PROJECT SUMMARY
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.