The influence of autapse on synchronous firing in small-world neural networks

Lu Peng, Jun Tang, Jun Ma and Jinming Luo

Physica A: Statistical Mechanics and its Applications, 2022, vol. 594, issue C

Abstract: The synchronization of the nervous system is strongly related to diseases such as Parkinson’s, epilepsy, and schizophrenia. Given that the existence of autapse has been proved experimentally, the influence of autapse on the synchronization in a neural network is studied numerically. The results show that increasing coupling intensity could destroy the synchronization of the neural firing pattern, and reduce the firing rate in the network. Especially, an inhibition zone, in which the neural firing is inhibited completely, exists for changes of both coupling intensity and time delay in all types of autapses. As a key factor for different types of autapses, the transmission time delay influences the synchronization complicatedly, i.e., increasing time delay could modulate synchronization for different types of autapse and parameter regions. The theoretical results in this paper shed some light on the study about the mechanism of neural synchronization.

Keywords: Autapse; Small-world neural network; Synchronization (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:594:y:2022:i:c:s0378437122000607

DOI: 10.1016/j.physa.2022.126956

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