State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China.
Cereb Cortex. 2017 Dec 1;27(12):5496-5508. doi: 10.1093/cercor/bhw317.
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.
空间工作记忆（SWM）是工作记忆的重要组成部分，对驱动高级认知能力起着至关重要的作用。最近的研究表明，个体的 SWM 与大脑整体的连通性有关。然而，特定的网络节点连通性（如大脑枢纽连通性）是否参与个体的 SWM 表现仍知之甚少。在这里，我们从一大群 130 名年轻健康的参与者中收集了静息态 fMRI（R-fMRI）数据，并评估了他们的 SWM 表现。采用全脑网络分析方法，研究了节点功能连接强度（FCS）与 SWM 行为评分之间的关系，并进一步估计了大脑枢纽在个体 SWM 中的参与程度。我们发现，节点 FCS 与 SWM 表现之间存在显著关联，主要集中在默认模式、视觉、背侧注意和额顶叶系统。此外，超过 41%的这些节点区域被鉴定为大脑网络枢纽，这些枢纽的 FCS 值对个体 SWM 表现的 57%的方差有贡献，而所有与 SWM 相关的区域可以解释其中的 57%。总之，我们的研究结果强调了大脑网络枢纽在 SWM 中的认知意义，进一步加深了我们对内在大脑网络结构如何影响 SWM 处理个体差异的理解。
