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. 2017 Sep 7;7:10879. doi: 10.1038/s41598-017-07846-w

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© The Author(s) 2017

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Multi-frequency brain networks. Panel (a) shows brain networks of a representative subject extracted from seven frequency bands. Links are inferred by means of spectral coherence and thresholded to have in each layer an average node degree k = 12. (b) Procedure to construct a multi-frequency network. Each layer corresponds to a different frequency band. Only nodes representing the same brain region in each layer are virtually connected. Hence, inter-layer links code for identity relationships. (c) Inter-frequency node centrality. A two-layer multiplex is considered for the sake of simplicity. The blue node acts as an inter-frequency hub (i.e., multi-participation coefficient MPC = 1) as it allows for a balanced information transfer between layer β ₁ and β ₂; the red node, who is disconnected in layer β ₂, blocks the information flow and has MPC = 0.