Empirical evidence for structural balance theory in functional brain networks

Area of Science:

• Neuroscience
• Network Science
• Computational Biology

Background:

• Structural balance theory, applied to social networks, posits stable balanced triads and unstable imbalanced triads.
• This theory's core assumptions lack empirical validation within brain network studies.
• Understanding higher-order interactions is crucial for neural function and dysfunction.

Purpose of the Study:

• To empirically validate structural balance theory in brain networks.
• To analyze the temporal dynamics of triadic configurations in the brain.
• To introduce dynamic measures for characterizing triadic brain interactions.

Main Methods:

• Utilized resting-state fMRI data from the Human Connectome Project.
• Defined and analyzed triad lifetime and absolute peak energy for triadic configurations.
• Compared findings with surrogate null models to confirm non-random patterns.

Main Results:

• Balanced triads exhibited significantly longer lifetimes and higher peak energy than imbalanced triads.
• Imbalanced triads were more transient and weaker, indicating structural conflict.
• The joint distribution of lifetime and energy revealed two clusters aligning with strong structural balance theory.

Conclusions:

• Provided empirical validation for structural balance theory in brain networks.
• Introduced dynamic measures (lifetime, peak energy) for brain triad analysis.
• Established a framework for studying higher-order interaction dynamics and brain network stability.