Point singularities and suprathreshold stochastic resonance in optimal coding

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dc.creatorMcDonnell, Mark D.
dc.creatorStocks, Nigel G.
dc.creatorPearce, Charles E. M.
dc.creatorAbbott, Derek
dc.date2004-09-21
dc.date.accessioned2026-07-07T08:13:11Z
dc.date.available2026-07-07T08:13:11Z
dc.descriptionMotivated by recent studies of population coding in theoretical neuroscience, we examine the optimality of a recently described form of stochastic resonance known as suprathreshold stochastic resonance, which occurs in populations of noisy threshold devices such as models of sensory neurons. Using the mutual information measure, it is shown numerically that for a random input signal, the optimal threshold distribution contains singularities. For large enough noise, this distribution consists of a single point and hence the optimal encoding is realized by the suprathreshold stochastic resonance effect. Furthermore, it is shown that a bifurcational pattern appears in the optimal threshold settings as the noise intensity increases. Fisher information is used to examine the behavior of the optimal threshold distribution as the population size approaches infinity.
dc.description11 pages, 3 figures, RevTeX
dc.identifierhttps://arxiv.org/abs/cond-mat/0409528
dc.identifierhttp://arxiv.org/abs/cond-mat/0409528
dc.identifierPhysics Letters A, 352 (3), pp 183-189, 2006
dc.identifierdoi:10.1016/j.physleta.2005.11.068
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/132711
dc.subjectStatistical Mechanics
dc.subjectNeurons and Cognition
dc.titlePoint singularities and suprathreshold stochastic resonance in optimal coding
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