ArticleNature biomedical engineering2024
Macroscopic resting-state brain dynamics are best described by linear models.
Article in Nature biomedical engineering, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.
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Who cites it
62 citing papers in PubMed, 114 citations in OpenAlex.
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- State-dependent signal flow hierarchy in the human cerebral cortex.Nature neuroscience · 2026Article
- On the Optimal Temporal Resolution for Information Representation in Neural Activity: A Theoretical Analysis.bioRxiv : the preprint server for biology · 2026Article
- Minimizing Stochastic Complexity with Ridge Regression.Entropy (Basel, Switzerland) · 2026Article
- Input-dependent directionality of interactions between cortical areas.bioRxiv : the preprint server for biology · 2026Article
- Metric validation for detection of delayed and directed coupling.Journal of neural engineering · 2026Article
- The influence of nonlinear resonance on human cortical oscillations.Communications biology · 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
- Normative Modeling of Static and Dynamic Functional Connectivity.bioRxiv : the preprint server for biology · 2026Article
- Brain energetic landscapes shape state dysregulation in major depressive disorder: a morphological network controllability perspective.Translational psychiatry · 2026Article
- Competitive interactions shape mammalian brain network dynamics and computation.Nature neuroscience · 2026Article
- System identification and surrogate data analyses imply approximate Gaussianity and non-stationarity of resting-brain dynamics.bioRxiv : the preprint server for biology · 2026Article
- Hierarchical whole-brain modeling of critical synchronization dynamics in the human brain.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Altered functional connectivity is associated with Repeatable Battery for the Assessment of Neuropsychological Status across the dementia spectrum.Journal of the International Neuropsychological Society : JINS · 2026Article
- Towards an informational account of interpersonal coordination.Nature reviews. Neuroscience · 2026Review
- The network architecture of general intelligence in the human connectome.Nature communications · 2026Article
- Controllability of morphometric network colocalize with underlying neurobiology in major depression.Psychological medicine · 2026Article
2 more citing papers are in PubMed but not listed here.
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
Abstract
It is typically assumed that large networks of neurons exhibit a large repertoire of nonlinear behaviours. Here we challenge this assumption by leveraging mathematical models derived from measurements of local field potentials via intracranial electroencephalography and of whole-brain blood-oxygen-level-dependent brain activity via functional magnetic resonance imaging. We used state-of-the-art linear and nonlinear families of models to describe spontaneous resting-state activity of 700 participants in the Human Connectome Project and 122 participants in the Restoring Active Memory project. We found that linear autoregressive models provide the best fit across both data types and three performance metrics: predictive power, computational complexity and the extent of the residual dynamics unexplained by the model. To explain this observation, we show that microscopic nonlinear dynamics can be counteracted or masked by four factors associated with macroscopic dynamics: averaging over space and over time, which are inherent to aggregated macroscopic brain activity, and observation noise and limited data samples, which stem from technological limitations. We therefore argue that easier-to-interpret linear models can faithfully describe macroscopic brain dynamics during resting-state conditions.
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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.