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Proceedings Paper

A hierarchy of phase transitions in optimal neuronal coding: from binary to M-ary discrete optimal codes
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Paper Abstract

We have investigated how optimal coding for neural systems changes with the time available for decoding. Optimization was in terms of maximizing information transmission. We have estimated the parameters for Poisson neurons that optimize Shannon transinformation with the assumption of rate coding. We observed a hierarchy of phase transitions from binary coding, for small decoding times, toward discrete (M-ary) coding with two, three and more quantization levels for larger decoding times. We postulate that the presence of subpopulations with specific neural characteristics could be a signiture of an optimal population coding scheme and we use the mammalian auditory system as an example.

Paper Details

Date Published: 8 June 2007
PDF: 9 pages
Proc. SPIE 6602, Noise and Fluctuations in Biological, Biophysical, and Biomedical Systems, 66020H (8 June 2007); doi: 10.1117/12.724410
Show Author Affiliations
A. Nikitin, Univ. of Warwick (United Kingdom)
N. G. Stocks, Univ. of Warwick (United Kingdom)
R. P. Morse, Univ. of Aston (United Kingdom)

Published in SPIE Proceedings Vol. 6602:
Noise and Fluctuations in Biological, Biophysical, and Biomedical Systems
Sergey M. Bezrukov, Editor(s)

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