Your browser doesn't support javascript.
loading
Transitions between human functional brain networks reveal complex, cost-efficient and behaviorally-relevant temporal paths.
Ramirez-Mahaluf, Juan P; Medel, Vicente; Tepper, Ángeles; Alliende, Luz Maria; Sato, Joao R; Ossandon, Tomas; Crossley, Nicolas A.
Afiliação
  • Ramirez-Mahaluf JP; Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile.
  • Medel V; Center for Integrative Neuroscience, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile.
  • Tepper Á; Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile.
  • Alliende LM; Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile.
  • Sato JR; Center for Mathematics, Computing and Cognition, Universidade Federal do ABC - Santo André, São Paulo, Brazil.
  • Ossandon T; Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile; Center for Integrative Neuroscience, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile.
  • Crossley NA; Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile; Center for Integrative Neuroscience, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile; Biomedical Imaging Center, Pontificia Universidad Católica de Chile, Chile; Mil
Neuroimage ; 219: 117027, 2020 10 01.
Article em En | MEDLINE | ID: mdl-32522663
Resting-state functional MRI activity is organized as a complex network. However, this coordinated brain activity changes with time, raising questions about its evolving temporal arrangement. Does the brain visit different configurations through time in a random or ordered way? Advances in this area depend on developing novel paradigms that would allow us to shed light on these issues. We here propose to study the temporal changes in the functional connectome by looking at transition graphs of network activity. Nodes of these graphs correspond to brief whole-brain connectivity patterns (or meta-states), and directed links to the temporal transition between consecutive meta-states. We applied this method to two datasets of healthy subjects (160 subjects and a replication sample of 54), and found that transition networks had several non-trivial properties, such as a heavy-tailed degree distribution, high clustering, and a modular organization. This organization was implemented at a low biological cost with a high cost-efficiency of the dynamics. Furthermore, characteristics of the subjects' transition graphs, including global efficiency, local efficiency and their transition cost, were correlated with cognition and motor functioning. All these results were replicated in both datasets. We conclude that time-varying functional connectivity patterns of the brain in health progress in time in a highly organized and complex order, which is related to behavior.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Encéfalo / Cognição / Rede de Modo Padrão / Rede Nervosa Tipo de estudo: Health_economic_evaluation / Prognostic_studies Limite: Adult / Female / Humans / Male Idioma: En Revista: Neuroimage Assunto da revista: DIAGNOSTICO POR IMAGEM Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Chile País de publicação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Encéfalo / Cognição / Rede de Modo Padrão / Rede Nervosa Tipo de estudo: Health_economic_evaluation / Prognostic_studies Limite: Adult / Female / Humans / Male Idioma: En Revista: Neuroimage Assunto da revista: DIAGNOSTICO POR IMAGEM Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Chile País de publicação: Estados Unidos