Retinal Ganglion Cell Type Characterization Through Closed-Loop Adaptation of Light Stimulation Patterns

The goal of this project is to develop a method for high-throughput screening of retinal ganglion cells (RGCs) by means of detecting and categorizing their extracellular action potentials recorded with high-density microelectrode arrays (HD-MEA).

For this project, we will develop new types of light stimuli that activate RGC types differentially using closed-loop adaptation during experiment, in order to maximize the response difference between the various cell types. With an optimal set of light stimuli, we should then be able to categorize and cluster the RGC according to cell type.

It is yet to be determined whether the measurement of electrical activity in response to specific light stimuli alone is enough to identify a larger number of RCG types, as well as to make predictions about each cell type’s role in the transmission of visual information to the brain. Therefore, in a later step, we will use genetic and pharmacological methods in order to establish a ground truth with which the clustering method can be optimized and corroborated.

Keywords: Neuroscience, vision, retina, retinal ganglion cells, electrophysiology, microelectrode array, light stimulation, spike-sorting