Resting-state Brain Information Flow Predicts Cognitive Flexibility in Humans.

Details

Ressource 1Download: Granger.pdf (3433.20 [Ko])
State: Public
Version: Final published version
License: CC BY 4.0
Serval ID
serval:BIB_EB738CFEE321
Type
Article: article from journal or magazin.
Collection
Publications
Title
Resting-state Brain Information Flow Predicts Cognitive Flexibility in Humans.
Journal
Scientific reports
Author(s)
Chén Oliver Y, Cao Hengyi, Reinen Jenna M, Qian Tianchen, Gou Jiangtao, Phan Huy, de Vos Maarten, Cannon Tyrone D
ISSN
2045-2322 (Electronic)
ISSN-L
2045-2322
Publication state
Published
Issued date
07/03/2019
Peer-reviewed
Oui
Volume
9
Number
1
Pages
3879
Language
english
Notes
Publication types: Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
Publication Status: epublish
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 top-down 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.
Keywords
Adult, Brain/diagnostic imaging, Brain/physiology, Cognition/physiology, Connectome, Female, Humans, Magnetic Resonance Imaging, Male, Models, Neurological, Models, Psychological, Rest, Signal Processing, Computer-Assisted, Young Adult
Pubmed
Web of science
Open Access
Yes
Create date
11/01/2024 19:05
Last modification date
18/01/2024 16:05
Usage data