Stochastic resonance can enhance information transmission of supra-threshold neural signals.

Minato Kawaguchi, Hiroyuki Mino, Keiko Momose, Dominique M. Durand

Research output: Contribution to journalArticle

Abstract

Stochastic resonance (SR) has been shown to improve detection of sub-threshold signals with additive uncor-related background noise, not only in a single hippocampal CA1 neuron model, but in a population of hippocampal CA1 neuron models (Array-Enhanced Stochastic Resonance; AESR). However, most of the information in the CNS is transmitted through supra-threshold signals and the effect of stochastic resonance in neurons on these signals is unknown. Therefore, we investigate through computer simulations whether information transmission of supra-threshold input signal can be improved by uncorrelated noise in a population of hippocampal CA1 neuron models by supra-threshold stochastic resonance (SSR). The mutual information was estimated as an index of information transmission via total and noise entropies from the inter-spike interval (ISI) histograms of the spike trains generated by gathering each of spike trains in a population of hippocampal CA1 neuron models at N = 1, 2, 4, 10, 20 and 50. It was shown that the mutual information was maximized at a specific amplitude of uncorrelated noise, i.e., a typical curve of SR was observed when the number of neurons was greater than 10 with SSR. However, SSR did not affect the information transfer with a small number of neurons. In conclusion, SSR may play an important role in processing information such as memory formation in a population of hippocampal neurons.

Original languageEnglish
Pages (from-to)6806-6809
Number of pages4
JournalConference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
Publication statusPublished - 2009
Externally publishedYes

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

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