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Toward a theory of coactivation patterns in excitable neural networks.
Messé, Arnaud; Hütt, Marc-Thorsten; Hilgetag, Claus C.
Afiliação
  • Messé A; Institute of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, Hamburg, Germany.
  • Hütt MT; Department of Life Sciences and Chemistry, Jacobs University, Bremen, Germany.
  • Hilgetag CC; Institute of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, Hamburg, Germany.
PLoS Comput Biol ; 14(4): e1006084, 2018 04.
Article em En | MEDLINE | ID: mdl-29630592
The relationship between the structural connectivity (SC) and functional connectivity (FC) of neural systems is of central importance in brain network science. It is an open question, however, how the SC-FC relationship depends on specific topological features of brain networks or the models used for describing neural dynamics. Using a basic but general model of discrete excitable units that follow a susceptible-excited-refractory activity cycle (SER model), we here analyze how the network activity patterns underlying functional connectivity are shaped by the characteristic topological features of the network. We develop an analytical framework for describing the contribution of essential topological elements, such as common inputs and pacemakers, to the coactivation of nodes, and demonstrate the validity of the approach by comparison of the analytical predictions with numerical simulations of various exemplar networks. The present analytic framework may serve as an initial step for the mechanistic understanding of the contributions of brain network topology to brain dynamics.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Encéfalo / Modelos Neurológicos / Rede Nervosa Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Encéfalo / Modelos Neurológicos / Rede Nervosa Idioma: En Ano de publicação: 2018 Tipo de documento: Article