Effective subnetwork topology for synchronizing interconnected networks of coupled phase oscillators

Hideaki Yamamoto, Shigeru Kubota, Fabio A. Shimizu, Ayumi Hirano-Iwata, Michio Niwano

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

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.

Original languageEnglish
Article number17
JournalFrontiers in Computational Neuroscience
Volume12
DOIs
Publication statusPublished - 2018 Mar 28

Keywords

  • Complex networks
  • Kuramoto model
  • Modular organization
  • Phase oscillator
  • Synchronization
  • Synchrony alignment function

ASJC Scopus subject areas

  • Neuroscience (miscellaneous)
  • Cellular and Molecular Neuroscience

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