Information Diversity in Structure and Dynamics of Simulated Neuronal Networks

    Tutkimustuotos: ArtikkeliScientificvertaisarvioitu

    8 Sitaatiot (Scopus)
    9 Lataukset (Pure)

    Abstrakti

    Neuronal networks exhibit a wide diversity of structures, which contributes to the diversity of the dynamics therein. The presented work applies an information theoretic framework to simultaneously analyze structure and dynamics in neuronal networks. Information diversity within the structure and dynamics of a neuronal network is studied using the normalized compression distance. To describe the structure, a scheme for generating distance-dependent networks with identical in-degree distribution but variable strength of dependence on distance is presented. The resulting network structure classes possess differing path length and clustering coefficient distributions. In parallel, comparable realistic neuronal networks are generated with NETMORPH simulator and similar analysis is done on them. To describe the dynamics, network spike trains are simulated using different network structures and their bursting behaviors are analyzed. For the simulation of the network activity the Izhikevich model of spiking neurons is used together with the Tsodyks model of dynamical synapses. We show that the structure of the simulated neuronal networks affects the spontaneous bursting activity when measured with bursting frequency and a set of intraburst measures: the more locally connected produce more and longer bursts than the more random networks. The information diversity of the structure of a network is greatest in the most locally connected, smallest in random networks, and somewhere in between in the networks between order and disorder. As for the dynamics, the most locally connected and some of the in-between networks produce the most complex intraburst spike trains. The same result also holds for sparser of the two considered network densities in the case of full spike trains.
    AlkuperäiskieliEnglanti
    Artikkeli26
    Sivut1-17
    Sivumäärä17
    JulkaisuFrontiers in Computational Neuroscience
    Vuosikerta5
    Numero26
    DOI - pysyväislinkit
    TilaJulkaistu - 2011
    OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

    Julkaisufoorumi-taso

    • Jufo-taso 1

    Sormenjälki

    Sukella tutkimusaiheisiin 'Information Diversity in Structure and Dynamics of Simulated Neuronal Networks'. Ne muodostavat yhdessä ainutlaatuisen sormenjäljen.

    Siteeraa tätä