White matter disconnection of left multiple demand network is associated with post-lesion deficits in cognitive control

Cognitive control modulates other cognitive functions to achieve internal goals and is important for adaptive behavior. Cognitive control is enabled by the neural computations distributed over cortical and subcortical areas. However, due to technical challenges in recording neural activity from the...

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Published inNature communications Vol. 14; no. 1; pp. 1740 - 12
Main Authors Jiang, Jiefeng, Bruss, Joel, Lee, Woo-Tek, Tranel, Daniel, Boes, Aaron D.
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 29.03.2023
Nature Publishing Group
Nature Portfolio
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ISSN2041-1723
2041-1723
DOI10.1038/s41467-023-37330-1

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Summary:Cognitive control modulates other cognitive functions to achieve internal goals and is important for adaptive behavior. Cognitive control is enabled by the neural computations distributed over cortical and subcortical areas. However, due to technical challenges in recording neural activity from the white matter, little is known about the anatomy of white matter tracts that coordinate the distributed neural computations that support cognitive control. Here, we leverage a large sample of human patients with focal brain lesions (n = 643) and investigate how lesion location and connectivity profiles account for variance in cognitive control performance. We find that lesions in white matter connecting left frontoparietal regions of the multiple demand network reliably predict deficits in cognitive control performance. These findings advance our understanding of the white matter correlates of cognitive control and provide an approach for incorporating network disconnection to predict deficits following lesions. The anatomy of white matter tracts which coordinate the computations of cognitive control are not well understood. Here, the authors show that lesions in white matter connecting left frontoparietal regions are associated with deficits in cognitive control performance.
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ISSN:2041-1723
2041-1723
DOI:10.1038/s41467-023-37330-1