Suprathreshold Stochastic Resonance in a Neuronal Network Model: a Possible Strategy for Sensory Coding

  • Nigel G. Stocks
  • Riccardo Mannella
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 45)


The possible mechanism to explain the dynamics of the transduction in sensory neurons is investigated. We consider a parallel array of noisy FitzHugh-Nagumo model neurons, subject to a common input signal. The information transmission of the signal through the array is studied as a function of the internal noise intensity. The threshold of each neuron is set suprathreshold with respect to the input signal. A form of stochastic resonance, termed suprathreshold stochastic resonance (SSR), which has recently been observed in a network of threshold devices [8] is also found to occur in the FHN array. It is demonstrated that significant information gain, over and above that attainable in a single FHN element, can be achieved via the SSR effect. These information gains are still achievable under the assumption that the thresholds are fully adjustable.


Power Spectral Density Noise Intensity Stochastic Resonance Average Mutual Information Internal Noise 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Nigel G. Stocks
    • 1
  • Riccardo Mannella
    • 2
  1. 1.School of EngineeringUniversity of WarwickCoventryEngland
  2. 2.Dipartimento di FisicaUniversità di Pisa and INFM UdR PisaPisaItaly

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