IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v185y2024ics0960077924006659.html
   My bibliography  Save this article

Emergence of pathological beta oscillation and its uncertainty quantification in a time-delayed feedback Parkinsonian model

Author

Listed:
  • Chen, Yaqian
  • Nakao, Hiroya
  • Kang, Yanmei

Abstract

It has been experimentally found that transmission delays play an important role in the emergence of excessively synchronized beta oscillations (13–30 Hz) related to the onset of Parkinson’s symptoms. In order to clarify the dynamical mechanism underlying beta oscillations, we generalize a conventional resonance model based on the subthalamic nucleus (STN)-external segment of globus pallidus (GPe)-cortex circuit to a feedback Parkinsonian model by incorporating the transmission delay within the basal ganglia (STN-GPe circuit) and the transmission delay from the STN to the cortex. By combining the theory of center manifolds and normal forms with numerical simulations, it is revealed how the pathological beta oscillations occur as the transmission delays increase beyond critical values. Furthermore, by regarding the transmission delays and the connection weights as random variables, variance-based sensitivity analysis is performed based on polynomial chaos expansion. It is identified that the transmission delays and connection strength in the long STN-cortex circuit are more significant than those in the STN-GPe circuit for beta oscillations. Our results also suggest that the severity of the Parkinsonian symptoms could be alleviated if a clinical therapy, such as deep brain stimulation, can enlarge the transmission delays in the STN-GPe and STN-cortex circuits simultaneously.

Suggested Citation

  • Chen, Yaqian & Nakao, Hiroya & Kang, Yanmei, 2024. "Emergence of pathological beta oscillation and its uncertainty quantification in a time-delayed feedback Parkinsonian model," Chaos, Solitons & Fractals, Elsevier, vol. 185(C).
  • Handle: RePEc:eee:chsofr:v:185:y:2024:i:c:s0960077924006659
    DOI: 10.1016/j.chaos.2024.115113
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077924006659
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.chaos.2024.115113?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:185:y:2024:i:c:s0960077924006659. 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.