ArticleNetwork neuroscience (Cambridge, Mass.)2023
The impact of regional heterogeneity in whole-brain dynamics in the presence of oscillations.
Article in Network neuroscience (Cambridge, Mass.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Biophysically inspired mean-field model of neuronal populations driven by ion-exchange mechanisms.eLife · 2026Article
- Spatially structured heterogeneity shapes large-scale cortical dynamics in a model of the human cortex.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Mechanistic corticostriatal circuit model predicts learning-dependent fMRI dynamics and individual reward bias in humans.bioRxiv : the preprint server for biology · 2026Article
- Competitive interactions shape mammalian brain network dynamics and computation.Nature neuroscience · 2026Article
- A Virtual Clinical Trial of Psychedelics to Treat Patients With Disorders of Consciousness.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- TVB C++: A Fast and Flexible Back-End for The Virtual Brain.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- The turbulent brain: Modeling vortex interactions for understanding human cognition.Network neuroscience (Cambridge, Mass.) · 2026Article
- Computational whole-body-exposome models for global precision brain health.Nature communications · 2025Article
- Noradrenaline and acetylcholine shape functional connectivity organization of NREM substages: An empirical and simulation study.PLoS computational biology · 2025Article
- Understanding the high-order network plasticity mechanisms of ultrasound neuromodulation.PLoS computational biology · 2025Article
- Mapping global brain reconfigurations following local targeted manipulations.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
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- A synergetic turn in cognitive neuroscience of brain diseases.Trends in cognitive sciences · 2024Review
- The BrainLat project, a multimodal neuroimaging dataset of neurodegeneration from underrepresented backgrounds.Scientific data · 2023Article
- Visual deep learning of unprocessed neuroimaging characterises dementia subtypes and generalises across non-stereotypic samples.EBioMedicine · 2023Article
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13 authors.
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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.
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