Symmetry breaker governs synchrony patterns in neuronal inspired networks.

IF 2.7 2区 数学 Q1 MATHEMATICS, APPLIED
Chaos Pub Date : 2024-11-01 DOI:10.1063/5.0209865
Anil Kumar, Edmilson Roque Dos Santos, Paul J Laurienti, Erik Bollt
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引用次数: 0

Abstract

Experiments in the human brain reveal switching between different activity patterns and functional network organization over time. Recently, multilayer modeling has been employed across multiple neurobiological levels (from spiking networks to brain regions) to unveil novel insights into the emergence and time evolution of synchrony patterns. We consider two layers with the top layer directly coupled to the bottom layer. When isolated, the bottom layer would remain in a specific stable pattern. However, in the presence of the top layer, the network exhibits spatiotemporal switching. The top layer in combination with the inter-layer coupling acts as a symmetry breaker, governing the bottom layer and restricting the number of allowed symmetry-induced patterns. This structure allows us to demonstrate the existence and stability of pattern states on the bottom layer, but most remarkably, it enables a simple mechanism for switching between patterns based on the unique symmetry-breaking role of the governing layer. We demonstrate that the symmetry breaker prevents complete synchronization in the bottom layer, a situation that would not be desirable in a normal functioning brain. We illustrate our findings using two layers of Hindmarsh-Rose (HR) oscillators, employing the Master Stability function approach in small networks to investigate the switching between patterns.

对称性断路器制约着神经元启发网络的同步模式。
人脑实验显示,随着时间的推移,不同的活动模式和功能网络组织之间会发生切换。最近,多层建模被用于多个神经生物学层面(从尖峰网络到脑区),以揭示同步模式的出现和时间演化的新见解。我们考虑了顶层与底层直接耦合的两层。在孤立状态下,底层会保持特定的稳定模式。然而,在顶层存在的情况下,网络会出现时空切换。顶层与层间耦合相结合,就像对称性断路器一样,控制着底层,并限制了允许的对称性诱导模式的数量。这种结构使我们能够证明底层上图案状态的存在和稳定性,但最引人注目的是,它使我们能够在治理层独特的对称性破坏作用基础上实现图案间切换的简单机制。我们证明,对称性破坏器可以防止底层完全同步,而这种情况在正常运作的大脑中是不可取的。我们利用两层兴德马什-罗斯(HR)振荡器来说明我们的发现,在小型网络中采用主稳定函数方法来研究模式之间的切换。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Chaos
Chaos 物理-物理:数学物理
CiteScore
5.20
自引率
13.80%
发文量
448
审稿时长
2.3 months
期刊介绍: Chaos: An Interdisciplinary Journal of Nonlinear Science is a peer-reviewed journal devoted to increasing the understanding of nonlinear phenomena and describing the manifestations in a manner comprehensible to researchers from a broad spectrum of disciplines.
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