Articles producció científica> Enginyeria Informàtica i Matemàtiques

Mapping multiplex hubs in human functional brain networks

  • Identification data

    Identifier: PC:1904
    Authors:
    Manlio de DomenicoShuntaro SasaiAlex Arenas
    Abstract:
    Typical brain networks consist of many peripheral regions and a few highly central ones, i.e., hubs, playing key functional roles in cerebral inter-regional interactions. Studies have shown that networks, obtained from the analysis of specific frequency components of brain activity, present peculiar architectures with unique profiles of region centrality. However, the identification of hubs in networks built from different frequency bands simultaneously is still a challenging problem, remaining largely unexplored. Here we identify each frequency component with one layer of a multiplex network and face this challenge by exploiting the recent advances in the analysis of multiplex topologies. First, we show that each frequency band carries unique topological information, fundamental to accurately model brain functional networks. We then demonstrate that hubs in the multiplex network, in general different from those ones obtained after discarding or aggregating the measured signals as usual, provide a more accurate map of brain's most important functional regions, allowing to distinguish between healthy and schizophrenic populations better than conventional network approaches.
  • Others:

    Author, as appears in the article.: Manlio de Domenico; Shuntaro Sasai; Alex Arenas
    Department: Enginyeria Informàtica i Matemàtiques
    URV's Author/s: DE DOMENICO ., MANLIO; Shuntaro Sasai; ARENAS MORENO, ALEJANDRO
    Keywords: Brain fMRI schizophrenia Multiplex hubs
    Abstract: Typical brain networks consist of many peripheral regions and a few highly central ones, i.e., hubs, playing key functional roles in cerebral inter-regional interactions. Studies have shown that networks, obtained from the analysis of specific frequency components of brain activity, present peculiar architectures with unique profiles of region centrality. However, the identification of hubs in networks built from different frequency bands simultaneously is still a challenging problem, remaining largely unexplored. Here we identify each frequency component with one layer of a multiplex network and face this challenge by exploiting the recent advances in the analysis of multiplex topologies. First, we show that each frequency band carries unique topological information, fundamental to accurately model brain functional networks. We then demonstrate that hubs in the multiplex network, in general different from those ones obtained after discarding or aggregating the measured signals as usual, provide a more accurate map of brain's most important functional regions, allowing to distinguish between healthy and schizophrenic populations better than conventional network approaches.
    Research group: Algorithms embedded in Physical Systems
    Thematic Areas: Computer engineering Ingeniería informática Enginyeria informàtica
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    ISSN: 1662-453X
    Author identifier: 0000-0001-5158-8594; 0000-0002-9941-6510; 0000-0003-0937-0334
    Record's date: 2016-09-21
    Journal volume: 10
    Papper version: info:eu-repo/semantics/publishedVersion
    Link to the original source: http://journal.frontiersin.org/article/10.3389/fnins.2016.00326/full
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Article's DOI: 10.3389/fnins.2016.00326
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2016
    First page: Art. num. 326
    Publication Type: Article Artículo Article
  • Keywords:

    Frequency bands
    Cartografia cerebral
    Esquizofrènia
    Xarxes -- Anàlisi
    Brain fMRI
    schizophrenia
    Multiplex hubs
    Computer engineering
    Ingeniería informática
    Enginyeria informàtica
    1662-453X
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