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Resting-state brain information flow predicts cognitive flexibility in humans

Chén, Oliver Y., Cao, Hengyi, Reinen, Jenna, Qian, Tianchen, Gou, Jiangtao, Phan, Huy, Vos, Maarten De, Cannon, Tyrone (2019) Resting-state brain information flow predicts cognitive flexibility in humans. Scientific reports, 9 . p. 3879. ISSN 2045-2322. (doi:10.1038/s41598-019-40345-8)

Abstract

The human brain is a dynamic system, where communication between spatially distinct areas facilitates complex cognitive functions and behaviors. How information transfers between brain regions and how it gives rise to human cognition, however, are unclear. In this article, using resting-state functional magnetic resonance imaging (fMRI) data from 783 healthy adults in the Human Connectome Project (HCP) dataset, we map the brain’s directed information flow architecture through a Granger-Geweke causality prism. We demonstrate that the information flow profiles in the general population primarily involve local exchanges within specialized functional systems, long-distance exchanges from the dorsal brain to the ventral brain, and topdown exchanges from the higher-order systems to the primary systems. Using an information flow map discovered from 550 subjects, the individual directed information flow profiles can significantly predict cognitive flexibility scores in 233 novel individuals. Our results provide evidence for directed information network architecture in the cerebral cortex, and suggest that features of the information flow configuration during rest underpin cognitive ability in humans.

Item Type: Article
DOI/Identification number: 10.1038/s41598-019-40345-8
Divisions: Faculties > Sciences > School of Computing > Data Science
Depositing User: Huy Phan
Date Deposited: 20 Feb 2019 17:12 UTC
Last Modified: 15 Jan 2020 12:03 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/72658 (The current URI for this page, for reference purposes)
Phan, Huy: https://orcid.org/0000-0003-4096-785X
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