Resting-state brain information flow predicts cognitive flexibility in humans.

Area of Science:

• Neuroscience
• Cognitive Science
• Network Science

Background:

• The human brain's complex cognitive functions rely on communication between distinct regions.
• Understanding information transfer and its link to cognition remains a challenge.

Purpose of the Study:

• To map the brain's directed information flow architecture using Granger-Geweke causality.
• To investigate the relationship between resting-state information flow and cognitive flexibility.

Main Methods:

• Utilized resting-state functional magnetic resonance imaging (fMRI) data from the Human Connectome Project (HCP) dataset (N=783).
• Applied Granger-Geweke causality analysis to map directed information flow.
• Validated predictive power of information flow profiles on cognitive flexibility in a separate cohort.

Main Results:

• Identified primary information flow patterns: local, dorsal-to-ventral, and top-down exchanges.
• Individual directed information flow profiles significantly predicted cognitive flexibility scores.
• Established evidence for a directed information network architecture in the cerebral cortex.

Conclusions:

• Resting-state directed information flow architecture is a fundamental feature of the human brain.
• Information flow patterns during rest are associated with cognitive abilities, specifically cognitive flexibility.
• This framework offers insights into the neural basis of human cognition.