Partial Phase Cohesiveness in Networks of Networks of Kuramoto Oscillators

Yuzhen Qin, Yu Kawano, Oscar Portoles Marin, Ming Cao

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Abstract

Partial, instead of complete, synchronization has been widely observed in various networks including, in particular, brain networks. Motivated by data from human brain functional networks, in this technical note, we analytically show that partial
synchronization can be induced by strong regional connections in coupled subnetworks of Kuramoto oscillators. To quantify the required strength of regional connections, we first obtain a critical value for the algebraic connectivity of the corresponding subnetwork using the incremental 2-norm. We then introduce the concept of the generalized complement graph, and obtain another
condition on the node strength by using the incremental infinity-norm. Under these two conditions, regions of attraction for partial phase cohesiveness are estimated in the forms of the incremental 2- and infinity-norms, respectively. Our result based on the incremental infinity-norm is the first known criterion that applies to non-complete graphs. Numerical simulations are performed on a two-level network to illustrate our theoretical results; more importantly, we use real anatomical brain network data to show how our results may contribute to a better understanding of the interplay between anatomical structure and empirical patterns of synchrony.
Original languageEnglish
Number of pages8
JournalIEEE-Transactions on Automatic Control
Volume67
Issue number2
Early online date24-Feb-2021
DOIs
Publication statusE-pub ahead of print - 24-Feb-2021

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