title: Integration versus segregation in functional brain networks.
abstract: We propose a new methodology to evaluate the balance between segregation and integration in functional brain networks by using singular value decomposition techniques. By means of magnetoencephalography, we obtain the brain activity of a control group of 19 individuals during a memory task. Next, we project the node-to-node correlations into a complex network that is analyzed from the perspective of its modular structure encoded in the contribution matrix. In this way, we are able to study the role that nodes play I/O its community and to identify connector and local hubs. At the mesoscale level, the analysis of the contribution matrix allows us to measure the degree of overlapping between communities and quantify how far the functional networks are from the configuration that better balances the integrated and segregated activity.
authors: Complex Systems Group, Universidad Rey Juan Carlos, Móstoles, Madrid 28933, Spain. irene.sendina@urjc.es
authors: I
authors: I
authors: Sendiña-Nadal
authors: Javier M
authors: JM
authors: Buldú
authors: I
authors: I
authors: Leyva
authors: R
authors: R
authors: Bajo
authors: J A
authors: JA
authors: Almendral
authors: F
authors: F
authors: del-Pozo
mesh_terms: D000368:Aged; D000465:Algorithms; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D006801:Humans; D015225:Magnetoencephalography; D008568:Memory / Q000502:physiology*; D009415:Nerve Net / Q000502:physiology*; D012815:Signal Processing, Computer-Assisted; D013647:Task Performance and Analysis