气候变化领域集成服务门户(CCPortal): Segregation, integration, and balance of large-scale resting brain networks configure different cognitive abilities

CCPortal

DOI	10.1073/pnas.2022288118
	Segregation, integration, and balance of large-scale resting brain networks configure different cognitive abilities
	Wang R.; Liu M.; Cheng X.; Wu Y.; Hildebrandt A.; Zhou C.
发表日期	2021
ISSN	0027-8424
卷号	118 期号:23
英文摘要	Diverse cognitive processes set different demands on locally segregated and globally integrated brain activity. However, it remains an open question how resting brains configure their functional organization to balance the demands on network segregation and integration to best serve cognition. Here we use an eigenmode-based approach to identify hierarchical modules in functional brain networks and quantify the functional balance between network segregation and integration. In a large sample of healthy young adults (n = 991), we combine the whole-brain resting state functional magnetic resonance imaging (fMRI) data with a mean-filed model on the structural network derived from diffusion tensor imaging and demonstrate that resting brain networks are on average close to a balanced state. This state allows for a balanced time dwelling at segregated and integrated configurations and highly flexible switching between them. Furthermore, we employ structural equation modeling to estimate general and domain-specific cognitive phenotypes from nine tasks and demonstrate that network segregation, integration, and their balance in resting brains predict individual differences in diverse cognitive phenotypes. More specifically, stronger integration is associated with better general cognitive ability, stronger segregation fosters crystallized intelligence and processing speed, and an individual's tendency toward balance supports better memory. Our findings provide a comprehensive and deep understanding of the brain's functioning principles in supporting diverse functional demands and cognitive abilities and advance modern network neuroscience theories of human cognition. © This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY).
英文关键词	Functional brain network; Hierarchical modules; Human cognition; Segregation-integration balance; Structural equation modeling
语种	英语
scopus关键词	adult; article; controlled study; crystallization; diffusion tensor imaging; female; functional magnetic resonance imaging; human; human experiment; human tissue; intelligence; major clinical study; male; memory; nerve cell network; neuroscience; phenotype; processing speed; quantitative analysis; structural equation modeling; young adult
来源期刊	Proceedings of the National Academy of Sciences of the United States of America
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/238899
作者单位	College of Science, Xi'an University of Science and Technology, Xi'an, 710054, China; Department of Physics, Centre for Nonlinear Studies, Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Hong Kong; School of Aerospace Engineering, Xi'an Jiaotong University, Xi'an, 710049, China; State Key Laboratory for Strength and Vibration of Mechanical Structures, Xi'an Jiaotong University, Xi'an, 710049, China; School of Biomedical Engineering, ShanghaiTech University, Shanghai, 201210, China; National Demonstration Center for Experimental Mechanics Education, Xi'an Jiaotong University, Xi'an, 710049, China; Department of Psychology, Carl von Ossietzky Universität Oldenburg, Oldenburg, 26129, Germany; Research Center Neurosensory Science, Carl von Ossietzky Universität Oldenburg, Oldenburg, 26129, Germany; Department of Physics, Zhejiang University, Hangzhou, 310027, China
推荐引用方式 GB/T 7714	Wang R.,Liu M.,Cheng X.,et al. Segregation, integration, and balance of large-scale resting brain networks configure different cognitive abilities[J],2021,118(23).
APA	Wang R.,Liu M.,Cheng X.,Wu Y.,Hildebrandt A.,&Zhou C..(2021).Segregation, integration, and balance of large-scale resting brain networks configure different cognitive abilities.Proceedings of the National Academy of Sciences of the United States of America,118(23).
MLA	Wang R.,et al."Segregation, integration, and balance of large-scale resting brain networks configure different cognitive abilities".Proceedings of the National Academy of Sciences of the United States of America 118.23(2021).