Interaction of Functional Brain Networks Is Associated With k-Clique Percolation in the Human Structural Connectome

Area of Science:

• Neuroscience
• Network Science
• Computational Biology

Background:

• The human structural connectome exhibits complex community organization with overlapping communities.
• This organization is linked to brain function and cognitive processes.
• Understanding the principles governing this organization is crucial for neuroscience.

Purpose of the Study:

• To explore connectivity properties within human connectome networks.
• To investigate the role of clique percolation in structural brain organization.
• To model the emergence of high-order clique percolation and its relation to functional subnetworks.

Main Methods:

• Analysis of human connectome networks to identify connectivity properties.
• Application of k-clique percolation at high orders to characterize the structural connectome.
• Development of a novel network formation model incorporating phase transitions and connection length constraints.

Main Results:

• The human structural connectome is characterized by anomalously high-order k-clique percolation.
• This organization results in high local connectivity density while maintaining overall network sparsity.
• A direct relationship was found between functional subnetwork interactions and structural clique cluster formation.

Conclusions:

• Percolating clique clusters act as distributed bridges connecting interacting functional subnetworks.
• Common structural connections are vital for maintaining the integrity of structural communities.
• Individual-specific connections introduce variability in functional subnetwork interactions.