4.6 Article

Topologically Reorganized Connectivity Architecture of Default-Mode, Executive-Control, and Salience Networks across Working Memory Task Loads

期刊

CEREBRAL CORTEX
卷 26, 期 4, 页码 1501-1511

出版社

OXFORD UNIV PRESS INC
DOI: 10.1093/cercor/bhu316

关键词

connectomics; default-mode network; executive-control network; module; salience network

资金

  1. Intramural Research Program of the National Institute on Drug Abuse (NIDA), National Institutes of Health, USA
  2. Natural Science Foundation of China [81030028, 31221003, 81201142]
  3. National Science Fund for Distinguished Young Scholars Grant [81225012]

向作者/读者索取更多资源

The human brain is topologically organized into a set of spatially distributed, functionally specific networks. Of these networks, the default-mode network (DMN), executive-control network (ECN), and salience network (SN) have received the most attention recently for their vital roles in cognitive functions. However, very little is known about whether and how the interactions within and between these 3 networks would be modulated by cognitive demands. Here, we employed graph-based modularity analysis to identify the DMN, ECN, and SN during an N-back working memory (WM) task and further investigated the modulation of intra- and inter-network interactions at different cognitive loads. As the task load elevated, functional connectivity decreased within the DMN while increased within the ECN, and the SN connected more with both the DMN and ECN. Within-network connectivity of the ventral and dorsal posterior cingulate cortex was differentially modulated by cognitive load. Further, the superior parietal regions in the ECN showed increased internetwork connections at higher WM loads, and these increases correlated positively with WM task performance. Together, these findings advance our understanding of dynamic integrations of specialized brain systems in response to cognitive demands and may serve as a baseline for assessing potential disruptions of these interactions in pathological conditions.

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