Dynamics and bifurcations in multistable 3-cell neural networks.

Journal: Chaos (Woodbury, N.Y.)
Published Date: Jul 1, 2020

Abstract

We disclose the generality of the intrinsic mechanisms underlying multistability in reciprocally inhibitory 3-cell circuits composed of simplified, low-dimensional models of oscillatory neurons, as opposed to those of a detailed Hodgkin-Huxley type [Wojcik et al., PLoS One 9, e92918 (2014)]. The computational reduction to return maps for the phase-lags between neurons reveals a rich multiplicity of rhythmic patterns in such circuits. We perform a detailed bifurcation analysis to show how such rhythms can emerge, disappear, and gain or lose stability, as the parameters of the individual cells and the synapses are varied.

Authors

  • J Collens
    Neuroscience Institute, Georgia State University, Atlanta, Georgia 30303, USA.
  • K Pusuluri
    Neuroscience Institute, Georgia State University, Atlanta, Georgia 30303, USA.
  • A Kelley
    Neuroscience Institute, Georgia State University, Atlanta, Georgia 30303, USA.
  • D Knapper
    Neuroscience Institute, Georgia State University, Atlanta, Georgia 30303, USA.
  • T Xing
    Department of Mathematics and Statistics, Georgia State University, Atlanta, Georgia 30303, USA.
  • S Basodi
    Department of Computer Science, Georgia State University, Atlanta, Georgia 30303, USA.
  • D Alacam
    Department of Mathematics and Statistics, Georgia State University, Atlanta, Georgia 30303, USA.
  • A L Shilnikov
    Neuroscience Institute, Georgia State University, Atlanta, Georgia 30303, USA.

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