title: Modelling hierarchical structure in functional brain networks.
abstract: In this work, we focus on a complex-network approach for the study of the brain. In particular, we consider functional brain networks, where the vertices represent different anatomical regions and the links their functional connectivity. First, we build these networks using data obtained with functional magnetic resonance imaging. Then, we analyse the main characteristics of these complex networks, including degree distribution, the presence of modules and hierarchical structure. Finally, we present a network model with dynamical nodes and adaptive links. We show that the model allows for the emergence of complex networks with characteristics similar to those observed in functional brain networks.
authors.affiliation: Centro Atómico Bariloche, Instituto Balseiro, CONICET, Bariloche, 8400 Río Negro, Argentina. gleiser@cab.cnea.gov.ar
authors.forename: Pablo M
authors.initials: PM
authors.lastname: Gleiser
authors.forename: Victor I
authors.initials: VI
authors.lastname: Spoormaker
mesh_terms: D000465:Algorithms; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping; D016000:Cluster Analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008954:Models, Biological; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology