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Sensory, somatomotor and internal mentation networks emerge dynamically in the resting brain with internal mentation predominating in older age.
Zhang, Lu; Zhao, Jiajia; Zhou, Qunjie; Liu, Zhaowen; Zhang, Yi; Cheng, Wei; Gong, Weikang; Hu, Xiaoping; Lu, Wenlian; Bullmore, Edward T; Lo, Chun-Yi Zac; Feng, Jianfeng.
Afiliación
  • Zhang L; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China; Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China; Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA
  • Zhao J; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China.
  • Zhou Q; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China.
  • Liu Z; Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, United States; Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, United States.
  • Zhang Y; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China.
  • Cheng W; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China.
  • Gong W; Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford OX3 9DU, United Kingdom.
  • Hu X; Department of Bioengineering, University of California, Riverside, CA, United States.
  • Lu W; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China; Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China; School of Mathematical Sciences, Fudan University, Shanghai, China.
  • Bullmore ET; Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, United Kingdom; Cambridgeshire and Peterborough NHS Foundation Trust, Huntingdon PE29 3RJ, United Kingdom.
  • Lo CZ; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China. Electronic address: zaclocy@gmail.com.
  • Feng J; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China; Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China; Oxford Centre for Computational Neuroscience, Oxford, United Kingdom; Department of Computer Science, Universit
Neuroimage ; 237: 118188, 2021 08 15.
Article en En | MEDLINE | ID: mdl-34020018
Age-related changes in the brain are associated with a decline in functional flexibility. Intrinsic functional flexibility is evident in the brain's dynamic ability to switch between alternative spatiotemporal states during resting state. However, the relationship between brain connectivity states, associated psychological functions during resting state, and the changes in normal aging remain poorly understood. In this study, we analyzed resting-state functional magnetic resonance imaging (rsfMRI) data from the Human Connectome Project (HCP; N = 812) and the UK Biobank (UKB; N = 6,716). Using signed community clustering to identify distinct states of dynamic functional connectivity, and text-mining of a large existing literature for functional annotation of each state, our findings from the HCP dataset indicated that the resting brain spontaneously transitions between three functionally specialized states: sensory, somatomotor, and internal mentation networks. The occurrence, transition-rate, and persistence-time parameters for each state were correlated with behavioural scores using canonical correlation analysis. We estimated the same brain states and parameters in the UKB dataset, subdivided into three distinct age ranges: 50-55, 56-67, and 68-78 years. We found that the internal mentation network was more frequently expressed in people aged 71 and older, whereas people younger than 55 more frequently expressed sensory and somatomotor networks. Furthermore, analysis of the functional entropy - a measure of uncertainty of functional connectivity - also supported this finding across the three age ranges. Our study demonstrates that dynamic functional connectivity analysis can expose the time-varying patterns of transition between functionally specialized brain states, which are strongly tied to increasing age.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Encéfalo / Envejecimiento / Conectoma / Red en Modo Predeterminado / Procesos Mentales / Red Nerviosa Tipo de estudio: Prognostic_studies Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Neuroimage Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2021 Tipo del documento: Article

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Encéfalo / Envejecimiento / Conectoma / Red en Modo Predeterminado / Procesos Mentales / Red Nerviosa Tipo de estudio: Prognostic_studies Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Neuroimage Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2021 Tipo del documento: Article