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Integrating cross-frequency and within band functional networks in resting-state MEG: A multi-layer network approach

Van Mieghem, Piet; Tewarie, Prejaas; Hillebrand, Arjan; van Dijk, Bob W.; Stam, Cornelis J.; O'Neill, George C.; Morris, Peter G.; Meier, Jil M.; Woolrich, Mark W.; Brookes, Matthew J.

Authors

Piet Van Mieghem

Prejaas Tewarie

Arjan Hillebrand

Bob W. van Dijk

Cornelis J. Stam

George C. O'Neill

Jil M. Meier

Mark W. Woolrich



Abstract

Neuronal oscillations exist across a broad frequency spectrum, and are thought to provide a mechanism of interaction between spatially separated brain regions. Since ongoing mental activity necessitates the simultaneous formation of multiple networks, it seems likely that the brain employs interactions within multiple frequency bands, as well as cross-frequency coupling, to support such networks. Here, we propose a multi-layer network framework that elucidates this pan-spectral picture of network interactions. Our network consists of multiple layers (frequency-band specific networks) that influence each other via inter-layer (cross-frequency) coupling. Applying this model to MEG resting-state data and using envelope correlations as connectivity metric, we demonstrate strong dependency between within layer structure and inter-layer coupling, indicating that networks obtained in different frequency bands do not act as independent entities. More specifically, our results suggest that frequency band specific networks are characterised by a common structure seen across all layers, superimposed by layer specific connectivity, and inter-layer coupling is most strongly associated with this common mode. Finally, using a biophysical model, we demonstrate that there are two regimes of multi-layer network behaviour; one in which different layers are independent and a second in which they operate highly dependent. Results suggest that the healthy human brain operates at the transition point between these regimes, allowing for integration and segregation between layers. Overall, our observations show that a complete picture of global brain network connectivity requires integration of connectivity patterns across the full frequency spectrum.

Citation

Van Mieghem, P., Tewarie, P., Hillebrand, A., van Dijk, B. W., Stam, C. J., O'Neill, G. C., …Brookes, M. J. (2016). Integrating cross-frequency and within band functional networks in resting-state MEG: A multi-layer network approach. NeuroImage, 142, 324-336. https://doi.org/10.1016/j.neuroimage.2016.07.057

Journal Article Type Article
Acceptance Date Jul 27, 2016
Online Publication Date Aug 3, 2016
Publication Date Nov 15, 2016
Deposit Date Feb 28, 2020
Publicly Available Date Feb 28, 2020
Journal NeuroImage
Print ISSN 1053-8119
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 142
Pages 324-336
DOI https://doi.org/10.1016/j.neuroimage.2016.07.057
Public URL https://nottingham-repository.worktribe.com/output/4050295
Additional Information This article is maintained by: Elsevier; Article Title: Integrating cross-frequency and within band functional networks in resting-state MEG: A multi-layer network approach; Journal Title: NeuroImage; CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.neuroimage.2016.07.057; Content Type: article; Copyright: © 2016 Published by Elsevier Inc.

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