IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v200y2025ip2s0960077925010963.html
   My bibliography  Save this article

Synchronization stability in conductance-based neural networks under electromagnetic modulation

Author

Listed:
  • Ye, Zhiqiu
  • Liu, Lu
  • Liu, Yingqi
  • Zeng, Jiapei
  • Xie, Ying
  • Jia, Ya
  • Yang, Lijian

Abstract

Neuronal synchronization plays a crucial role in maintaining brain function and regulating neural rhythms, and its stability is influenced by both synaptic coupling and external regulatory mechanisms. In particular, how electromagnetic induction modulates synchronization stability remains insufficiently understood, especially in conductance-based neural networks, where varying synaptic conductance introduce more complex synchronization dynamics. In this study, we employ a modified Morris-Lecar (mML) neuron model incorporating a flux-dependent feedback mechanism to construct conductance-based neural networks, and systematically analyze the synergistic effects of electromagnetic induction and synaptic conductance on synchronization stability using the master stability function (MSF). The results show that in excitatory networks, electromagnetic modulation exhibits a monotonic enhancement effect on synchronization stability, with higher conductance requiring stronger electromagnetic gain to maintain stability. In contrast, inhibitory networks exhibit a non-monotonic modulation: electromagnetic feedback suppresses synchronization at low conductance levels, but as conductance increases, it initially promotes and then weakens synchronization stability, reflecting a dynamic mechanism based on the balance of interacting currents. Numerical simulations consistent well with the theoretical predictions of MSF across various representative network topologies. These findings reveal the complex coupling mechanism between electromagnetic feedback and synaptic conductance, providing theoretical insight and modeling foundations for understanding synchronization regulation in complex neuronal systems.

Suggested Citation

  • Ye, Zhiqiu & Liu, Lu & Liu, Yingqi & Zeng, Jiapei & Xie, Ying & Jia, Ya & Yang, Lijian, 2025. "Synchronization stability in conductance-based neural networks under electromagnetic modulation," Chaos, Solitons & Fractals, Elsevier, vol. 200(P2).
  • Handle: RePEc:eee:chsofr:v:200:y:2025:i:p2:s0960077925010963
    DOI: 10.1016/j.chaos.2025.117083
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077925010963
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.chaos.2025.117083?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:200:y:2025:i:p2:s0960077925010963. 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.