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Proceedings Paper

The application of Gaussian channel theory to the estimation of information transmission rates in neural systems
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Paper Abstract

We consider the application of Gaussian channel theory (GCT) to the problem of estimating the rate of information transmission through a nonlinear channel such as a neural element. We suggest that, contrary to popular belief, GCT can be applied to neural systems even when the dynamics are highly nonlinear. We show that, under suitable conditions, the Gaussianity of the response is not compromised and hence GCT can be usefully applied. Using the GCT approach we develop a new method for estimating information rates in the time domain. Finally, using this new method, we show that a recently introduced form of stochastic resonance, termed suprathreshold stochastic resonance, is also displayed by the information rate.

Paper Details

Date Published: 25 May 2004
PDF: 10 pages
Proc. SPIE 5467, Fluctuations and Noise in Biological, Biophysical, and Biomedical Systems II, (25 May 2004); doi: 10.1117/12.547114
Show Author Affiliations
Alexander Nikitin, Univ. of Warwick (United Kingdom)
Nigel G. Stocks, Univ. of Warwick (United Kingdom)


Published in SPIE Proceedings Vol. 5467:
Fluctuations and Noise in Biological, Biophysical, and Biomedical Systems II
Derek Abbott; Sergey M. Bezrukov; Andras Der; Angel Sanchez, Editor(s)

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