Robust decoding in a network of retinal ganglion cells sharing common input

Michael Vidne, Yashar Ahmadian, Jonathon Shlens, Jonathan Pillow, Jayant Kulkarni, Alan Litke, Eero Simoncelli, E.J. Chichilnisky, and Liam Paninski

In preparation; presented as talks at COSYNE and SAND meetings

Synchronized firing among retinal ganglion cells (RGCs) has been reported in many studies. Two major candidate mechanisms of synchronized firing are direct coupling between the cells and common input to the cells. Recent experimental work (Khuc-Trong and Rieke, 2008) indicates that electrical coupling between parasol cells is weak, and neighboring parasol cells share significant synaptic input even in the absence of modulated light stimuli. These findings suggest that an accurate model of synchronized firing must include the effects of common input. Here, we develop a new model of synchronized firing that incorporates the effects of common input, and use it to simulate the light responses and synchronized firing of a nearly complete network of 279 simultaneously recorded parasol cells. We use a generalized linear model augmented with a state-space model to infer common input, spatio-temporal light response properties, and post-spike history effects. The model captures the statistical structure of the spike trains as well as the encoding of the visual stimulus. We then proceed to decode the visual stimulus from the spike train given the model parameters. We demonstrate that the common-input model is much less sensitive to spike jitter than a model with direct coupling.
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