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通过使用具有异质时滞的反馈耦合来自适应地消除耦合神经元的同步。

Eliminating synchronization of coupled neurons adaptively by using feedback coupling with heterogeneous delays.

机构信息

School of Mathematical Sciences, LMNS and SCMS, Fudan University, Shanghai 200433, China.

出版信息

Chaos. 2021 Feb;31(2):023114. doi: 10.1063/5.0035327.

Abstract

In this paper, we present an adaptive scheme involving heterogeneous delay interactions to suppress synchronization in a large population of oscillators. We analytically investigate the incoherent state stability regions for several specific kinds of distributions for delays. Interestingly, we find that, among the distributions that we discuss, the exponential distribution may offer great convenience to the performance of our adaptive scheme because this distribution renders an unbounded stability region. Moreover, we demonstrate our scheme in the realization of synchronization elimination in some representative, realistic neuronal networks, which makes it possible to deepen the understanding and even refine the existing techniques of deep brain stimulation in the treatment of some synchronization-induced mental disorders.

摘要

在本文中,我们提出了一种涉及异质时滞相互作用的自适应方案,以抑制一大群振荡器中的同步。我们分析研究了几种特定的时滞分布的非相干态稳定区域。有趣的是,我们发现,在所讨论的分布中,指数分布可能为我们的自适应方案的性能提供极大的便利,因为该分布给出了一个无界的稳定区域。此外,我们在一些有代表性的实际神经元网络中实现了同步消除,这使得加深理解甚至改进现有的深部脑刺激技术以治疗某些由同步引起的精神障碍成为可能。

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