Yamamoto Hideaki, Kubota Shigeru, Shimizu Fabio A, Hirano-Iwata Ayumi, Niwano Michio
Frontier Research Institute for Interdisciplinary Sciences, Tohoku University, Sendai, Japan.
Graduate School of Science and Engineering, Yamagata University, Yamagata, Japan.
Front Comput Neurosci. 2018 Mar 28;12:17. doi: 10.3389/fncom.2018.00017. eCollection 2018.
A system consisting of interconnected networks, or a network of networks (NoN), appears diversely in many real-world systems, including the brain. In this study, we consider NoNs consisting of heterogeneous phase oscillators and investigate how the topology of subnetworks affects the global synchrony of the network. The degree of synchrony and the effect of subnetwork topology are evaluated based on the Kuramoto order parameter and the minimum coupling strength necessary for the order parameter to exceed a threshold value, respectively. In contrast to an isolated network in which random connectivity is favorable for achieving synchrony, NoNs synchronize with weaker interconnections when the degree distribution of subnetworks is heterogeneous, suggesting the major role of the high-degree nodes. We also investigate a case in which subnetworks with different average natural frequencies are coupled to show that direct coupling of subnetworks with the largest variation is effective for synchronizing the whole system. In real-world NoNs like the brain, the balance of synchrony and asynchrony is critical for its function at various spatial resolutions. Our work provides novel insights into the topological basis of coordinated dynamics in such networks.
一个由相互连接的网络组成的系统,即网络的网络(NoN),在包括大脑在内的许多现实世界系统中都有不同的表现。在本研究中,我们考虑由异构相位振荡器组成的NoN,并研究子网拓扑结构如何影响网络的全局同步性。同步程度和子网拓扑结构的影响分别基于Kuramoto序参量和序参量超过阈值所需的最小耦合强度来评估。与随机连接有利于实现同步的孤立网络不同,当子网的度分布不均匀时,NoN在较弱的互连情况下就能同步,这表明了高度数节点的主要作用。我们还研究了具有不同平均固有频率的子网耦合的情况,以表明变化最大的子网之间的直接耦合对于整个系统的同步是有效的。在像大脑这样的现实世界NoN中,同步和异步的平衡对于其在各种空间分辨率下的功能至关重要。我们的工作为此类网络中协调动力学的拓扑基础提供了新的见解。