Task-induced brain state manipulation improves prediction of individual traits

Abigail S. Greene; Siyuan Gao; Dustin Scheinost; R. Todd Constable

doi:10.1038/s41467-018-04920-3

Nature Communications (Jul 2018)

Task-induced brain state manipulation improves prediction of individual traits

Abigail S. Greene,
Siyuan Gao,
Dustin Scheinost,
R. Todd Constable

Affiliations

Abigail S. Greene: Interdepartmental Neuroscience Program, Yale School of Medicine
Siyuan Gao: Department of Biomedical Engineering, Yale School of Engineering and Applied Science
Dustin Scheinost: Department of Radiology and Biomedical Imaging, Yale School of Medicine
R. Todd Constable: Interdepartmental Neuroscience Program, Yale School of Medicine

DOI: https://doi.org/10.1038/s41467-018-04920-3
Journal volume & issue: Vol. 9, no. 1
pp. 1 – 13

Abstract

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Decoding or predicting cognitive traits from brain activity is an exciting prospect. Here, the authors show that task-based functional connectivity better predicts intelligence-related measures than rest-based connectivity, suggesting that cognitive tasks amplify individual differences in trait-relevant circuitry.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

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