ArticleNature communications2025
Using an ordinary differential equation model to separate rest and task signals in fMRI.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Neural population models for EEG: From Canonical models to alternative model structures.PLoS computational biology · 2026Article
- Task-induced topological and geometrical changes in whole-brain dynamics predict cognitive individual differences.bioRxiv : the preprint server for biology · 2026Article
- System identification and surrogate data analyses imply approximate Gaussianity and non-stationarity of resting-brain dynamics.bioRxiv : the preprint server for biology · 2026Article
- A novel spatiotemporal decomposition and identification of sparse equations for human brain deformation.Scientific reports · 2026Article
- The turbulent brain: Modeling vortex interactions for understanding human cognition.Network neuroscience (Cambridge, Mass.) · 2026Article
- Stable individualized brain computing model informed by spatiotemporal co-activity patterns.PLoS computational biology · 2025Article
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Authors and funding
8 authors.
Funding
Abstract
Cortical activity results from the interplay between network-connected regions that integrate information and stimulus-driven processes originating from sensory motor networks responding to specific tasks. Separating the information due to each of these components has been challenging, and the relationship as measured by fMRI in each of these cases Rest (network) and Task (stimulus-driven) remains a significant open question in the study of large-scale brain dynamics. In this study, we develop a network ordinary differential equation (ODE) model using advanced system identification tools to analyze fMRI data from both rest and task conditions. We demonstrate that task-specific ODEs are essentially a subset of rest-specific ODEs across four different tasks from the Human Connectome Project. By assuming that task activity is a relative complement of rest activity, our model significantly improves predictions of reaction times on a trial-by-trial basis, leading to a 9% increase in explanatory power (R
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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 Socratic graph.