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Abstract:
Right at the first synapse, the stream of incoming visual information is split into multiple parallel channels, represented in the retina by different kinds of photo¬receptors (PRs), bipolar cells (BCs) and ganglion cells (RGCs). Complex circuits and, in particular, synaptic interactions in the retina’s two synaptic layers tune these channels to distinct sets of visual features. Cracking the “retinal code”, that is understanding how the visual scenery is encoded by the outputs of the ~20 RGC types, is a major aim of vision research. Here, we study the signal at different processing stages of the retinal signal channels by recording from the majority of cells in the vertical cone photoreceptor pathway, including PR, BC[1] and RGC types[2]. We use 2P imaging in the mouse retina to measure Ca2+ activity evoked by a comprehensive set of stimuli, including frequency/contrast modulated full-field and white noise stimuli. So far our database contains recordings of ~100 BCs and >7,000 RGCs. In addition, we started with electrical single-cell RGC measurements, which provide us with ground truth data about spiking activity underlying Ca2+ signals and anatomical descriptions that can be compared with published RGC catalogues. We have implemented a probabilistic framework for clustering RGCs into functional types based on their responses to different visual stimuli. Clustering is refined and verified by employing reference data (e.g. soma size/shape and retinal tiling). A similar approach allowed us to cluster BC responses into 8 morpho-functional clusters[1]. For RGCs (and displaced amacrine cells), ~25-29 functional clusters can be distinguished, some of which were already verified using our single cell data (e.g. alpha RGCs). Our results suggest that this dataset allows us to study the computations performed along the retina’s vertical pathway and to obtain a complete sample of the information the mouse eye sends to the mouse brain.