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Dynamic reconfiguration of human brain networks across altered states of consciousness

文献类型：期刊论文

作者Liu, Haiyang8; Hu, Ke5,6,7; Peng, Yingjie3,4; Tian, Xiaohan4; Wang, Meng5,6,7; Ma, Bo8; Wu, Youxuan8; Sun, Wanchen8; Liu, Bing2,3; Li, Ang1,4
刊名BEHAVIOURAL BRAIN RESEARCH
出版日期2022-02-15
卷号419页码:11
关键词Functional magnetic resonance imaging Multilayer networks Dynamic functional connectivity Consciousness Sedation Dexmedetomidine
ISSN号0166-4328
DOI10.1016/j.bbr.2021.113685
通讯作者Li, Ang(al@ibp.ac.cn) ; Han, Ruquan(ruquan.han@ccmu.edu.cn)
英文摘要Consciousness is supported by rich neuronal dynamics to orchestrate behaviors and conscious processing can be disrupted by general anesthetics. Previous studies suggested that dynamic reconfiguration of large-scale functional network is critical for learning and higher-order cognitive function. During altered states of consciousness, how brain functional networks are dynamically changed and reconfigured at the whole-brain level is still unclear. To fill this gap, using multilayer network approach and functional magnetic resonance imaging (fMRI) data of 21 healthy subjects, we investigated the dynamic network reconfiguration in three different states of consciousness: wakefulness, dexmedetomidine-induced sedation, and recovery. Applying time-varying community detection algorithm, we constructed multilayer modularity networks to track and quantify dynamic interactions among brain areas that span time and space. We compared four high-level network features (i.e., switching, promiscuity, integration, and recruitment) derived from multilayer modularity across the three conditions. We found that sedation state is primarily characterized by increased switching rates as well as decreased integration, representing a whole-brain pattern with higher modular dynamics and more fragmented communication; such alteration can be mostly reversed after the recovery of consciousness. Thus, our work can provide additional insights to understand the modular network reconfiguration across different states of consciousness and may provide some clinical implications for disorders of consciousness.
WOS关键词RESTING-STATE ; FUNCTIONAL CONNECTIVITY ; TIME ; MODULARITY ; THALAMUS ; CORTEX ; SLEEP
资助项目Institutional Review Board of Beijing Tiantan Hospital, China[KY2017-036-02] ; Beijing Natural Science Foundation Program, China[7192055] ; Strategic Priority Research Program (B) of the Chinese Academy of Sciences, China[XDB32020200]
WOS研究方向Behavioral Sciences ; Neurosciences & Neurology
语种英语
WOS记录号WOS:000754453200003
出版者ELSEVIER
资助机构Institutional Review Board of Beijing Tiantan Hospital, China ; Beijing Natural Science Foundation Program, China ; Strategic Priority Research Program (B) of the Chinese Academy of Sciences, China
源URL[http://ir.ia.ac.cn/handle/173211/47912]  
专题自动化研究所_脑网络组研究中心
通讯作者Li, Ang; Han, Ruquan
作者单位1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
2.Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing 100875, Peoples R China
3.Shandong Normal Univ, Sch Informat, Jinan 250013, Peoples R China
4.Chinese Acad Sci, Inst Biophys, State Key Lab Brain & Cognit Sci, Beijing 100101, Peoples R China
5.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
6.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
7.Chinese Acad Sci, Brainnetome Ctr, Beijing 100190, Peoples R China
8.Capital Med Univ, Beijing Tiantan Hosp, Dept Anesthesiol, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Liu, Haiyang,Hu, Ke,Peng, Yingjie,et al. Dynamic reconfiguration of human brain networks across altered states of consciousness[J]. BEHAVIOURAL BRAIN RESEARCH,2022,419:11.
APA Liu, Haiyang.,Hu, Ke.,Peng, Yingjie.,Tian, Xiaohan.,Wang, Meng.,...&Han, Ruquan.(2022).Dynamic reconfiguration of human brain networks across altered states of consciousness.BEHAVIOURAL BRAIN RESEARCH,419,11.
MLA Liu, Haiyang,et al."Dynamic reconfiguration of human brain networks across altered states of consciousness".BEHAVIOURAL BRAIN RESEARCH 419(2022):11.

入库方式： OAI收割

来源：自动化研究所

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