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Adaptive reconfiguration of fractal small-world human brain functional networks

Proceedings of the National Academy of Sciences - PNAS, 2006-12, Vol.103 (51), p.19518-19523 [Peer Reviewed Journal]

Copyright 2006 National Academy of Sciences of the United States of America ;Copyright National Academy of Sciences Dec 19, 2006 ;2006 by The National Academy of Sciences of the USA 2006 ;ISSN: 0027-8424 ;EISSN: 1091-6490 ;DOI: 10.1073/pnas.0606005103 ;PMID: 17159150

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  • Title:
    Adaptive reconfiguration of fractal small-world human brain functional networks
  • Author: Bassett, Danielle S. ; Meyer-Lindenberg, Andreas ; Achard, Sophie ; Duke, Thomas ; Bullmore, Edward
  • Subjects: Behavioral neuroscience ; Biological Sciences ; Brain ; Brain - cytology ; Brain - physiology ; Connectivity ; Fractals ; Frequency ranges ; Humans ; Magnetoencephalography ; Mathematical independent variables ; Mental Processes - physiology ; Models, Neurological ; Motor ability ; Nerve Net ; Neurology ; Neurosciences ; Psychomotor Performance ; Studies ; Time series ; Topology ; Vibrational frequencies ; Wavelet analysis
  • Is Part Of: Proceedings of the National Academy of Sciences - PNAS, 2006-12, Vol.103 (51), p.19518-19523
  • Description: Brain function depends on adaptive self-organization of large-scale neural assemblies, but little is known about quantitative network parameters governing these processes in humans. Here, we describe the topology and synchronizability of frequency-specific brain functional networks using wavelet decomposition of magnetoencephalographic time series, followed by construction and analysis of undirected graphs. Magnetoencephalographic data were acquired from 22 subjects, half of whom performed a finger-tapping task, whereas the other half were studied at rest. We found that brain functional networks were characterized by small-world properties at all six wavelet scales considered, corresponding approximately to classical δ (low and high), {theta}, α, β, and γ frequency bands. Global topological parameters (path length, clustering) were conserved across scales, most consistently in the frequency range 2-37 Hz, implying a scale-invariant or fractal small-world organization. Dynamical analysis showed that networks were located close to the threshold of order/disorder transition in all frequency bands. The highest-frequency γ network had greater synchronizability, greater clustering of connections, and shorter path length than networks in the scaling regime of (lower) frequencies. Behavioral state did not strongly influence global topology or synchronizability; however, motor task performance was associated with emergence of long-range connections in both β and γ networks. Long-range connectivity, e.g., between frontal and parietal cortex, at high frequencies during a motor task may facilitate sensorimotor binding. Human brain functional networks demonstrate a fractal small-world architecture that supports critical dynamics and task-related spatial reconfiguration while preserving global topological parameters.
  • Publisher: United States: National Academy of Sciences
  • Language: English
  • Identifier: ISSN: 0027-8424
    EISSN: 1091-6490
    DOI: 10.1073/pnas.0606005103
    PMID: 17159150
  • Source: Open Access: PubMed Central
    GFMER Free Medical Journals
    MEDLINE
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