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

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Stochastic resonance (SR) has been shown to improve detection of sub-threshold signals with additive uncorrelated 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
Title of host publicationProceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publicationEngineering the Future of Biomedicine, EMBC 2009
PublisherIEEE Computer Society
Pages6806-6809
Number of pages4
ISBN (Print)9781424432967
DOIs
Publication statusPublished - 2009 Jan 1
Event31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 - Minneapolis, MN, United States
Duration: 2009 Sep 22009 Sep 6

Publication series

NameProceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009

Conference

Conference31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009
CountryUnited States
CityMinneapolis, MN
Period09/9/209/9/6

Keywords

  • Action potential
  • Hodgkin-Huxley model
  • Homogeneous poisson process
  • Information-theoretic analysis
  • Monte Carlo simulation
  • Numerical method
  • Supra-threshold stochastic resonance
  • Synaptic noise

ASJC Scopus subject areas

  • Biomedical Engineering
  • Medicine(all)
  • Cell Biology
  • Developmental Biology

Fingerprint Dive into the research topics of 'Stochastic resonance can enhance information transmission of supra-threshold neural signals'. Together they form a unique fingerprint.

  • Cite this

    Kawaguchi, M., Mino, H., Momose, K., & Durand, D. M. (2009). Stochastic resonance can enhance information transmission of supra-threshold neural signals. In Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 (pp. 6806-6809). [5333973] (Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009). IEEE Computer Society. https://doi.org/10.1109/IEMBS.2009.5333973