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Journal Article

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

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Deco,  Gustavo
Center for Brain and Cognition, University Pompeu Fabra, Barcelona, Spain;
Department of Information and Communication Technologies, University Pompeu Fabra, Barcelona, Spain;
Catalan Institution for Research and Advanced Studies (ICREA), University Pompeu Fabra, Barcelona, Spain;
Department Neuropsychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
School of Psychological Sciences, Monash University, Melbourne, Australia;

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Fulltext (public)

SanzPerl_ZamoraLopez_2023.pdf
(Publisher version), 2MB

Supplementary Material (public)

SanzPerl_ZamoraLopez_2023_Suppl.pdf
(Supplementary material), 378KB

Citation

Sanz Perl, Y., Zamora-Lopez, G., Montbrió, E., Monge-Asensio, M., Vohryzek, J., Fittipaldi, S., et al. (2023). The impact of regional heterogeneity in whole-brain dynamics in the presence of oscillations. Network Neuroscience, 7(2), 632-660. doi:10.1162/netn_a_00299.


Cite as: https://hdl.handle.net/21.11116/0000-000D-6801-D
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.