This paper studies possible bifurcations and synchronization of subpopulations of a class of macroscopic models called neural mass models. These models describe the mean activity of entire neural populations, represented by their averaged firing rates and membrane potentials. Connections between the nodes represent the static nonlinear sigmoidal function. We study local bifurcations and make a global stability analysis for one subpopulation of the neural mass model. Also we consider the behavior of two coupled subpopulations and find the sufficient conditions of their synchronization. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

Original languageEnglish
Pages (from-to)14741-14745
Number of pages5
JournalIFAC-PapersOnLine
Volume50
Issue number1
DOIs
StatePublished - 2017
Event20th World Congress of the International-Federation-of-Automatic-Control (IFAC) - Toulouse, France
Duration: 9 Jul 201714 Jul 2017

    Scopus subject areas

  • Mathematics(all)
  • Neuroscience(all)

    Research areas

  • Neural dynamics, Nonlinear systems, Pitchfork bifurcation, Synchronization, Lyapunov function, DYNAMICS, NETWORKS, RESPONSES, SYSTEMS, DISEASE, BRAIN, EEG

ID: 37787133