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.