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Get Free AccessPrevious studies investigated the distinct roles played by different cognitive regions and suggested that the patterns of connectivity of these regions are associated with working memory. However, the specific causal mechanism through which the neuronal circuits that involve these brain regions contribute to working memory is still unclear. Here, in a large sample of healthy young adults, we first identified the core working memory regions by linking working memory accuracy to resting-state functional connectivity with the bilateral dorsolateral prefrontal cortex (a principal region in the central-executive network). Then a spectral dynamic causal modeling analysis was performed to quantify the effective connectivity between these regions. Finally, the effective connectivity was correlated with working memory accuracy to characterize the relationship between these connections and working memory performance. We found that the functional connections between the bilateral dorsolateral prefrontal cortex and the dorsal anterior cingulate cortex and between the right dorsolateral prefrontal cortex and the left orbital fronto-insular cortex were correlated with working memory accuracy. Furthermore, the effective connectivity from the dorsal anterior cingulate cortex to the bilateral dorsolateral prefrontal cortex and from the right dorsolateral prefrontal cortex to the left orbital fronto-insular cortex could predict individual differences in working memory. Because the dorsal anterior cingulate cortex and orbital fronto-insular cortex are core regions of the salience network, we inferred that the inter- and causal-connectivity between core regions within the central-executive and salience networks is functionally relevant for working memory performance. In summary, the current study identified the dorsolateral prefrontal cortex-related resting-state effective connectivity underlying working memory and suggests that individual differences in cognitive ability could be characterized by resting-state effective connectivity.
Xiaojing Fang, Yuanchao Zhang, Yuan Zhou, Luqi Cheng, Jin Li, Yulin Wang, Karl Friston, Tianzi Jiang (2016). Resting-State Coupling between Core Regions within the Central-Executive and Salience Networks Contributes to Working Memory Performance. , 10, DOI: https://doi.org/10.3389/fnbeh.2016.00027.
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Type
Article
Year
2016
Authors
8
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.3389/fnbeh.2016.00027
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