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Proceedings Paper

Optimal coding of a random stimulus by a population of parallel neuron models
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Paper Abstract

We examine the question of how a population of independently noisy sensory neurons should be configured to optimize the encoding of a random stimulus into sequences of neural action potentials. For the case where firing rates are the same in all neurons, we consider the problem of optimizing the noise distribution for a known stimulus distribution, and the converse problem of optimizing the stimulus for a given noise distribution. This work is related to suprathreshold stochastic resonance (SSR). It is shown that, for a large number of neurons, the SSR model is equivalent to a single rate-coding neuron with multiplicative output noise.

Paper Details

Date Published: 15 June 2007
PDF: 10 pages
Proc. SPIE 6602, Noise and Fluctuations in Biological, Biophysical, and Biomedical Systems, 66020R (15 June 2007); doi: 10.1117/12.724618
Show Author Affiliations
Mark D. McDonnell, The Univ. of Adelaide (Australia)
Nigel G. Stocks, The Univ. of Warwick (United Kingdom)
Derek Abbott, The Univ. of Adelaide (Australia)

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

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