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Nat Commun. 2018 Jul 18;9(1):2807. doi: 10.1038/s41467-018-04920-3.

Task-induced brain state manipulation improves prediction of individual traits.

Author information

1
Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, 06520, CT, USA. abigail.greene@yale.edu.
2
Department of Biomedical Engineering, Yale School of Engineering and Applied Science, New Haven, 06520, CT, USA.
3
Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, 06520, CT, USA.
4
Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, 06520, CT, USA.
5
Department of Neurosurgery, Yale School of Medicine, New Haven, 06520, CT, USA.

Abstract

Recent work has begun to relate individual differences in brain functional organization to human behaviors and cognition, but the best brain state to reveal such relationships remains an open question. In two large, independent data sets, we here show that cognitive tasks amplify trait-relevant individual differences in patterns of functional connectivity, such that predictive models built from task fMRI data outperform models built from resting-state fMRI data. Further, certain tasks consistently yield better predictions of fluid intelligence than others, and the task that generates the best-performing models varies by sex. By considering task-induced brain state and sex, the best-performing model explains over 20% of the variance in fluid intelligence scores, as compared to <6% of variance explained by rest-based models. This suggests that identifying and inducing the right brain state in a given group can better reveal brain-behavior relationships, motivating a paradigm shift from rest- to task-based functional connectivity analyses.

PMID:
30022026
PMCID:
PMC6052101
DOI:
10.1038/s41467-018-04920-3
[Indexed for MEDLINE]
Free PMC Article

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