The impact of regional heterogeneity in whole-brain dynamics in the presence of oscillations

Zamora-Lopez, Gorka; Montbrio, Ernest; Monge-Asensio, Marti; Vohryzek, Jakub; Ibáñez, Agustín; Yeo, B. T. Thomas

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 meanfield 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. © 2023.

Más información

Título según WOS: The impact of regional heterogeneity in whole-brain dynamics in the presence of oscillations
Título según SCOPUS: The impact of regional heterogeneity in whole-brain dynamics in the presence of oscillations
Título de la Revista: Network Neuroscience
Volumen: 7
Número: 2
Editorial: MIT Press Journals
Fecha de publicación: 2023
Página de inicio: 632
Página final: 660
Idioma: English
DOI:

10.1162/netn_a_00299

Notas: ISI, SCOPUS