Neural circuits for visual feature detection

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 DESCRIPTION (provided by applicant): A significant percentage of people in the US suffer from disabilities resulting from traumatic injury, stroke, or degenerative disease which result in deficits in visual perception. Therefore, an understanding of the basic circuit neurobiology and neuromodulation of feature-based visual perception will sharpen our understanding of the mechanism of visual processing, and should facilitate the development of treatments for these disabilities. One form of visual attention is targeted to salient features of the visual scene, durng which a subject detects spatio-temporal disparities that distinguish a feature from a cluttered visual surround. The cell-circuit mechanism for how this occurs is not well understood. This project will capitalize on the significant experimental advantages of the fruit fly Drosophila to explore the neural circuits that produce an elementary analogue of feature-based visual attention. The fly has a numerically simple nervous system, with which highly advanced genetic techniques can be used to identify, manipulate, and repeatedly record the activity of individual neurons, as well as their upstream and downstream network partners. The fly also displays robust feature-based visual perception, even under stimulus conditions that defeat classical models of motion vision, for which similar processes have been localized to cortical pathways in humans and non-human primates. The PI hypothesizes that flies detect and process these higher-order features with specialized circuits that integrate first-order elementary motion signals with parallel higher-order spatiotemporal disparities, each of which are sculpted by the action of inhibitory neurotransmitters. The PI will perform two-photon Ca2+ imaging of candidate cellular pathways in response to stimuli the PI has discovered to elicit robust higher-order feature detection by flies within a virtual reality flight simulator. Armed with physiological receptive fields, the PI will examine how feature perception observed during active flight behavior is perturbed by optogenetically silencing these circuits and testing the effects using a systems identification technique that extracts input-output functions of first-order and higher-order feature vision from an intact behaving fly. Finally, the PI will study how specific inhibitor neurotransmitters such as GABA and glutamate sculpt the physiology of feature coding neurons and feature attention behavior.