Print Email Facebook Twitter Brain network clustering with information flow motifs Title Brain network clustering with information flow motifs Author Märtens, M. (TU Delft Network Architectures and Services) Meier, J.M. (TU Delft Network Architectures and Services) Hillebrand, Arjan (Amsterdam UMC) Tewarie, Prejaas (University of Nottingham) Van Mieghem, P.F.A. (TU Delft Network Architectures and Services) Date 2017 Abstract Recent work has revealed frequency-dependent global patterns of information flow by a network analysis of magnetoencephalography data of the human brain. However, it is unknown which properties on a small subgraph-scale of those functional brain networks are dominant at different frequencies bands. Motifs are the building blocks of networks on this level and have previously been identified as important features for healthy and abnormal brain function. In this study, we present a network construction that enables us to search and analyze motifs in different frequency bands. We give evidence that the bi-directional two-hop path is the most important motif for the information flow in functional brain networks. A clustering based on this motif exposes a spatially coherent yet frequency-dependent sub-division between the posterior, occipital and frontal brain regions. Subject Network motifsNetwork clusteringBrain networksInformation flowEffective connectivityOA-Fund TU Delft To reference this document use: http://resolver.tudelft.nl/uuid:077bcb2c-126c-4022-be0f-8c3bf1a60251 DOI https://doi.org/10.1007/s41109-017-0046-z ISSN 2364-8228 Source Applied Network Science, 2, 1-18 Part of collection Institutional Repository Document type journal article Rights © 2017 M. Märtens, J.M. Meier, Arjan Hillebrand, Prejaas Tewarie, P.F.A. Van Mieghem Files PDF s41109_017_0046_z.pdf 2.61 MB Close viewer /islandora/object/uuid:077bcb2c-126c-4022-be0f-8c3bf1a60251/datastream/OBJ/view