• DocumentCode
    2500462
  • Title

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

  • Author

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

  • Author_Institution
    Inst. of Sci. & Technol., Kanto Gakuin Univ., Yokohama, Japan
  • fYear
    2011
  • fDate
    Aug. 30 2011-Sept. 3 2011
  • Firstpage
    7328
  • Lastpage
    7331
  • 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.
  • Keywords
    neural nets; neurophysiology; stochastic processes; computer simulation; information transmission; mutual information; neural spike trains; neuron model; stochastic resonance; subthreshold stimuli; suprathreshold stimuli; Computational modeling; Computer simulation; Educational institutions; Neurons; Noise; Stochastic resonance; Strontium; Action Potential; Fluctuations; Hodgkin-Huxley Model; Homogeneous Poisson Process; Monte Carlo Simulation; Mutual Information; Neural Spike Trains; Numerical Method; Action Potentials; Algorithms; Computer Simulation; Humans; Membrane Potentials; Models, Neurological; Monte Carlo Method; Neurons; Poisson Distribution; Reproducibility of Results; Signal Processing, Computer-Assisted; Signal-To-Noise Ratio; Stochastic Processes; Synaptic Transmission; Time Factors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE
  • Conference_Location
    Boston, MA
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-4121-1
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2011.6091709
  • Filename
    6091709