ArticleScience advances2023
Characterization of regional differences in resting-state fMRI with a data-driven network model of brain dynamics.
Article in Science advances, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
36 citing papers in PubMed.
- Siibra: a software tool suite for realizing a Multilevel Human Brain Atlas from complex data resources.Nature methods · 2026Article
- Neural population models for EEG: From Canonical models to alternative model structures.PLoS computational biology · 2026Article
- Accurately modeling resting-brain functional connectivity using hypergraph neural field-Fourier deep neural network.Scientific reports · 2026Article
- A digital twin approach for simultaneous reconstruction of brain anatomy and dynamics from neural data.PLOS digital health · 2026Article
- Comparing Dynamical Models Through Diffeomorphic Vector Field Alignment.Neural computation · 2026Article
- Linearizing and Forecasting: A Reservoir Computing Route to Digital Twins of the Brain.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Task-induced topological and geometrical changes in whole-brain dynamics predict cognitive individual differences.bioRxiv : the preprint server for biology · 2026Article
- Resting-state EEG alpha-BOLD coupling spatially follows cortical cell-type and receptor gradients.bioRxiv : the preprint server for biology · 2026Article
- Competitive interactions shape mammalian brain network dynamics and computation.Nature neuroscience · 2026Article
- A novel spatiotemporal decomposition and identification of sparse equations for human brain deformation.Scientific reports · 2026Article
- The role of connectivity for the degeneracy of the brain's resting state dynamics.Journal of computational neuroscience · 2026Article
- Artificial intelligence as a surrogate brain: bridging neural dynamical models and data.National science review · 2026Review
- AI-enabled multimodal neuroimaging for neurotransmitter mapping in normal aging and age-related disease.Frontiers in aging neuroscience · 2026Review
- The turbulent brain: Modeling vortex interactions for understanding human cognition.Network neuroscience (Cambridge, Mass.) · 2026Article
- Article
- Observing hidden neuronal states in experiments.PLoS computational biology · 2025Article
- Stable individualized brain computing model informed by spatiotemporal co-activity patterns.PLoS computational biology · 2025Article
- Deep oscillatory neural network.Scientific reports · 2025Article
- Revealing excitation-inhibition imbalance in Alzheimer's disease using multiscale neural model inversion of resting-state functional MRI.Communications medicine · 2025Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Model-based data analysis of whole-brain dynamics links the observed data to model parameters in a network of neural masses. Recently, studies focused on the role of regional variance of model parameters. Such analyses however necessarily depend on the properties of preselected neural mass model. We introduce a method to infer from the functional data both the neural mass model representing the regional dynamics and the region- and subject-specific parameters while respecting the known network structure. We apply the method to human resting-state fMRI. We find that the underlying dynamics can be described as noisy fluctuations around a single fixed point. The method reliably discovers three regional parameters with clear and distinct role in the dynamics, one of which is strongly correlated with the first principal component of the gene expression spatial map. The present approach opens a novel way to the analysis of resting-state fMRI with possible applications for understanding the brain dynamics during aging or neurodegeneration.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.