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Stochastic bursting in networks of excitable units with delayed coupling.

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  • Author(s): Zheng C;Zheng C; Pikovsky A; Pikovsky A; Pikovsky A
  • Source:
    Biological cybernetics [Biol Cybern] 2022 Apr; Vol. 116 (2), pp. 121-128. Date of Electronic Publication: 2021 Jun 28.
  • Publication Type:
    Journal Article; Research Support, Non-U.S. Gov't
  • Language:
    English
  • Additional Information
    • Source:
      Publisher: Springer Verlag Country of Publication: Germany NLM ID: 7502533 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1432-0770 (Electronic) Linking ISSN: 03401200 NLM ISO Abbreviation: Biol Cybern Subsets: MEDLINE
    • Publication Information:
      Publication: Berlin : Springer Verlag
      Original Publication: Berlin, New York, Springer-Verlag.
    • Subject Terms:
      Models, Neurological* ; Noise*; Action Potentials ; Probability ; Stochastic Processes
    • Abstract:
      We investigate the phenomenon of stochastic bursting in a noisy excitable unit with multiple weak delay feedbacks, by virtue of a directed tree lattice model. We find statistical properties of the appearing sequence of spikes and expressions for the power spectral density. This simple model is extended to a network of three units with delayed coupling of a star type. We find the power spectral density of each unit and the cross-spectral density between any two units. The basic assumptions behind the analytical approach are the separation of timescales, allowing for a description of the spike train as a point process, and weakness of coupling, allowing for a representation of the action of overlapped spikes via the sum of the one-spike excitation probabilities.
      (© 2021. The Author(s).)
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    • Contributed Indexing:
      Keywords: Excitable system; Noise-induced spikes; Point process; Time-delayed coupling
    • Publication Date:
      Date Created: 20210628 Date Completed: 20220506 Latest Revision: 20220716
    • Publication Date:
      20250114
    • Accession Number:
      PMC9068677
    • Accession Number:
      10.1007/s00422-021-00883-9
    • Accession Number:
      34181074