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Study of effects of cognitive reserve on brain networks based on rest state functional magnetic resonance imaging / 医疗卫生装备
Article en Zh | WPRIM | ID: wpr-1022946
Biblioteca responsable: WPRO
ABSTRACT
Objective To explore the effects of cognitive reserve on brain networks based on rest state functional magnetic resonance imaging(rsfMRI).Methods Firstly,7 973 healthy middle-aged and elderly individuals were selected for rsfMRI images at UK Biobank(UKB),and 21 resting-state networks were obtained through group independent component analysis.Secondly,the parameters of network node efficiency,shortest path length and node degree centrality were extracted using graph theory analysis.Finally,four indicators of resting-state networks including activeness,network node efficiency,node shortest path length and node degree centrality were compared and analyzed,whose relationships with five cognitive reserve proxies such as education level,early fluid intelligence,sports,leisure activities and socialization level.Results The education level,early fluid intelligence and sports,and the activity correlated positively with the activeness of multi resting-state networks and the node efficiency and node degree centrality of most of cognitive control networks and default mode networks,while negatively with the shortest path length of most of cognitive control networks and default mode networks.Leisure activities,socialization level and sports had negative correlations with the activeness of the resting-state network,and had little effects on the overall topological properties of the functional network.Conclusion Resting-state networks may be affected positively by education level,early fluid intelligence and sports,while negatively by two cognitive reserve proxies including leisure activities and socialization level.[Chinese Medical Equipment Journal,2024,45(1):1-8]
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Texto completo: 1 Índice: WPRIM Idioma: Zh Revista: Chinese Medical Equipment Journal Año: 2024 Tipo del documento: Article
Texto completo: 1 Índice: WPRIM Idioma: Zh Revista: Chinese Medical Equipment Journal Año: 2024 Tipo del documento: Article