Intrinsic Brain Hub Connectivity Underlies Individual Differences in Spatial Working Memory.
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 fronto-parietal 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.
State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China.
Jin
J
Liu
State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China.
Mingrui
M
Xia
State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China.
Zhengjia
Z
Dai
State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China.
Xiaoying
X
Wang
State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China.
Xuhong
X
Liao
State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China.
Yanchao
Y
Bi
State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China.
Yong
Y
He
D000328:Adult; D001921:Brain / Q000000981:diagnostic imaging / Q000502:physiology*; D063132:Connectome; D005260:Female; D006801:Humans; D007206:Individuality; D008279:Magnetic Resonance Imaging; D008297:Male; D009434:Neural Pathways / Q000000981:diagnostic imaging / Q000502:physiology; D012146:Rest; D065852:Spatial Memory / Q000502:physiology; D055815:Young Adult
connectomics; default mode; functional connectivity; graph-theory; module