Journal of the Korean Physical Society

Korean Physical Society (한국물리학회)
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Study of Collective Synchronous Dynamics in a Neural Network Model

  • Cho, Myoung Won (Department of Global Medical Science, Sungshin Women's University)
  • Received : 2018.04.25
  • Accepted : 2018.06.05
  • Published : 2018.11.15
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Abstract

A network with coupled biological neurons provides various forms of collective synchronous dynamics. Such phase-locking dynamics states resemble eigenvectors in a linear coupling system in that the forms are determined by the symmetry of the coupling strengths. However, the states behave as attractors in a nonlinear dynamics system. We here study the collective synchronous dynamics in a neural system by using a novel theory. We exhibit how the period and the stability of individual phase-locking dynamics states are determined by the characteristics of synaptic couplings. We find that, contrary to common sense, the firing rate of a synchronized state decreases with increasing synaptic coupling strength.

Keywords

Acknowledgement

Supported by : Sungshin Women's University

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