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Dissecting the neural circuits of early visual processing in Drosophila [electronic resource]

Visual inputs are high-dimensional, dynamic, and may consist of significant levels of noise. Nevertheless, visual processing systems in many animals are capable of efficiently extracting information out of these signals to guide behavior. Flies, in particular, use visual information to guide behavior in challenging conditions such as during rapid flight maneuvers. In this dissertation we examine how early visual processing cells in the visual system of the Fruit Fly, Drosophila, achieve this feat. In particular, we focus on cells that provide inputs to motion detecting circuits and assess how these cells balance the goal of facilitating computational specializations with the goal of efficiently capturing all visual information. In these studies, we used two-photon calcium imaging in vivo to monitor the responses of specific cells in the fly visual system to visual stimuli. Using this system, we found that two first order interneurons providing inputs to pathways specialized for the detection of moving bright and dark edges nevertheless similarly encode information about both brightening and darkening. However, an in depth study of the functional properties of one of these interneurons revealed that it responds differently to bright and dark moving objects of different sizes in a manner that could facilitate the downstream specialization. Furthermore, via genetic and pharmacological manipulations it was found that GABAergic circuits providing lateral and feedback inputs to this cell enhance its responses to dark stimuli and thus enable it to relay critical information for the downstream pathway. These circuits were found to give rise to a center-surround antagonistic, anisotropic and spatiotemporally coupled RF structure in this cell. Interestingly, our studies uncovered deep similarities between the function of early visual processing cells in the fly and in vertebrate retinas. This suggests that different systems have converged on a similar set of solutions for addressing the challenge of efficiently using the resources available to the nervous system to process visual signals.