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Investigating bifurcation points of neural networks: application to the epileptic seizure

Author

Listed:
  • Zahra Faghani

    (Bernstein Center for Computational Neuroscience Berlin, Philippstr. 13, Haus 6)

  • Sajad Jafari

    (Biomedical Engineering Department, Amirkabir University of Technology
    Health Technology Research Institute, Amirkabir University of Technology, No. 350, Hafez Ave, Valiasr Square)

  • Chao-Yang Chen

    (School of Information and Electrical Engineering, Hunan University of Science and Technology
    Center for Polymer Studies and Department of Physics, Boston University)

  • Fahimeh Nazarimehr

    (Biomedical Engineering Department, Amirkabir University of Technology)

Abstract

In this paper, we investigate epileptic seizures with the help of bifurcations in the network of neurons. The bifurcations of these neurons are investigated in one-layer and multi-layer network with different coupling strength. Bifurcations of networks are studied in various aspects. Also, dynamical properties of different networks and the single neuron out of network are compared. Some measures are reviewed to predict the bifurcation points of a network. These measures are justified by the bifurcations’ plots. The main goal of this paper is investigating the bifurcations in networks of neurons and studying their dynamical properties. Also, the results are discussed from the viewpoint of physiological facts. Graphical abstract

Suggested Citation

  • Zahra Faghani & Sajad Jafari & Chao-Yang Chen & Fahimeh Nazarimehr, 2020. "Investigating bifurcation points of neural networks: application to the epileptic seizure," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 93(12), pages 1-18, December.
  • Handle: RePEc:spr:eurphb:v:93:y:2020:i:12:d:10.1140_epjb_e2020-10477-6
    DOI: 10.1140/epjb/e2020-10477-6
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    Cited by:

    1. Yu, Haiyan & Liu, Quansheng & Bi, Yuanhong, 2023. "Lévy noise-induced phase transition in p53 gene regulatory network near bifurcation points," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).

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    Keywords

    Statistical and Nonlinear Physics;

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