IDEAS home Printed from https://ideas.repec.org/a/spr/eurphb/v87y2014i9p1-610.1140-epjb-e2014-50437-1.html
   My bibliography  Save this article

Noise-induced synchronization transitions in neuronal network with delayed electrical or chemical coupling

Author

Listed:
  • Yanan Wu
  • Yubing Gong
  • Qi Wang

Abstract

In this paper, we numerically study synaptic noise-induced synchronization transitions in scale-free network of thermo-sensitive neurons with delayed electrical or chemical coupling. It is found that the neurons exhibit synchronization transitions as synaptic noise strength is varied, and the synchronization transitions are enhanced when time delay is proper. For electrical coupling, noise can induce weak synchronization transitions, and the synchronization transitions decrease as network average degree increases; while, for chemical coupling, noise can induce strong synchronization transitions, and the synchronization transitions become strongest when network average degree is optimal. Different mechanisms of linear electrical and nonlinear chemical coupling could be the reason for these differences. These results show that synaptic noise can induce different synchronization transitions in the scale-free neuronal network with electrical or chemical coupling, and hence could play different roles in the information transmission of neural systems. Copyright EDP Sciences, SIF, Springer-Verlag Berlin Heidelberg 2014

Suggested Citation

  • Yanan Wu & Yubing Gong & Qi Wang, 2014. "Noise-induced synchronization transitions in neuronal network with delayed electrical or chemical coupling," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 87(9), pages 1-6, September.
  • Handle: RePEc:spr:eurphb:v:87:y:2014:i:9:p:1-6:10.1140/epjb/e2014-50437-1
    DOI: 10.1140/epjb/e2014-50437-1
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1140/epjb/e2014-50437-1
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1140/epjb/e2014-50437-1?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wang, Baoying & Gong, Yubing & Xie, Huijuan & Wang, Qi, 2016. "Optimal autaptic and synaptic delays enhanced synchronization transitions induced by each other in Newman–Watts neuronal networks," Chaos, Solitons & Fractals, Elsevier, vol. 91(C), pages 372-378.
    2. Xie, Huijuan & Gong, Yubing, 2017. "Multiple coherence resonances and synchronization transitions by time delay in adaptive scale-free neuronal networks with spike-timing-dependent plasticity," Chaos, Solitons & Fractals, Elsevier, vol. 94(C), pages 80-85.
    3. Xie, Huijuan & Gong, Yubing & Wang, Baoying, 2018. "Spike-timing-dependent plasticity optimized coherence resonance and synchronization transitions by autaptic delay in adaptive scale-free neuronal networks," Chaos, Solitons & Fractals, Elsevier, vol. 108(C), pages 1-7.

    More about this item

    Keywords

    Statistical and Nonlinear Physics;

    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:spr:eurphb:v:87:y:2014:i:9:p:1-6:10.1140/epjb/e2014-50437-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.