The ability to recognize faces is essential for navigating our social world. The human visual system can effortlessly categorize, identify, and remember thousands of faces over a lifetime. Research using functional magnetic resonance imaging (fMRI) has identified several regions in the human visual cortex that specifically and selectively respond to faces, but key questions remain with respect to the neural mechanisms underlying face recognition. For example, it is unclear whether face-selective regions are equally responsive to all human faces, or how perceptual measures of similarity correlate with neural measures of similarity between faces. With support from the National Science Foundation, the investigator will use recent methodological innovations that enable high-resolution fMRI, combined with innovative psychophysical methods and computational models to study the neural basis of within-category representation of faces. The project will identify the fundamental properties that drive responses in face-selective regions, determine whether these responses are tuned to the distribution of faces experienced by individuals over their lifetime, and determine whether measures of similarity of neural responses are tightly related to measures of perceptual or physical similarity among faces. Overall, this research will provide significant advancement in the understanding of how neural responses support our ability to identify individual faces.
The research will have significant implications beyond providing support for a particular computational theory of face representation. It would provide a useful tool for comparing the representations of any other visual category, for example, comparing between neural responses to faces and to objects, which is an issue of central debate. The understanding of neural correlates of normal face identification also provides an important baseline for understanding impairments in face identification as manifested in cogenital prosopagnosia, Asperger's Syndrome and Autism, and as such has broad health and societal implications. This project also aims to advance neuroimaging methods by further developing high-resolution fMRI techniques and by examining whether different experimental designs and analyses for high-resolution imaging show convergent results. Finally, this research will provide training opportunities for students at the undergraduate, graduate, and post-doctoral levels.
Recognizing people from their faces and bodies is important for social interactions. Indeed, humans recognize thousands of faces in their daily lives. However, the brain mechanisms underlying this remarkable ability are still mysterious. In this project, funded by the NSF, we studied how the human brain represents faces and bodyparts and how these brain representations are linked to perception. In brief, the human visual system contains more than 30 areas. Prior research has found that the human visual cortex contains high-level visual regions responding preferentially to images of faces and bodyparts. Here, we used high-resolution (e.g. finer-grained than typically implemented) functional magnetic resonance imaging (fMRI) to study how these regions are arranged in the brain, what are the functional characteristics of these regions, and how these regions contribute to conscious perception. Our studies yielded several significant findings that are reported in scientific peer-reviewed journals that are freely available to the public to read through PMC. First, we find that there is a fine-grained organization of high-visual cortex, where in fact there are multiple regions in visual cortex that respond selectively to images of faces or bodyparts over other stimuli (such as images of objects or places), rather than a single face or bodypart area dedicated for processing these stimuli, as suggested by prior research. Second, we find a very precise arrangement of these regions on the brain where face-selective regions tend to neighbor body-part selective regions. This finding is important as it suggests that face- and bodypart-selective regions are part of a large map of the human body and that experience with the statistics of the natural world in which faces are attached to bodies is translated and incorporated into brain representations. Third, while the prevailing view in the field is that both brain anatomy and function vary across people, we find that people’s brains are remarkably similar, and in fact there is a regular organization of visual areas in the brain with respect to other brain regions as well as with respect to the anatomy, i.e. the sulci and gyri which generate the foldings of the cortex (referred to as ‘cortical folding’). As an analogy, consider a hand. While there is a lot of variability across people in the size and shapes of their hands, there is a striking regularity across people in their hand structure: in every human hand, the thumb sticks out to the side, and the pinky is the smallest finger. Extending this analogy to our brain measurements, we find that the structure of high-level visual cortex is like a hand: it will differ in specific shape and size from person to person, but the organization is strikingly similar across people. In fact, our research has shown that the pattern of cortical folding alone can predict functional regions. That is, the location of functional regions follow the trajectory of peaks and valleys of an individual’s cortex, and the structural-functional fingerprint across individuals is strikingly similar. We have further found that this consistency across people may stem from the underlying microarchitecture (i.e. the density and arrangement of neurons across cortical layers). In other words we found that the microarchitectonic partitions of the cortex near face-selective regions is also predictable relative to the cortical folding. These results have important clinical implications as often clinicians have access to measurements of brain anatomy, but not function. Fourth, we found that neuronal responses in face-selective regions in the fusiform gyrus are tuned to the statistics of faces in the real world: There is a better representation of typical than atypical faces (presumably because the former are more frequently encountered) and there is high sensitivity to the variability among faces that is useful in discriminating facial identity. Finally, using a combination of cutting edge high-resolution fMRI, electrocorticography (ECoG), and electrical brain stimulation (EBS) we measured signals and stimulated specific parts of high-level visual cortex in a rare patient with electrodes implanted for clinical purposes. Our understanding of the fine-grained structural-functional fingerprints of high-level visual cortex allowed us to identify two electrodes that were placed on two face-selective regions in the fusiform gyrus. We found a striking causal relationship between neural responses in face-selective regions and face perception, as disrupting normal brain activity in these face-selective regions by EBS generated a specific deficit in face perception, but not object perception or word recognition. This scientific report received a lot of press. The video of the patient’s perceptual report is available free to the public for viewing: www.jneurosci.org/content/32/43/14915.long. Overall, our research has significantly advanced understanding of the neural representations underlying face and bodypart perception in the human visual cortex.
