, possibly overlapping, populations of selective neurons co-exist at close quarters. Faces and bodies are represented by larger populations and/or more selective neurons than other categories. Existing data do not speak to the root cause of this bias, which could be present from birth or could develop through experience.
These findings must also be considered in light of the recent proposal that objects are represented in the ventral stream by distributed patterns of neural activity. On this view, highly selective peaks, such as those seen here for faces and bodies, play no unique role in this representation (Haxby et al. 2001). One way to test this prediction is to ask for which brain regions activity is systematically related to performance on perceptual tasks. A recent study using this approach (Grill-Spector et al. 2004) showed a positive correlation between successful face detection and identification and FFA activity. This relationship was not observed in other ventral areas, even those (such as the "parahippocampal place area" (Epstein and Kanwisher 1998)) where the response to faces is consistently low, and could in principle provide information relevant to face processing. This finding suggests that regions with high category selectivity may indeed have a privileged role in vision.
These considerations lead to possible avenues for further research. Scanning at higher resolution may help to elucidate the spatial relationship among subregions of the fusiform gyrus that show selectivity for faces, bodies, or other object kinds. Further stimulus or task manipulations will be necessary to determine whether these selective foci can be functionally dissociated. Finally, it will be important to determine for which categories activity in the fusiform region predicts trial-by-trial performance on perceptual tasks. If this relationship is found for the body-selective region identified here, it would provide additional evidence that the fusiform gyrus plays a previously unsuspected role in visual processing of the human body.
|
ACKNOWLEDGMENTS |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONACKNOWLEDGMENTSREFERENCES |
|---|
|
FOOTNOTES |
|---|
Address for reprint requests and other correspondence: P. Downing, School of Psychology, Centre for Cognitive Neuroscience, University of Wales, Bangor, United Kingdom LL57 2AS (E-mail: p.downing{at}bangor.ac.uk)
|
REFERENCES |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONACKNOWLEDGMENTSREFERENCES |
|---|
Andrews TJ, Schluppeck D, Homfray D, Matthews P, and Blakemore C. Activity in the fusiform gyrus predicts conscious perception of Rubin's vase-face illusion. Neuroimage 17: 890–901, 2002.[CrossRef][Web of Science][Medline]
Bartels A and Zeki S. Functional brain mapping during free viewing of natural scenes. Hum Brain Mapp 21: 75–85, 2004.[CrossRef][Web of Science][Medline]
Boynton GM, Engel SA, Glover GH, and Heeger DJ. Linear systems analysis of functional magnetic resonance imaging in human V1. J Neurosci 16: 4207–4221, 1996.
Chao LL, Martin A, and Haxby JV. Are face-responsive regions selective only for faces? Neuroreport 10: 2945–2950, 1999.[Web of Science][Medline]
Cohen JD and Tong F. Neuroscience. The face of controversy. Science 293: 2405–2407, 2001.
Cox D, Meyers E, and Sinha P. Contextually evoked object-specific responses in human visual cortex. Science 304: 115–117, 2004.
Downing PE, Bray D, Rogers J, and Childs C. Bodies capture attention when nothing is expected. Cognition 93: B27–B38, 2004.[CrossRef][Web of Science][Medline]
Downing PE, Jiang Y, Shuman M, and Kanwisher N. A cortical area selective for visual processing of the human body. Science 293: 2470–2473, 2001.
Epstein R and Kanwisher N. A cortical representation of the local visual environment. Nature 392: 598–601, 1998.[CrossRef][Medline]
Gauthier I and Logothetis N. Is face recognition not so unique after all? Cogn Neuropsy 17: 125–142, 2000.
Gauthier I, Skudlarski P, Gore JC, and Anderson AW. Expertise for cars and birds recruits brain areas involved in face recognition. Nat Neurosci 3: 191–197, 2000.[CrossRef][Web of Science][Medline]
Grill-Spector K, Knouf N, and Kanwisher N. The fusiform face area subserves face perception, not generic within-category identification. Nat Neurosci 7: 555–562, 2004.[CrossRef][Web of Science][Medline]
Halgren E, Dale AM, Sereno MI, Tootell RB, Marinkovic K, and Rosen BR. Location of human face-selective cortex with respect to retinotopic areas. Hum Brain Mapp 7: 29–37, 1999.[CrossRef][Web of Science][Medline]
Hasson U, Hendler T, Ben Bashat D, and Malach R. Vase or face? A neural correlate of shape-selective grouping processes in the human brain. J Cogn Neurosci 13: 744–753, 2001.[CrossRef][Web of Science][Medline]
Haxby JV, Gobbini MI, Furey ML, Ishai A, Schouten JL, and Pietrini P. Distributed and overlapping representations of faces and objects in ventral temporal cortex. Science 293: 2425–2430, 2001.
Jellema T and Perrett DI. Cells in monkey STS responsive to articulated body motions and consequent static posture: a case of implied motion? Neuropsychologia 41: 1728–1737, 2003.[CrossRef][Web of Science][Medline]
Kanwisher N. Domain specificity in face perception. Nat Neurosci 3: 759–763, 2000.[CrossRef][Web of Science][Medline]
Kanwisher N, McDermott J, and Chun MM. The fusiform face area: a module in human extrastriate cortex specialized for face perception. J Neurosci 17: 4302–11, 1997.
Kanwisher N, Stanley D, and Harris A. The fusiform face area is selective for faces not animals. Neuroreport 10: 183–187, 1999.[Web of Science][Medline]
Levy I, Hasson U, Avidan G, Hendler T, and Malach R. Center-periphery organization of human object areas. Nat Neurosci 4: 533–539, 2001.[Web of Science][Medline]
O'Craven K and Kanwisher N. Mental imagery of faces and places activates corresponding stimulus-specific brain regions. J Cogn Neurosci 12: 1013–1023, 2000.[CrossRef][Web of Science][Medline]
Perrett DI, Rolls ET, and Caan W. Visual neurones responsive to faces in the monkey temporal cortex. Exp Brain Res 47: 329–342, 1982.[Web of Science][Medline]
Pruessmann KP, Weiger M, Scheidegger MB, and Boesiger P. SENSE: sensitivity encoding for fast MRI. Magn Reson Med 42: 952–962, 1999.[CrossRef][Web of Science][Medline]
Puce A, Allison T, Asgari M, Gore JC, and McCarthy G. Differential sensitivity of human visual cortex to faces, letterstrings, and textures: a functional magnetic resonance imaging study. J Neurosci 16: 5205–5215, 1996.
Puce A, Allison T, Gore JC, and McCarthy G. Face-sensitive regions in human extrastriate cortex studied by functional MRI. J Neurophysiol 74: 1192–9, 1995.
Reed CL, Stone VE, Bozova S, and Tanaka J. The body-inversion effect. Psych Sci 14: 302–308, 2003.[CrossRef]
Spiridon M and Kanwisher N. How distributed is visual category information in human occipito-temporal cortex? An fMRI study. Neuron 35: 1157–1165, 2002.[CrossRef][Web of Science][Medline]
Stekelenburg J and de Gelder B. The neural correlates of perceiving human bodies: an ERP study on the body-inversion effect. Neuroreport 15: 777–780, 2004.[CrossRef][Web of Science][Medline]
Talairach J and Tournoux P. Co-Planar Stereotaxic Atlas of the Human Brain. New York: Thieme, 1988.
Tarr MJ and Gauthier I. FFA: a flexible fusiform area for subordinate-level visual processing automatized by expertise. Nat Neurosci 3: 764–769, 2000.[CrossRef][Web of Science][Medline]
Tong F, Nakayama K, Moscovitch M, Weinrib O, and Kanwisher N. Response properties of the human fusiform face area. Cogn Neuropsy 17: 257–279, 2000.[CrossRef]
Tong F, Nakayama K, Vaughan JT, and Kanwisher N. Binocular rivalry and visual awareness in human extrastriate cortex. Neuron 21: 753–759, 1998.[CrossRef][Web of Science][Medline]
Tsao DY, Freiwald WA, Knutsen TA, Mandeville JB, and Tootell RB. Faces and objects in macaque cerebral cortex. Nat Neurosci 6: 989–995, 2003.[CrossRef][Web of Science][Medline]
Wachsmuth E, Oram MW, and Perrett DI. Recognition of objects and their component parts: responses of single units in the temporal cortex of the macaque. Cereb Cortex 4: 509–22, 1994.
This article has been cited by other articles:
|
|
 |
|
  J. Jastorff and G. A. Orban Human Functional Magnetic Resonance Imaging Reveals Separation and Integration of Shape and Motion Cues in Biological Motion Processing J. Neurosci., June 3, 2009; 29(22): 7315 - 7329. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
H.-O. Karnath, J. Ruter, A. Mandler, and M. Himmelbach The Anatomy of Object Recognition--Visual Form Agnosia Caused by Medial Occipitotemporal Stroke J. Neurosci., May 6, 2009; 29(18): 5854 - 5862. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M. A. Pinsk, M. Arcaro, K. S. Weiner, J. F. Kalkus, S. J. Inati, C. G. Gross, and S. Kastner Neural Representations of Faces and Body Parts in Macaque and Human Cortex: A Comparative fMRI Study J Neurophysiol, May 1, 2009; 101(5): 2581 - 2600. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M. V. Peelen, N. Lucas, E. Mayer, and P. Vuilleumier Emotional attention in acquired prosopagnosia Soc Cogn Affect Neurosci, April 28, 2009; (2009) nsp014v1. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 A. Brancucci, G. Lucci, A. Mazzatenta, and L. Tommasi Asymmetries of the human social brain in the visual, auditory and chemical modalities Phil Trans R Soc B, April 12, 2009; 364(1519): 895 - 914. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 A. S. Heberlein and A. P. Atkinson Neuroscientific Evidence for Simulation and Shared Substrates in Emotion Recognition: Beyond Faces Emotion Review, April 1, 2009; 1(2): 162 - 177. [Abstract] [PDF]
|
|
|
|
 |
|
 R. Hari and M. V. Kujala Brain Basis of Human Social Interaction: From Concepts to Brain Imaging Physiol Rev, April 1, 2009; 89(2): 453 - 479. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
A. H. Bell, F. Hadj-Bouziane, J. B. Frihauf, R. B. H. Tootell, and L. G. Ungerleider Object Representations in the Temporal Cortex of Monkeys and Humans as Revealed by Functional Magnetic Resonance Imaging J Neurophysiol, February 1, 2009; 101(2): 688 - 700. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 D. Y. Tsao, S. Moeller, and W. A. Freiwald Comparing face patch systems in macaques and humans PNAS, December 9, 2008; 105(49): 19514 - 19519. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
R. F. Schwarzlose, J. D. Swisher, S. Dang, and N. Kanwisher The distribution of category and location information across object-selective regions in human visual cortex PNAS, March 18, 2008; 105(11): 4447 - 4452. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. V. Peelen, A. P. Atkinson, F. Andersson, and P. Vuilleumier Emotional modulation of body-selective visual areas Soc Cogn Affect Neurosci, December 1, 2007; 2(4): 274 - 283. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. C. Taylor, A. J. Wiggett, and P. E. Downing Functional MRI Analysis of Body and Body Part Representations in the Extrastriate and Fusiform Body Areas J Neurophysiol, September 1, 2007; 98(3): 1626 - 1633. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
C. Urgesi, B. Calvo-Merino, P. Haggard, and S. M. Aglioti Transcranial Magnetic Stimulation Reveals Two Cortical Pathways for Visual Body Processing J. Neurosci., July 25, 2007; 27(30): 8023 - 8030. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 R. A. Epstein and J. S. Higgins Differential Parahippocampal and Retrosplenial Involvement in Three Types of Visual Scene Recognition Cereb Cortex, July 1, 2007; 17(7): 1680 - 1693. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
P. Vuilleumier and J. Driver Modulation of visual processing by attention and emotion: windows on causal interactions between human brain regions Phil Trans R Soc B, May 29, 2007; 362(1481): 837 - 855. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
C. I. Baker, J. Liu, L. L. Wald, K. K. Kwong, T. Benner, and N. Kanwisher Visual word processing and experiential origins of functional selectivity in human extrastriate cortex PNAS, May 22, 2007; 104(21): 9087 - 9092. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
N. Kanwisher and G. Yovel The fusiform face area: a cortical region specialized for the perception of faces Phil Trans R Soc B, December 29, 2006; 361(1476): 2109 - 2128. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
P. E. Downing, A. W.-Y. Chan, M. V. Peelen, C. M. Dodds, and N. Kanwisher Domain Specificity in Visual Cortex Cereb Cortex, October 1, 2006; 16(10): 1453 - 1461. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
G. Kovacs, M. Zimmer, E. Banko, I. Harza, A. Antal, and Z. Vidnyanszky Electrophysiological Correlates of Visual Adaptation to Faces and Body Parts in Humans Cereb Cortex, May 1, 2006; 16(5): 742 - 753. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. Lange and M. Lappe A model of biological motion perception from configural form cues. J. Neurosci., March 15, 2006; 26(11): 2894 - 2906. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
R. F. Schwarzlose, C. I. Baker, and N. Kanwisher Separate Face and Body Selectivity on the Fusiform Gyrus J. Neurosci., November 23, 2005; 25(47): 11055 - 11059. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. A. Pinsk, K. DeSimone, T. Moore, C. G. Gross, and S. Kastner Representations of faces and body parts in macaque temporal cortex: A functional MRI study PNAS, May 10, 2005; 102(19): 6996 - 7001. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| Visit Other APS Journals Online |
