Information transmission velocity-based dynamic hierarchical brain networks

Area of Science:

• Neuroscience
• Cognitive Science
• Brain Imaging

Background:

• The brain's hierarchical organization and information propagation mechanisms during high-level cognition remain incompletely understood.
• Existing methods lack the precision to dynamically map information flow across cortical networks.

Purpose of the Study:

• To develop and apply a novel method for quantifying information transmission velocity (ITV) in the human brain.
• To map the cortical information transmission velocity network (ITVN) and explore brain information processing mechanisms.
• To investigate the neural basis of cognitive processes like P300 generation and inter-individual variability.

Main Methods:

• Combined electroencephalogram (EEG) and diffusion tensor imaging (DTI) to quantify ITV.
• Developed a novel scheme for mapping the cortical ITV network (ITVN).
• Applied the ITVN mapping to MRI-EEG data during P300 event-related potential generation.

Main Results:

• Revealed hierarchical organization of the ITVN with four distinct modules.
• Demonstrated bottom-up and top-down interactions within the ITVN during P300 generation.
• Identified high information transmission velocity between visual and attention regions, linked to myelination.
• Attributed inter-individual P300 variability to differences in information transmission efficiency.

Conclusions:

• The developed ITV method effectively quantifies information propagation efficiency in the brain.
• ITVN mapping provides insights into hierarchical information processing and cognitive function.
• Transmission velocity differences may offer new perspectives on cognitive decline in neurodegenerative diseases.