IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v208y2026ip3s0960077926004455.html

Periodic and quasi-periodic dynamics of neuronal oscillators based on an inorganic memristive device

Author

Listed:
  • Kipelkin, Ivan M.
  • Gerasimova, Svetlana A.
  • Guseinov, Davud V.
  • Belov, Alexey I.
  • Tyukin, Ivan Y.
  • Mikhaylov, Alexey N.
  • Kazantsev, Victor B.

Abstract

This paper presents a mathematical model and hardware implementation of synaptically coupled neurons, realized by two modified FitzHugh–Nagumo oscillators interconnected via an inorganic memristive device. Our study focuses on the adaptive characteristics of the memristive device as a function of the driving signal parameters, thereby capturing key features of synaptic plasticity observed in biological systems. We provide experimental measurements of the average relative change in memristive resistance, which serves as the effective coupling coefficient in our mathematical model. Furthermore, we identify the optimal duty cycle of the master oscillator and demonstrate its direct impact on both the coupling strength and the oscillation amplitude. Through a combination of computational modeling and experimental validation, we reveal synchronization regimes at the natural frequency, as well as at harmonic and subharmonic frequencies. The corresponding phase-space structures of the coupled system are analyzed in detail, providing insight into the underlying dynamical mechanisms governing memristive synaptic interaction.

Suggested Citation

  • Kipelkin, Ivan M. & Gerasimova, Svetlana A. & Guseinov, Davud V. & Belov, Alexey I. & Tyukin, Ivan Y. & Mikhaylov, Alexey N. & Kazantsev, Victor B., 2026. "Periodic and quasi-periodic dynamics of neuronal oscillators based on an inorganic memristive device," Chaos, Solitons & Fractals, Elsevier, vol. 208(P3).
    • Handle: RePEc:eee:chsofr:v:208:y:2026:i:p3:s0960077926004455
    DOI: 10.1016/j.chaos.2026.118304
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077926004455
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2026.118304?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:chsofr:v:208:y:2026:i:p3:s0960077926004455. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.