Spectral patterns of MEG oscillatory coupling emerge from meta-stable dynamics with small coupling delays

Functional connectivity (FC) is a fundamental mechanism of neural communication, connecting distinct oscillating populations. Oscillatory networks exhibit heterogeneity across frequencies and coupling modes whose origins are not well understood, but have been suggested to involve a complex interplay of critical-like dynamics and structure-function coupling. We here utilized structural connectivity (SC) to tune a whole-brain computational model of delay-coupled damped oscillators near a Hopf bifurcation to match oscillations and FC as observed in resting-state magnetoencephalography (MEG) data.

We assessed two forms of oscillation-based FC from empirical and model data, namely phase synchronization (PS) and amplitude coupling (AC). We found that both oscillations and FC best matched with empirical observations in a meta-stable regime which was characterized by small delays, realistic oscillation lifetimes, and FC with intermediate strength and high variability. How well MEG FC patterns were matched by the model varied between frequency bands and best fits were observed for high-alpha and beta-band networks. These fits could partially, but not fully, be explained by correlations with SC, implicating that both structure-function coupling and critical-like metastable dynamics underlie empirical FC, and the contributions of these mechanisms varies between different frequency bands in MEG data.