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Chimeras in leaky integrate-and-fire neural networks: effects of reflecting connectivities

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  • Nefeli Dimitra Tsigkri-DeSmedt

    (Institute of Nanoscience and Nanotechnology
    Section of Solid State Physics, Department of Physics, National and Kapodistrian University of Athens)

  • Johanne Hizanidis

    (Institute of Nanoscience and Nanotechnology
    Crete Center for Quantum Complexity and Nanotechnology, Department of Physics, University of Crete)

  • Eckehard Schöll

    (Institut für Theoretische Physik, Technische Universität Berlin)

  • Philipp Hövel

    (Institut für Theoretische Physik, Technische Universität Berlin
    Bernstein Center for Computational Neuroscience Berlin, Humboldt-Universität zu Berlin)

  • Astero Provata

    (Institute of Nanoscience and Nanotechnology)

Abstract

The effects of attracting-nonlocal and reflecting connectivity are investigated in coupled Leaky Integrate-and-Fire (LIF) elements, which model the exchange of electrical signals between neurons. Earlier investigations have demonstrated that repulsive-nonlocal and hierarchical network connectivity can induce complex synchronization patterns and chimera states in systems of coupled oscillators. In the LIF system we show that if the elements are nonlocally linked with positive diffusive coupling on a ring network, the system splits into a number of alternating domains. Half of these domains contain elements whose potential stays near the threshold and they are interrupted by active domains where the elements perform regular LIF oscillations. The active domains travel along the ring with constant velocity, depending on the system parameters. When we introduce reflecting coupling in LIF networks unexpected complex spatio-temporal structures arise. For relatively extensive ranges of parameter values, the system splits into two coexisting domains: one where all elements stay near the threshold and one where incoherent states develop, characterized by multi-leveled mean phase velocity profiles.

Suggested Citation

  • Nefeli Dimitra Tsigkri-DeSmedt & Johanne Hizanidis & Eckehard Schöll & Philipp Hövel & Astero Provata, 2017. "Chimeras in leaky integrate-and-fire neural networks: effects of reflecting connectivities," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 90(7), pages 1-11, July.
    • Handle: RePEc:spr:eurphb:v:90:y:2017:i:7:d:10.1140_epjb_e2017-80162-0
    DOI: 10.1140/epjb/e2017-80162-0
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    Cited by:

    1. Andreev, Andrey V. & Ivanchenko, Mikhail V. & Pisarchik, Alexander N. & Hramov, Alexander E., 2020. "Stimulus classification using chimera-like states in a spiking neural network," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    2. Alexandros Rontogiannis & Astero Provata, 2021. "Chimera states in FitzHugh–Nagumo networks with reflecting connectivity," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 94(5), pages 1-12, May.
    3. Sebastian Jenderny & Karlheinz Ochs & Philipp Hövel, 2023. "A memristor-based circuit approximation of the Hindmarsh–Rose model," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 96(8), pages 1-10, August.

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    Keywords

    Statistical and Nonlinear Physics;

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