Institut für Theoretische Physik, Technische Universität Berlin, 10623 Berlin, Germany.
Department of Neurosurgery, Stanford University, Stanford, California 94305, USA.
Chaos. 2023 Feb;33(2):023123. doi: 10.1063/5.0128102.
Rhythmic activities that alternate between coherent and incoherent phases are ubiquitous in chemical, ecological, climate, or neural systems. Despite their importance, general mechanisms for their emergence are little understood. In order to fill this gap, we present a framework for describing the emergence of recurrent synchronization in complex networks with adaptive interactions. This phenomenon is manifested at the macroscopic level by temporal episodes of coherent and incoherent dynamics that alternate recurrently. At the same time, the dynamics of the individual nodes do not change qualitatively. We identify asymmetric adaptation rules and temporal separation between the adaptation and the dynamics of individual nodes as key features for the emergence of recurrent synchronization. Our results suggest that asymmetric adaptation might be a fundamental ingredient for recurrent synchronization phenomena as seen in pattern generators, e.g., in neuronal systems.
在化学、生态、气候或神经等系统中，普遍存在在连贯和非连贯相位之间交替的节奏性活动。尽管它们很重要，但对于它们的出现的一般机制却知之甚少。为了填补这一空白，我们提出了一个框架，用于描述具有自适应相互作用的复杂网络中反复同步的出现。这种现象在宏观层面上表现为连贯和非连贯动力学的时间片段反复交替。同时，个体节点的动力学没有定性变化。我们确定了不对称的适应规则和个体节点的适应和动力学之间的时间分离，作为反复同步出现的关键特征。我们的研究结果表明，不对称适应可能是模式生成器中反复同步现象的基本组成部分，例如在神经元系统中。
