DESCRIPTION (provided by applicant): Humans recognize and categorize the visual input in about a tenth of a second. However, it is still a mystery how the brain achieves this remarkable ability. The cortical visual recognition system consists of a processing stream starting in V1 and ascending into high-level visual areas associated with recognition in ventral temporal cortex (VTC). The goal of the proposed research is to make important theoretical and empirical progress in our understanding of the neural basis of recognition by examining the interplay between neural implementation, representations, and computations in human VTC. Prior research from our lab used high-resolution functional magnetic resonance imaging (HR-fMRI) to advance understanding of the functional organization of VTC by generating an organizational framework detailing its neuroanatomical and topological characteristics. Leveraging these findings, this proposal uses an innovative approach with cutting edge techniques combining HR-fMRI, macro-anatomical, cytoarchitechtonic and myeloarchitectonic measurements, high spatial and angular resolution diffusion imaging (HARDI), advanced tracking algorithms, and computational modeling to address the following three key questions: (1) Is neural microarchitecture an implementational constraint underlying the topological organization of functional representations in VTC? (2) Does structural and functional connectivity regulate functional representations of VTC? (3) How does the neural implementation relate to computations in VTC? Aim 1 will inform if/how the topology of functional representations in VTC is determined by the underlying cytoarchictecture and myeloarchitecture, which may have evolved to optimize particular computations. Aim 2 will investigate the fine-scale functional and structural connectivity of high-level visual cortex determining how information is segregated and integrated within and across adjacent specialized cortical networks. Aim 3 will develop the first generative and quantitative model of VTC computations with the ability to predict responses to stimuli varying in shape, position, and size, while also determining if there is a perceptually-relevant hierarchical processing of information across VTC. This research has important clinical applications for identifying abnormalities in the functional neuroanatomy of VTC within individual brains, and thus, is relevant for patient populations with anatomical or functional VTC deficits, and for individuals with atypical perception or recognition. Overall, the research will break new ground in understanding the neural bases of visual recognition in humans by elucidating the interplay between neural implementation, representations, and computations in human VTC.

PUBLIC HEALTH RELEVANCE: Our proposed research is in-line with the mission of the NEI to advance knowledge of how the visual system functions in health and disease. A crucial portion of our research strives to link the neural and functional architecture of visual cortex to different aspects of high-level vision through novel methods aiming to automatically identify fine-grained high-level functional regions from macroanatomical landmarks alone. This is especially critical for clinical applications as doctors often only have access to anatomical, but not functional, brain data. We expect our proposed research to significantly advance the understanding of the underlying neural mechanisms of visual perception, providing an essential base for future research in identifying abnormalities in the functional neuroanatomy of the ventral stream within individual brains, and thus, is relevant for populations with atypical face and body processing, such as developmental prosopagnosia, Williams Syndrome, autism, as well as visual body agnosia and autotopagnosia.