IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v552y2020ics0378437119317923.html
   My bibliography  Save this article

Channel noise effects on neural synchronization

Author

Listed:
  • Maisel, Brenton
  • Lindenberg, Katja

Abstract

Synchronization in neural networks is believed to be linked to cognitive processes, while abnormal synchronization has been associated with disorders such as epilepsy and schizophrenia. We examine the synchronization of small Hodgkin–Huxley neuronal networks. The principal features of Hodgkin–Huxley neurons are protein channels in the neural membrane that transition between open and closed states with voltage dependent rate constants. The standard assumption of infinitely many channels neglects the fact that real neurons have finitely many channels, which leads to fluctuations in the membrane voltage and modifies neuronal spike times. These fluctuations are referred to as channel noise. We demonstrate that regardless of channel noise magnitude, neurons in the network reach a steady state synchronization level dependent only on the number of neurons in the network, equivalent to the steady state level of uncoupled Poisson neurons. The channel noise only affects the time to reach the steady state synchronization level.

Suggested Citation

  • Maisel, Brenton & Lindenberg, Katja, 2020. "Channel noise effects on neural synchronization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 552(C).
  • Handle: RePEc:eee:phsmap:v:552:y:2020:i:c:s0378437119317923
    DOI: 10.1016/j.physa.2019.123186
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119317923
    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.2019.123186?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:552:y:2020:i:c:s0378437119317923. 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.