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Optimal stimulus and noise distributions for information transmission via suprathreshold stochastic resonance

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McDonnell, Mark D., Stocks, Nigel G. and Abbott, Derek (2007) Optimal stimulus and noise distributions for information transmission via suprathreshold stochastic resonance. Physical Review E, Vol.75 (No.6). Article: 061105. doi:10.1103/PhysRevE.75.061105

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Official URL: http://dx.doi.org/10.1103/PhysRevE.75.061105

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Abstract

Suprathreshold stochastic resonance (SSR) is a form of noise-enhanced signal transmission that occurs in a parallel array of independently noisy identical threshold nonlinearities, including model neurons. Unlike most forms of stochastic resonance, the output response to suprathreshold random input signals of arbitrary magnitude is improved by the presence of even small amounts of noise. In this paper, the information transmission performance of SSR in the limit of a large array size is considered. Using a relationship between Shannon's mutual information and Fisher information, a sufficient condition for optimality, i.e., channel capacity, is derived. It is shown that capacity is achieved when the signal distribution is Jeffrey's prior, as formed from the noise distribution, or when the noise distribution depends on the signal distribution via a cosine relationship. These results provide theoretical verification and justification for previous work in both computational neuroscience and electronics.

Item Type: Journal Article
Subjects: Q Science > QC Physics
Divisions: Faculty of Science > Engineering
Journal or Publication Title: Physical Review E
Publisher: American Physical Society
ISSN: 1539-3755
Official Date: June 2007
Dates:
DateEvent
June 2007Published
Volume: Vol.75
Number: No.6
Number of Pages: 13
Page Range: Article: 061105
DOI: 10.1103/PhysRevE.75.061105
Status: Peer Reviewed
Publication Status: Published

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