SPIKE TRAIN STATISTICS FROM EMPIRICAL FACTS TO THEORY: THE CASE OF THE RETINA
Author
Cessac, BrunoPalacios Vargas, Adrian Galo
Abstract
This chapter focuses on methods from statistical physics and probability theory allowing the analysis of spike trains in neural networks. Taking as an example the retina we present recent works attempting to understand how retina ganglion cells encode the information transmitted to the visual cortex via the optical nerve, by analyzing their spike train statistics. We compare the maximal entropy models used in the literature of retina spike train ...
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This chapter focuses on methods from statistical physics and probability theory allowing the analysis of spike trains in neural networks. Taking as an example the retina we present recent works attempting to understand how retina ganglion cells encode the information transmitted to the visual cortex via the optical nerve, by analyzing their spike train statistics. We compare the maximal entropy models used in the literature of retina spike train analysis to rigorous results establishing the exact form of spike train statistics in conductance-based Integrate-and-Fire neural networks.
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Book's title
MODELING IN COMPUTATIONAL BIOLOGY AND BIOMEDICINE. A MULTIDISCIPLINARY ENDEAVOR
Publication date of the book
2013Start page
261
End page
302
Country
ALEMANIA