Exploring the transmission of cognitive task information through optimal brain pathways

Area of Science:

• Cognitive Neuroscience
• Computational Neuroscience
• Network Science

Background:

• Complex human cognition relies on large-scale information processing within the brain.
• Current models often assume neural communication follows the shortest path in brain networks.

Purpose of the Study:

• To investigate whether the shortest path is the optimal route for cognitive information transmission.
• To challenge the prevailing shortest path assumption in brain network models.

Main Methods:

• Utilized a large-scale activity flow mapping framework.
• Compared the predictive performance of different network communication strategies, including shortest path, direct path, search information, path ensembles, and navigation.

Main Results:

• Shortest path routing was significantly outperformed by direct path routing in activity flow prediction.
• Shortest path routing was superior to other strategies like search information, path ensembles, and navigation.
• Shortest path outperformed direct path only when physical distance and asymmetric routing were considered.

Conclusions:

• The shortest path assumption in brain network models is challenged by empirical findings.
• Cognitive task information routing is influenced by the spatial and functional constraints of brain networks.