IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v638y2024ics0378437124001468.html
   My bibliography  Save this article

“All-or-none” dynamics and local-range dominated interaction leading to criticality in neural systems

Author

Listed:
  • Yang, JinHao
  • Ding, Yiming
  • Di, Zengru
  • Wang, DaHui

Abstract

Since the first observation of criticality in neural systems, many researchers have thought that the nervous system can operate in a critical state, and an increasing number of models equipped with different mechanisms have been proposed. We believe that there are simple mechanisms underlying the criticality in neural systems. We constructed a neural network model to investigate the mechanism underlying criticality in neural systems. We found that a neural system consisting of neurons with all-or-none dynamics and local-range dominated interaction exhibits critical behavior when properly driven. The all-or-none dynamics of single neuron and local-range dominated interaction are the identical mechanisms of criticality in the BTW sandpile model, so we concluded that whatever mechanism causes the neural system to evolve to the state where short-range dominated interaction and appropriate input is received, critical behavior can be observed.

Suggested Citation

  • Yang, JinHao & Ding, Yiming & Di, Zengru & Wang, DaHui, 2024. "“All-or-none” dynamics and local-range dominated interaction leading to criticality in neural systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 638(C).
  • Handle: RePEc:eee:phsmap:v:638:y:2024:i:c:s0378437124001468
    DOI: 10.1016/j.physa.2024.129638
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437124001468
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2024.129638?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:phsmap:v:638:y:2024:i:c:s0378437124001468. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.