ArticleNetwork neuroscience (Cambridge, Mass.)2024
Neural mass modeling for the masses: Democratizing access to whole-brain biophysical modeling with FastDMF.
Article in Network neuroscience (Cambridge, Mass.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Accurately modeling resting-brain functional connectivity using hypergraph neural field-Fourier deep neural network.Scientific reports · 2026Article
- A multi-frequency whole-brain neural mass model with homeostatic feedback inhibition.PLoS computational biology · 2026Article
- Convergent transcriptomic and connectomic controllers of information integration and its anaesthetic breakdown across mammalian brains.Nature human behaviour · 2026Article
- The biological role of local and global fMRI BOLD signal variability in multiscale human brain organization.Nature communications · 2026Article
- THOI: An efficient and accessible library for computing higher-order interactions enhanced by batch-processing.PloS one · 2026Article
- The structural grammar of integration and competition in the human connectome.Frontiers in computational neuroscience · 2026Article
- Deep learning and whole-brain networks for biomarker discovery: modeling the dynamics of brain fluctuations in resting-state and cognitive tasks.Scientific reports · 2025Article
- A multi-frequency whole-brain neural mass model with homeostatic feedback inhibition.bioRxiv : the preprint server for biology · 2025Article
- Entropy and Complexity Tools Across Scales in Neuroscience: A Review.Entropy (Basel, Switzerland) · 2025Review
- From neurotransmitters to networks: Transcending organisational hierarchies with molecular-informed functional imaging.Neuroscience and biobehavioral reviews · 2023Review
- A whole-brain model of the neural entropy increase elicited by psychedelic drugs.Scientific reports · 2023Article
- Reduced emergent character of neural dynamics in patients with a disrupted connectome.NeuroImage · 2023Article
- Segregation, integration and balance in resting-state brain functional networks associated with bipolar disorder symptoms.Human brain mapping · 2023Article
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9 authors.
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Abstract
Different whole-brain computational models have been recently developed to investigate hypotheses related to brain mechanisms. Among these, the Dynamic Mean Field (DMF) model is particularly attractive, combining a biophysically realistic model that is scaled up via a mean-field approach and multimodal imaging data. However, an important barrier to the widespread usage of the DMF model is that current implementations are computationally expensive, supporting only simulations on brain parcellations that consider less than 100 brain regions. Here, we introduce an efficient and accessible implementation of the DMF model: the FastDMF. By leveraging analytical and numerical advances-including a novel estimation of the feedback inhibition control parameter and a Bayesian optimization algorithm-the FastDMF circumvents various computational bottlenecks of previous implementations, improving interpretability, performance, and memory use. Furthermore, these advances allow the FastDMF to increase the number of simulated regions by one order of magnitude, as confirmed by the good fit to fMRI data parcellated at 90 and 1,000 regions. These advances open the way to the widespread use of biophysically grounded whole-brain models for investigating the interplay between anatomy, function, and brain dynamics and to identify mechanistic explanations of recent results obtained from fine-grained neuroimaging recordings.
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