2017/03/17 by Javier M. Buldú, Mason A. Porter, Buldú, Javier M. +1 · 3 citations
Computer Science · Neuroscience · #Blind Source Separation Techniques #Combinatorics (math.CO) #Data Analysis #FOS: Biological sciences #FOS: Mathematics #FOS: Physical sciences #Functional Brain Connectivity Studies #Neural dynamics and brain function #Neurons and Cognition (q-bio.NC) #Statistics and Probability (physics.data-an)
paper · pdf · doi:10.48550/arxiv.1703.06091
openalex publication_date 2017/03/17 · openalex created_date 2022/10/01 · openalex updated_date 2026/07/28
We explore how to study dynamical interactions between brain regions using\nfunctional multilayer networks whose layers represent the different frequency\nbands at which a brain operates. Specifically, we investigate the consequences\nof considering the brain as a multilayer network in which all brain regions can\ninteract with each other at different frequency bands, instead of as a\nmultiplex network, in which interactions between different frequency bands are\nonly allowed within each brain region and not between them. We study the second\nsmallest eigenvalue of the combinatorial supra-Laplacian matrix of the\nmultilayer network in detail, and we thereby show that the heterogeneity of\ninterlayer edges and, especially, the fraction of missing edges crucially\nmodify the spectral properties of the multilayer network. We illustrate our\nresults with both synthetic network models and real data sets obtained from\nresting state magnetoencephalography. Our work demonstrates an important issue\nin the construction of frequency-based multilayer brain networks.\n