Articles producció científica> Enginyeria Informàtica i Matemàtiques

Mapping multiplex hubs in human functional brain networks

  • Dades identificatives

    Identificador: PC:1904
    Autors:
    Manlio de DomenicoShuntaro SasaiAlex Arenas
    Resum:
    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.
  • Altres:

    Autor segons l'article: Manlio de Domenico; Shuntaro Sasai; Alex Arenas
    Departament: Enginyeria Informàtica i Matemàtiques
    Autor/s de la URV: DE DOMENICO ., MANLIO; Shuntaro Sasai; ARENAS MORENO, ALEJANDRO
    Paraules clau: Brain fMRI schizophrenia Multiplex hubs
    Resum: 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.
    Grup de recerca: Algorithms embedded in Physical Systems
    Àrees temàtiques: Computer engineering Ingeniería informática Enginyeria informàtica
    Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
    ISSN: 1662-453X
    Identificador de l'autor: 0000-0001-5158-8594; 0000-0002-9941-6510; 0000-0003-0937-0334
    Data d'alta del registre: 2016-09-21
    Volum de revista: 10
    Versió de l'article dipositat: info:eu-repo/semantics/publishedVersion
    Enllaç font original: http://journal.frontiersin.org/article/10.3389/fnins.2016.00326/full
    URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
    DOI de l'article: 10.3389/fnins.2016.00326
    Entitat: Universitat Rovira i Virgili
    Any de publicació de la revista: 2016
    Pàgina inicial: Art. num. 326
    Tipus de publicació: Article Artículo Article
  • Paraules clau:

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