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- W2598246502 abstract "We explore how to study dynamical interactions between brain regions by using functional multilayer networks whose layers represent different frequency bands at which a brain operates. Specifically, we investigate the consequences of considering the brain as (i) a multilayer network, in which all brain regions can interact with each other at different frequency bands; and as (ii) a multiplex network, in which interactions between different frequency bands are allowed only within each brain region and not between them. We study the second-smallest eigenvalue λ 2 of the combinatorial supra-Laplacian matrix of both the multiplex and multilayer networks, as λ 2 has been used previously as an indicator of network synchronizability and as a biomarker for several brain diseases. We show that the heterogeneity of interlayer edge weights and, especially, the fraction of missing edges crucially modify the value of λ 2 , and we illustrate our results with both synthetic network models and real data obtained from resting-state magnetoencephalography. Our work highlights the differences between using a multiplex approach and a full multilayer approach when studying frequency-based multilayer brain networks." @default.
- W2598246502 created "2017-04-07" @default.
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- W2598246502 date "2018-10-01" @default.
- W2598246502 modified "2023-10-10" @default.
- W2598246502 title "Frequency-based brain networks: From a multiplex framework to a full multilayer description" @default.
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- W2598246502 doi "https://doi.org/10.1162/netn_a_00033" @default.
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