There is a fundamental gap in our understanding of how cortical circuit operations aid in high-level visual information-processing like face recognition. The existence of this conceptual gap constitutes an important problem because, until it is filled, it will neither be possible to explain face recognition and the computations face- selective networks implement, nor understand the reasons for face-recognition impairments in disorders like developmental prosopagnosia (face blindness). The long-term goal is to understand the neural mechanisms of face recognition and build an artificial face-recognition system implementing neural computations and thus explain face recognition mechanistically. The overall objective of this proposal presents a major step towards this goal: the establishment of a new approach and a new model system that permits imaging of large neural populations with single-cell resolution and cell-type differentiation within face-selective areas and surrounding regions. These technological advances are expected to lead to the understanding of the functional organization of face areas and how it impacts population codes for faces. The central hypotheses that will be tested, are that face areas are composed of multiple columns with different functional specializations, and that facial codes are highly cell type specific. The rationale for this proposal is that, after completion of the proposed research, the central gap in the understanding of how cortical circuit operations enable high-level vision will have been narrowed through the establishment of a new model system with unprecedented power to uncover the functional organization and circuit mechanisms of population codes of object recognition. The hypothesis will be tested by pursuing two specific aims: 1) Uncover the Spatial Organization of Face-Specializations of the Marmoset Brain; and 2) Determine the Cell-Type Specificity of Face Representations in Face-Selective areas. Two-photon calcium imaging during visual stimulation, combined with tissue clearing and cell type identification through immunohistochemistry will identify the functional organization of face areas and their surroundings with single- cell resolution. The approach is innovative because it presents a new and substantive departure from the status quo and because it addresses an NEI-relevant problem, the neural mechanisms of social perception, in a new way. The proposed research is significant, because it will provide a critical step forward towards a mechanistic understanding of the neural computations performed inside face areas, allow for the development of highly improved artificial face-processing systems, and advance our understanding of the functional organization of face areas in a new dimension and from the level of single cells to the level of face areas. The outcomes will lay the foundation for the determination of the molecular organization of high-level visual circuits and the development of transgenic disease models. The project, therefore, is of direct relevance for the understanding of prosopagnosia, as well as altered social information processing in syndromes like autism spectrum disorders, fragile X, and Williams syndrome.
The proposed research is relevant to public health because the neural mechanisms that underlie face processing are essential to human social life, and altered social perception is characteristic of psychiatric disorders like autism spectrum disorders, face blindness, Fragile X, and Williams syndrome. Studies proposed in this application will examine how specializations within the brain, from different cell types to spatially organized face areas, support the computations of face recognition. Thus the proposed research is relevant to the part of the NIH?s mission that pertains to reducing illness and disability.
