ArticlePloS one2019
Robust, automated sleep scoring by a compact neural network with distributional shift correction.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 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
61 citing papers in PubMed.
- Simplified method for EEG recordings in mice.MethodsX · 2026Article
- A male-biased hypothalamic circuit modulates postmating sleep suppression in mice.Science advances · 2026Article
- Propofol-Facilitated Recovery Sleep Modulates Cognitive Function via Slow Oscillation-Spindle Coupling After Acute Sleep Deprivation in Rats.CNS neuroscience & therapeutics · 2026Article
- Tryptamine from wake-active monoaminergic neurons regulates sleep homeostasis.Nature neuroscience · 2026Article
- Cell-type targeted CRISPR/Cas9 Clock knockdown in mouse VTA dopamine neurons alter sleep, behavior, and cellular excitability.bioRxiv : the preprint server for biology · 2026Article
- Hypothalamic MCH neurons links tau pathology to sleep disruption.bioRxiv : the preprint server for biology · 2026Article
- Development of an automated REM sleep deprivation device for mice in neuroscience research.HardwareX · 2026Article
- Role of Preoptic Area γ-Aminobutyric Acid-mediated Neurons in Distinctly Regulating Sleep and Rousability during Dexmedetomidine Sedation in Mice.Anesthesiology · 2026Article
- A minimally invasive EEG recording method in mice using thin needle electrodes.bioRxiv : the preprint server for biology · 2026Article
- Heart rate and sleep history encode ultradian REM sleep timing.Current biology : CB · 2026Article
- Neural network architectures and normalization techniques for automated sleep stage classification using rodent EEG and EMG signals.PloS one · 2026Article
- A Novel Functional Ingredient Derived From a Mixture of Mulberry (Oxidative medicine and cellular longevity · 2026Article
- REST-a deep learning tool for automated mouse sleep stage classification.Sleep advances : a journal of the Sleep Research Society · 2026Article
- VTA dopaminergic neuronal activity during NREM sleep is modulated by learning and facilitates motor memory consolidation.Science advances · 2025Article
- Convergent Control of NREM Sleep and Anesthesia by Prefrontal Layer 5 Extratelencephalic Neurons.Research square · 2025Article
- Article
- An early surge of norepinephrine along brainstem pathways drives sensory-evoked awakening.Science advances · 2025Article
- Lemborexant ameliorates tau-mediated sleep loss and neurodegeneration in males in a mouse model of tauopathy.Nature neuroscience · 2025Article
- Abrupt and Gradual Changes in Neuronal Processing upon Falling Asleep and Awakening.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- A Role for δ Subunit-Containing GABAThe Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
1 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
5 authors.
Funding
Abstract
Studying the biology of sleep requires the accurate assessment of the state of experimental subjects, and manual analysis of relevant data is a major bottleneck. Recently, deep learning applied to electroencephalogram and electromyogram data has shown great promise as a sleep scoring method, approaching the limits of inter-rater reliability. As with any machine learning algorithm, the inputs to a sleep scoring classifier are typically standardized in order to remove distributional shift caused by variability in the signal collection process. However, in scientific data, experimental manipulations introduce variability that should not be removed. For example, in sleep scoring, the fraction of time spent in each arousal state can vary between control and experimental subjects. We introduce a standardization method, mixture z-scoring, that preserves this crucial form of distributional shift. Using both a simulated experiment and mouse in vivo data, we demonstrate that a common standardization method used by state-of-the-art sleep scoring algorithms introduces systematic bias, but that mixture z-scoring does not. We present a free, open-source user interface that uses a compact neural network and mixture z-scoring to allow for rapid sleep scoring with accuracy that compares well to contemporary methods. This work provides a set of computational tools for the robust automation of sleep scoring.
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.