Stochastic resonance with a mixture of sub-and supra-threshold stimuli in a population of neuron models

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

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

    Abstract

    This paper presents a novel type of stochastic resonance (SR) with a mixture of sub- and supra-threshold stimuli in a population of neuron models beyond regular SR and Supra-threshold SR (SSR) phenomena. We investigate through computer simulations if the novel type of SR can be observed or not, using the mutual information (MI) estimated from a population of neural spike trains as an index of information transmission. Computer simulations showed that the MI had a typical type of SR curves, even when the balance between sub-and supra-threshold stimuli was varied, suggesting the novel type of SR. Moreover, the peak of MI increased as the balance of supra-threshold stimuli got stronger, i.e., as the situation was getting close to the SSR from the regular SR. This finding could accelerate our understanding about how fluctuations play a role in processing information carried by a mixture of sub-and supra-threshold stimuli.

    Original languageEnglish
    Title of host publicationProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
    Pages7328-7331
    Number of pages4
    DOIs
    Publication statusPublished - 2011
    Event33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 - Boston, MA
    Duration: 2011 Aug 302011 Sep 3

    Other

    Other33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
    CityBoston, MA
    Period11/8/3011/9/3

    Fingerprint

    Computer Simulation
    Neurons
    Automatic Data Processing
    Population
    Computer simulation

    Keywords

    • Action Potential
    • Fluctuations
    • Hodgkin-Huxley Model
    • Homogeneous Poisson Process
    • Monte Carlo Simulation
    • Mutual Information
    • Neural Spike Trains
    • Numerical Method

    ASJC Scopus subject areas

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

    Cite this

    Kawaguchi, M., Mino, H., Momose, K., & Durand, D. M. (2011). Stochastic resonance with a mixture of sub-and supra-threshold stimuli in a population of neuron models. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (pp. 7328-7331). [6091709] https://doi.org/10.1109/IEMBS.2011.6091709

    Stochastic resonance with a mixture of sub-and supra-threshold stimuli in a population of neuron models. / Kawaguchi, Minato; Mino, Hiroyuki; Momose, Keiko; Durand, Dominique M.

    Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. 2011. p. 7328-7331 6091709.

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

    Kawaguchi, M, Mino, H, Momose, K & Durand, DM 2011, Stochastic resonance with a mixture of sub-and supra-threshold stimuli in a population of neuron models. in Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS., 6091709, pp. 7328-7331, 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011, Boston, MA, 11/8/30. https://doi.org/10.1109/IEMBS.2011.6091709
    Kawaguchi M, Mino H, Momose K, Durand DM. Stochastic resonance with a mixture of sub-and supra-threshold stimuli in a population of neuron models. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. 2011. p. 7328-7331. 6091709 https://doi.org/10.1109/IEMBS.2011.6091709
    Kawaguchi, Minato ; Mino, Hiroyuki ; Momose, Keiko ; Durand, Dominique M. / Stochastic resonance with a mixture of sub-and supra-threshold stimuli in a population of neuron models. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. 2011. pp. 7328-7331
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