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Testing pseudo-linear models of responses to natural scenes in primate retina

Alexander Heitman, Nora Brackbill, Martin Greschner, Alexander Sher, Alan M. Litke, E.J. Chichilnisky
doi: https://doi.org/10.1101/045336
Alexander Heitman
1Neurosciences Graduate Program, University of California, San Diego
2Systems Neurobiology Laboratories, The Salk Institute for Biological Studies
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Nora Brackbill
3Department of Physics, Stanford University
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Martin Greschner
2Systems Neurobiology Laboratories, The Salk Institute for Biological Studies
4Department of Neuroscience, University of Oldenburg, Germany
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Alexander Sher
5Santa Cruz Institute for Particle Physics, University of California, Santa Cruz
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Alan M. Litke
5Santa Cruz Institute for Particle Physics, University of California, Santa Cruz
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E.J. Chichilnisky
2Systems Neurobiology Laboratories, The Salk Institute for Biological Studies
6Department of Neurosurgery and Hansen Experimental Physics Laboratory, Stanford University
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Abstract

A central goal of systems neuroscience is to develop accurate quantitative models of how neural circuits process information. Prevalent models of light response in retinal ganglion cells (RGCs) usually begin with linear filtering over space and time, which reduces the high-dimensional visual stimulus to a simpler and more tractable scalar function of time that in turn determines the model output. Although these pseudo-linear models can accurately replicate RGC responses to stochastic stimuli, it is unclear whether the strong linearity assumption captures the function of the retina in the natural environment. This paper tests how accurately one pseudo-linear model, the generalized linear model (GLM), explains the responses of primate RGCs to naturalistic visual stimuli. Light responses from macaque RGCs were obtained using large-scale multi-electrode recordings, and two major cell types, ON and OFF parasol, were examined. Visual stimuli consisted of images of natural environments with simulated saccadic and fixational eye movements. The GLM accurately reproduced RGC responses to white noise stimuli, as observed previously, but did not generalize to predict RGC responses to naturalistic stimuli. It also failed to capture RGC responses when fitted and tested with naturalistic stimuli alone. Fitted scalar nonlinearities before and after the linear filtering stage were insufficient to correct the failures. These findings suggest that retinal signaling under natural conditions cannot be captured by models that begin with linear filtering, and emphasize the importance of additional spatial nonlinearities, gain control, and/or peripheral effects in the first stage of visual processing.

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Posted December 07, 2016.
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Testing pseudo-linear models of responses to natural scenes in primate retina
Alexander Heitman, Nora Brackbill, Martin Greschner, Alexander Sher, Alan M. Litke, E.J. Chichilnisky
bioRxiv 045336; doi: https://doi.org/10.1101/045336
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Testing pseudo-linear models of responses to natural scenes in primate retina
Alexander Heitman, Nora Brackbill, Martin Greschner, Alexander Sher, Alan M. Litke, E.J. Chichilnisky
bioRxiv 045336; doi: https://doi.org/10.1101/045336

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