IDEAS home Printed from https://ideas.repec.org/a/hin/complx/8459009.html
   My bibliography  Save this article

Effect of Electrical and Chemical Autapse on the Firing Pattern and Synchronization of the Rulkov Neuron Model

Author

Listed:
  • Sriram Parthasarathy
  • Fatemeh Parastesh
  • Hayder Natiq
  • Karthikeyan Rajagopal
  • Sajad Jafari
  • Fakhteh Ghanbarnejad

Abstract

The Rulkov map model is an efficient model for reproducing different dynamics of the neurons. In specific neurons, the electrical activity is regulated by time-delayed self-feedback called autapse. This paper investigates how the dynamics of the Rulkov model change by considering the autaptic current. Both electrical and chemical autapses are considered, and bifurcation diagrams are plotted for different autapse gains and time delays. Consequently, various firing patterns of the model are illustrated. The results represent that the firing pattern is greatly dependent on the values of autapse parameters. Moreover, the average firing frequency is computed and it is shown that the enhanced firing activity is induced by the inhibitory autapse. The synchronous dynamics of coupled Rulkov maps in the presence of autapse is also studied. It is shown that the electrical autapse enhances synchronization in small time delays, while the enhancement is achieved by chemical autapse in any time delay. However, increasing the time delay reduces the synchronization region.

Suggested Citation

  • Sriram Parthasarathy & Fatemeh Parastesh & Hayder Natiq & Karthikeyan Rajagopal & Sajad Jafari & Fakhteh Ghanbarnejad, 2023. "Effect of Electrical and Chemical Autapse on the Firing Pattern and Synchronization of the Rulkov Neuron Model," Complexity, Hindawi, vol. 2023, pages 1-15, July.
    • Handle: RePEc:hin:complx:8459009
    DOI: 10.1155/2023/8459009
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/complexity/2023/8459009.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/complexity/2023/8459009.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2023/8459009?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
    ---><---

    More about this item

    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:hin:complx:8459009. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    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.