Intrinsic Brain Hub Connectivity Underlies Individual Differences in Spatial Working Memory

被引:38
|
作者
Liu, Jin
Xia, Mingrui [1 ,2 ]
Dai, Zhengjia
Wang, Xiaoying
Liao, Xuhong
Bi, Yanchao
He, Yong
机构
[1] Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing 100875, Peoples R China
[2] Beijing Normal Univ, IDG McGovern Inst Brain Res, Beijing 100875, Peoples R China
基金
北京市自然科学基金; 中国国家自然科学基金;
关键词
connectomics; default mode; functional connectivity; graph-theory; module; STATE FUNCTIONAL CONNECTIVITY; GLOBAL SIGNAL; LOW-FREQUENCY; DEFAULT-MODE; FLUID INTELLIGENCE; NEURONAL-ACTIVITY; NETWORK HUBS; ORGANIZATION; FLUCTUATIONS; REVEALS;
D O I
10.1093/cercor/bhw317
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Spatial working memory (SWM) is an important component of working memory and plays an essential role in driving high-level cognitive abilities. Recent studies have demonstrated that individual SWM is associated with global brain communication. However, whether specific network nodal connectivity, such as brain hub connectivity, is involved in individual SWM performances remains largely unknown. Here, we collected resting-state fMRI (R-fMRI) data from a large group of 130 young healthy participants and evaluated their SWM performances. A voxel-wise whole-brain network analysis approach was employed to study the relationship between the nodal functional connectivity strength (FCS) and the SWM behavioral scores and to further estimate the participation of brain hubs in individual SWM. We showed significant associations between nodal FCS and SWM performance primarily in the default mode, visual, dorsal attention, and frontoparietal systems. Moreover, over 41% of these nodal regions were identified as brain network hubs, and these hubs' FCS values contributed to 57% of the variance of the individual SWM performances that all SWM-related regions could explain. Collectively, our findings highlight the cognitive significance of the brain network hubs in SWM, which furthers our understanding of how intrinsic brain network architectures underlie individual differences in SWM processing.
引用
收藏
页码:5496 / 5508
页数:13
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