title: Weighted phase lag index and graph analysis: preliminary investigation of functional connectivity during resting state in children.
abstract: Resting state functional connectivity of MEG data was studied in 29 children (9-10 years old). The weighted phase lag index (WPLI) was employed for estimating connectivity and compared to coherence. To further evaluate the network structure, a graph analysis based on WPLI was used to determine clustering coefficient (C) and betweenness centrality (BC) as local coefficients as well as the characteristic path length (L) as a parameter for global interconnectedness. The network's modular structure was also calculated to estimate functional segregation. A seed region was identified in the central occipital area based on the power distribution at the sensor level in the alpha band. WPLI reveals a specific connectivity map different from power and coherence. BC and modularity show a strong level of connectedness in the occipital area between lateral and central sensors. C shows different isolated areas of occipital sensors. Globally, a network with the shortest L is detected in the alpha band, consistently with the local results. Our results are in agreement with findings in adults, indicating a similar functional network in children at this age in the alpha band. The integrated use of WPLI and graph analysis can help to gain a better description of resting state networks.
authors.affiliation: MEG Center, University of Tübingen, Germany.
authors.forename: Erick
authors.initials: E
authors.lastname: Ortiz
authors.forename: Krunoslav
authors.initials: K
authors.lastname: Stingl
authors.forename: Jana
authors.initials: J
authors.lastname: Münssinger
authors.forename: Christoph
authors.initials: C
authors.lastname: Braun
authors.forename: Hubert
authors.initials: H
authors.lastname: Preissl
authors.forename: Paolo
authors.initials: P
authors.lastname: Belardinelli
mesh_terms: D000465:Algorithms; D001931:Brain Mapping / Q000379:methods; D002648:Child; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods; D005260:Female; D006801:Humans; D015225:Magnetoencephalography / Q000379:methods*; D008297:Male; D008959:Models, Neurological; D009415:Nerve Net / Q000503:physiopathology; D009434:Neural Pathways; D012044:Regression Analysis; D015203:Reproducibility of Results; D012146:Rest; D012815:Signal Processing, Computer-Assisted