title: Scale-free brain functional networks.
abstract: Functional magnetic resonance imaging is used to extract functional networks connecting correlated human brain sites. Analysis of the resulting networks in different tasks shows that (a) the distribution of functional connections, and the probability of finding a link versus distance are both scale-free, (b) the characteristic path length is small and comparable with those of equivalent random networks, and (c) the clustering coefficient is orders of magnitude larger than those of equivalent random networks. All these properties, typical of scale-free small-world networks, reflect important functional information about brain states.
authors.affiliation: Instituto Mediterráneo de Estudios Avanzados, IMEDEA, E07122 Palma de Mallorca, Spain.
authors.forename: Victor M
authors.initials: VM
authors.lastname: Eguíluz
authors.forename: Dante R
authors.initials: DR
authors.lastname: Chialvo
authors.forename: Guillermo A
authors.initials: GA
authors.lastname: Cecchi
authors.forename: Marwan
authors.initials: M
authors.lastname: Baliki
authors.forename: A Vania
authors.initials: AV
authors.lastname: Apkarian
mesh_terms: D001931:Brain Mapping / Q000379:methods*; D002540:Cerebral Cortex / Q000033:anatomy & histology / Q000502:physiology*; D003071:Cognition / Q000502:physiology*; D003198:Computer Simulation; D005071:Evoked Potentials / Q000502:physiology*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods; D008959:Models, Neurological; D015233:Models, Statistical; D009415:Nerve Net / Q000502:physiology*