Abstract

Large variability exists across brain regions in health and disease, considering their cellular and molecular composition, connectivity, and function. Large-scale whole-brain models comprising coupled brain regions provide insights into the underlying dynamics that shape complex patterns of spontaneous brain activity. In particular, biophysically grounded mean-field whole-brain models in the asynchronous regime were used to demonstrate the dynamical consequences of including regional variability. Nevertheless, the role of heterogeneities when brain dynamics are supported by synchronous oscillating state, which is a ubiquitous phenomenon in brain, remains poorly understood. Here, we implemented two models capable of presenting oscillatory behavior with different levels of abstraction: a phenomenological Stuart-Landau model and an exact mean-field model. The fit of these models informed by structural- to functional-weighted MRI signal (T1w/T2w) allowed us to explore the implication of the inclusion of heterogeneities for modeling resting-state fMRI recordings from healthy participants. We found that disease-specific regional functional heterogeneity imposed dynamical consequences within the oscillatory regime in fMRI recordings from neurodegeneration with specific impacts on brain atrophy/structure (Alzheimer's patients). Overall, we found that models with oscillations perform better when structural and functional regional heterogeneities are considered, showing that phenomenological and biophysical models behave similarly at the brink of the Hopf bifurcation. Author Summary Significant progress has been made in understanding the effects of regional heterogeneity on whole-brain dynamics. With imaging technologies, the number of high-resolution reference maps of brain structure and function has been increased, and whole-brain computational models have provided a suitable avenue to investigate the mechanisms supporting the relations between these maps and whole-brain dynamics. Here, we investigate the role of the heterogeneities when synchronous behavior is present in brain dynamics, which we could represent by models capable of oscillating in the presence of a Hopf bifurcation. We found that models with oscillations more faithfully reproduce empirical properties when structural and functional regional heterogeneities are considered, showing that both phenomenological and biophysical models behave similarly at the brink of the Hopf bifurcation.