IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v191y2025ics0960077924014413.html
   My bibliography  Save this article

Dynamic analysis of coupled Hindmarsh-Rose neurons with enhanced FPGA implementation

Author

Listed:
  • Lu, Jiakai
  • Min, Fuhong
  • Gan, Linghu
  • Yang, Songtao

Abstract

As the fundamental unit of the nervous system, neuron is essential for transmitting and processing information, playing a critical role in brain activity regulation. This article develops an electrically coupled Hindmarsh-Rose (HR) neurons incorporating external stimuli to simulate biological neuronal behavior. The bifurcation plot with varying the coupling strength of the system are analyzed through the discrete mapping method, in which period-doubling bifurcations and saddle bifurcation are obtained. The evolutions of period-1 to period-8 and period-3 to period-6 are predicted with stable and unstable periodic orbits, and multiple firing behaviors of such a neuron network are studied using Lyapunov exponent and timing-phase diagram. The real part and magnitudes of eigenvalues with varying the coupling strength for different periodic motions are also plotted to illustrate the bifurcation mechanism of the coupled HR neurons. Moreover, theoretical analysis is validated through FPGA technology, which also accelerates computation and minimizes data storage requirements. Ultimately, a uniform linear segmentation algorithm is utilized to construct bifurcation plots of the coupled HR neuron, and experimental results confirm the model's accuracy.

Suggested Citation

  • Lu, Jiakai & Min, Fuhong & Gan, Linghu & Yang, Songtao, 2025. "Dynamic analysis of coupled Hindmarsh-Rose neurons with enhanced FPGA implementation," Chaos, Solitons & Fractals, Elsevier, vol. 191(C).
  • Handle: RePEc:eee:chsofr:v:191:y:2025:i:c:s0960077924014413
    DOI: 10.1016/j.chaos.2024.115889
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077924014413
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.chaos.2024.115889?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 search for a different version of it.

    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:191:y:2025:i:c:s0960077924014413. 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.