Long-term intensive gymnastic training induced changes in intra- and inter-network functional connectivity: an independent component analysis

被引:44
作者
Huang, Huiyuan [1 ,2 ]
Wang, Junjing [1 ,2 ]
Seger, Carol [1 ,2 ,3 ,4 ]
Lu, Min [5 ]
Deng, Feng [1 ,2 ]
Wu, Xiaoyan [1 ,2 ]
He, Yuan [1 ,2 ]
Niu, Chen [1 ,2 ]
Wang, Jun [6 ,7 ]
Huang, Ruiwang [1 ,2 ]
机构
[1] South China Normal Univ, Sch Psychol, IBRR, Ctr Study Appl Psychol, Guangzhou 510631, Guangdong, Peoples R China
[2] South China Normal Univ, MRI Ctr, Key Lab Mental Hlth & Cognit Sci Guangdong Prov, Guangzhou 510631, Guangdong, Peoples R China
[3] Colorado State Univ, Dept Psychol, Ft Collins, CO 80523 USA
[4] Colorado State Univ, Program Mol Cellular & Integrat Neurosci, Ft Collins, CO 80523 USA
[5] Chinese Acad Sci, Key Lab Mental Hlth, Inst Psychol, Beijing 100101, Peoples R China
[6] Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing 100875, Peoples R China
[7] Beijing Normal Univ, IDG McGovern Inst Brain Res, Beijing 100875, Peoples R China
基金
中国国家自然科学基金;
关键词
Neuroplasticity; World class gymnasts; Independent component analysis (ICA); Resting-state networks (RSNs); Intra-network functional connectivity; Inter-network functional connectivity; RESTING-STATE NETWORKS; WORLD-CLASS GYMNASTS; HUMAN BRAIN; BASAL GANGLIA; VISUAL-CORTEX; MOTOR-SKILLS; DEFAULT-MODE; QUANTITATIVE METAANALYSIS; MULTISENSORY INTEGRATION; EXTRASTRIATE CORTEX;
D O I
10.1007/s00429-017-1479-y
中图分类号
R602 [外科病理学、解剖学]; R32 [人体形态学];
学科分类号
100101 ;
摘要
Long-term intensive gymnastic training can induce brain structural and functional reorganization. Previous studies have identified structural and functional network differences between world class gymnasts (WCGs) and non-athletes at the whole-brain level. However, it is still unclear how interactions within and between functional networks are affected by long-term intensive gymnastic training. We examined both intra- and inter-network functional connectivity of gymnasts relative to non-athletes using resting-state fMRI (R-fMRI). R-fMRI data were acquired from 13 WCGs and 14 non-athlete controls. Group-independent component analysis (ICA) was adopted to decompose the R-fMRI data into spatial independent components and associated time courses. An automatic component identification method was used to identify components of interest associated with resting-state networks (RSNs). We identified nine RSNs, the basal ganglia network (BG), sensorimotor network (SMN), cerebellum (CB), anterior and posterior default mode networks (aDMN/pDMN), left and right fronto-parietal networks (lFPN/rFPN), primary visual network (PVN), and extrastriate visual network (EVN). Statistical analyses revealed that the intra-network functional connectivity was significantly decreased within the BG, aDMN, lFPN, and rFPN, but increased within the EVN in the WCGs compared to the controls. In addition, the WCGs showed uniformly decreased inter-network functional connectivity between SMN and BG, CB, and PVN, BG and PVN, and pDMN and rFPN compared to the controls. We interpret this generally weaker intra- and inter-network functional connectivity in WCGs during the resting state as a result of greater efficiency in the WCGs' brain associated with long-term motor skill training.
引用
收藏
页码:131 / 144
页数:14
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