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Neuronal Signal Transduction Aided by Noise at Threshold and at Saturation

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Abstract

A classical model of neuronal signal transmission describing the presence of both a threshold and a saturation in the neuron response is considered. This model is used to analyze the transduction by the neuron of various types of information-carrying input signals in the presence of noise. Improvement by noise of the performance via stochastic resonance is established for transmission in both the threshold and the saturation regimes. Stochastic resonance at saturation is a novel form, expressing that the distortion experienced by large input signals transmitted at saturation, can be reduced by addition of noise.

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Authors and Affiliations

  1. Laboratoire d'Ingénierie des Systèmes Automatisés (LISA), Université d'Angers, 62 avenue Notre Dame du Lac, Angers, 49000, France

    David Rousseau & François Chapeau-blondeau

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  1. David Rousseau
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  2. François Chapeau-blondeau
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Rousseau, D., Chapeau-blondeau, F. Neuronal Signal Transduction Aided by Noise at Threshold and at Saturation. Neural Processing Letters 20, 71–83 (2004). https://doi.org/10.1007/s11063-004-0740-6

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  • DOI: https://doi.org/10.1007/s11063-004-0740-6

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