Assessment of Coupled Phase Oscillators-Based Modeling in Swine Brain Connectome

Area of Science:

• Neuroscience
• Computational Neuroscience
• Systems Neuroscience

Background:

• Linking structural connectivity (SC) to functional connectivity (FC) is a key challenge in network neuroscience.
• Mechanistic models are needed to bridge the gap between brain structure and function.

Purpose of the Study:

• To evaluate a structurally constrained Kuramoto phase-oscillator framework for reproducing resting-state FC.
• To assess the model's sensitivity to traumatic brain injury (TBI) and its longitudinal progression.
• To calibrate model parameters using empirical swine connectome data.

Main Methods:

• Utilized diffusion magnetic resonance imaging (dMRI) and resting-state functional MRI (rs-fMRI) for SC and FC reconstruction in a swine model.
• Employed a joint tuning procedure for natural frequencies and global coupling strength.
• Integrated a Kuramoto model with a Balloon-Windkessel hemodynamic model for phase evolution and FC simulation.

Main Results:

• Achieved significant edge-wise correspondence between simulated and empirical FC (r = 0.61, p < 0.001).
• Demonstrated strong agreement in graph-theoretical metrics like global efficiency and characteristic path length.
• Observed modest reductions in structure-function coupling post-TBI, with no significant differences across injury severities.

Conclusions:

• Optimized Kuramoto models can effectively reproduce key functional network features from structural data.
• The model demonstrates potential for studying brain dynamics and alterations following injury.
• The framework preserves inter-subject variability, highlighting its utility in personalized neuroscience research.