AUTHOR=Yamamoto Hideaki , Kubota Shigeru , Shimizu Fabio A. , Hirano-Iwata Ayumi , Niwano Michio TITLE=Effective Subnetwork Topology for Synchronizing Interconnected Networks of Coupled Phase Oscillators JOURNAL=Frontiers in Computational Neuroscience VOLUME=12 YEAR=2018 URL=https://www.frontiersin.org/journals/computational-neuroscience/articles/10.3389/fncom.2018.00017 DOI=10.3389/fncom.2018.00017 ISSN=1662-5188 ABSTRACT=

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.