ArticleNature communications2019
Discovery of key whole-brain transitions and dynamics during human wakefulness and non-REM sleep.
Article in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 112 papers, 2 of them syntheses that pooled it.
What it found
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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.
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Who cites it
112 citing papers in PubMed, 2 syntheses or guidelines pooled it, 266 citations in OpenAlex.
- Sleep dysregulation in ADHD children: a systematic review and meta-analysis.Psychological medicine · 2025Pooled it
- Effect-size seed-based d mapping of resting-state fMRI for persistent insomnia disorder.Sleep & breathing = Schlaf & Atmung · 2020Pooled it
- Awakening: Predicting external stimulation to force transitions between different brain states.Proceedings of the National Academy of Sciences of the United States of America · 2019Trial
- Electroconvulsive therapy shifting brain dynamics toward more adaptive and integrated states in treatment-resistant depression based on a hidden markov model.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2026Article
- A comprehensive framework for statistical testing of brain dynamics.Nature protocols · 2026Review
- Modeled Long-Term Effects of Psilocybin on Dynamic Activity and Effective Connectivity of Fronto-Striatal-Thalamic Circuits.Human brain mapping · 2026Article
- Sleep EEG foundation models reveal within-stage microstructure that improves health screening beyond traditional stages.Research square · 2026Article
- Exploring Neurofunctional Phase Transition Patterns in Autism Spectrum Disorder via Thermodynamics Parameters.Entropy (Basel, Switzerland) · 2026Article
- Dynamic Brain State Alterations in Narcolepsy: A Hidden Markov Model Approach to Thalamocortical Instability and Symptom-Specific Neural Correlates.Brain and behavior · 2026Article
- Unveiling state-specific neural dynamics in migraine with and without depressive symptom: a hidden Markov model and interpretable machine learning approach.The journal of headache and pain · 2026Article
- Human brain zero: uncovering the lowest neural state for consciousness engineering.Frontiers in neuroscience · 2026Article
- Multimodal neuroimaging of locus coeruleus-default mode network connectivity for predicting dexmedetomidine response in chronic insomnia disorder.Frontiers in psychiatry · 2026Article
- Circuit-level dynamics and propagation of slow wave activity modulate their interplay during the awakening process.iScience · 2025Article
- Brain-wide resting-state fMRI network dynamics elicited by activation of single thalamic input.Nature communications · 2025Article
- Sleep neuroimaging: Review and future directions.Journal of sleep research · 2025Review
- Falling asleep follows a predictable bifurcation dynamic.Nature neuroscience · 2025Article
- Article
- Neural correlates and dynamical brain states of creative insight in a spatial problem task.Scientific reports · 2025Article
- Seeing Is Craving: Neural Dynamics of Appetitive Processing During Food-Cue Video Watching and Its Impact on Obesity.Nutrients · 2025Article
- Exploratory GABAa-informed control network modulates hyperarousal brain dynamics in chronic insomnia.Communications biology · 2025Article
52 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 7 institutions in 8 countries.
Funding
Abstract
The modern understanding of sleep is based on the classification of sleep into stages defined by their electroencephalography (EEG) signatures, but the underlying brain dynamics remain unclear. Here we aimed to move significantly beyond the current state-of-the-art description of sleep, and in particular to characterise the spatiotemporal complexity of whole-brain networks and state transitions during sleep. In order to obtain the most unbiased estimate of how whole-brain network states evolve through the human sleep cycle, we used a Markovian data-driven analysis of continuous neuroimaging data from 57 healthy participants falling asleep during simultaneous functional magnetic resonance imaging (fMRI) and EEG. This Hidden Markov Model (HMM) facilitated discovery of the dynamic choreography between different whole-brain networks across the wake-non-REM sleep cycle. Notably, our results reveal key trajectories to switch within and between EEG-based sleep stages, while highlighting the heterogeneities of stage N1 sleep and wakefulness before and after sleep.
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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.