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Between-module functional connectivity of the salient ventral attention network and dorsal attention network is associated with motor inhibition

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  • Howard Muchen Hsu
  • Zai-Fu Yao
  • Kai Hwang
  • Shulan Hsieh

Abstract

The ability to inhibit motor response is crucial for daily activities. However, whether brain networks connecting spatially distinct brain regions can explain individual differences in motor inhibition is not known. Therefore, we took a graph-theoretic perspective to examine the relationship between the properties of topological organization in functional brain networks and motor inhibition. We analyzed data from 141 healthy adults aged 20 to 78, who underwent resting-state functional magnetic resonance imaging and performed a stop-signal task along with neuropsychological assessments outside the scanner. The graph-theoretic properties of 17 functional brain networks were estimated, including within-network connectivity and between-network connectivity. We employed multiple linear regression to examine how these graph-theoretical properties were associated with motor inhibition. The results showed that between-network connectivity of the salient ventral attention network and dorsal attention network explained the highest and second highest variance of individual differences in motor inhibition. In addition, we also found those two networks span over brain regions in the frontal-cingulate-parietal network, suggesting that these network interactions are also important to motor inhibition.

Suggested Citation

  • Howard Muchen Hsu & Zai-Fu Yao & Kai Hwang & Shulan Hsieh, 2020. "Between-module functional connectivity of the salient ventral attention network and dorsal attention network is associated with motor inhibition," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-15, December.
  • Handle: RePEc:plo:pone00:0242985
    DOI: 10.1371/journal.pone.0242985
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    1. Roger Guimerà & Luís A. Nunes Amaral, 2005. "Functional cartography of complex metabolic networks," Nature, Nature, vol. 433(7028), pages 895-900, February.
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    1. Macauley Smith Breault & Pierre Sacré & Zachary B. Fitzgerald & John T. Gale & Kathleen E. Cullen & Jorge A. González-Martínez & Sridevi V. Sarma, 2023. "Internal states as a source of subject-dependent movement variability are represented by large-scale brain networks," Nature Communications, Nature, vol. 14(1), pages 1-20, December.

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