Population Coding in the Retina

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DESCRIPTION (provided by applicant): A basic goal in vision research is to understand how the retinal output cells, the ganglion cells, represent the visual world. These cells are made up of many different classes, each with its own sensitivities to visual stimuli, and each producing its own set of signals. How these cells work together to collectively form visual representations has been a long-standing question - one whose answer is needed both for basic science (for understanding fundamentals of visual processing) and for applied science (for developing algorithms to drive visual prosthetics). We recently developed a tool for addressing this and use it for both these purposes. Briefly, the tool is a retinal input/output model. It differs from other models in that it's effective on a broad range of image statistics, including those of white noise, gratings, natural scenes (landscapes, faces, etc.) With the model we can make rapid advances on these goals. Our Specific Aims are the following: Aim 1 is to test hypotheses about the roles of the different ganglion cell classes in representing visual images. For this, we use the model as a screening tool. Because it reproduces ganglion cell responses to a wide array of stimuli, we can use it to explore stimulus space in a fast and systematic way and assess which cell classes, or combinations of classes, represent different stimulus features. Given specific predictions from the model, we can then test them experimentally using electrophysiological and/or behavioral assays, both of which are standard in our lab. Aim 2 focuses on the development of a new retinal prosthetic strategy. With the model we can reliably convert visual input into the code used by the ganglion cells - that is, we can drive a prosthetic system to produce normal retinal output, which produces a system with substantially better visual representation than existing methods. PUBLIC HEALTH RELEVANCE: These studies will provide fundamental information about the strategies the nervous system uses to represent and process information. Since a substantial portion of the work involves mapping the input/output relationship of the retina, this research will also contribute to the development of algorithms for retinal prosthetics.