ArticleSleep2022
High-throughput visual assessment of sleep stages in mice using machine learning.
Article in Sleep, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 22 citations in OpenAlex.
- Psilocybin enhances sociability only in altered behavioural state and does not need an awake experience to be effective.Nature communications · 2026Article
- The choice-wide behavioral association study: data-driven identification of interpretable behavioral components.Nature communications · 2026Article
- A tool for high-throughput quantification of sleep-wake transitions in data from noninvasive piezoelectric cage systems.Current research in neurobiology · 2026Article
- Respiratory pauses highlight sleep architecture in mice.Nature communications · 2026Article
- Optimizing Intermediate Representations: A Framework for Low-Cost, High-Accuracy Behavior Quantification.bioRxiv : the preprint server for biology · 2026Article
- REST-a deep learning tool for automated mouse sleep stage classification.Sleep advances : a journal of the Sleep Research Society · 2026Article
- Visual detection of seizures in mice using supervised machine learning.Cell reports methods · 2025Article
- Mineralocorticoid Receptor and Sleep Quality in Chronic Kidney Disease.International journal of molecular sciences · 2024Review
- A Survey on AI-Driven Mouse Behavior Analysis Applications and Solutions.Bioengineering (Basel, Switzerland) · 2024Review
- Highly accurate and precise determination of mouse mass using computer vision.Patterns (New York, N.Y.) · 2024Article
- Prospects of Electrocorticography in Neuropharmacological Studies in Small Laboratory Animals.Brain sciences · 2024Review
- Visual detection of seizures in mice using supervised machine learning.bioRxiv : the preprint server for biology · 2024Article
- SlumberNet: deep learning classification of sleep stages using residual neural networks.Scientific reports · 2024Article
- A convolutional neural network to characterize mouse hindlimb foot strikes during voluntary wheel running.Frontiers in bioengineering and biotechnology · 2023Article
- Synaptic dysfunction connects autism spectrum disorder and sleep disturbances: A perspective from studies in model organisms.Sleep medicine reviews · 2022Review
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
STUDY
objectivesSleep is an important biological process that is perturbed in numerous diseases, and assessment of its substages currently requires implantation of electrodes to carry out electroencephalogram/electromyogram (EEG/EMG) analysis. Although accurate, this method comes at a high cost of invasive surgery and experts trained to score EEG/EMG data. Here, we leverage modern computer vision methods to directly classify sleep substages from video data. This bypasses the need for surgery and expert scoring, provides a path to high-throughput studies of sleep in mice.
methodsWe collected synchronized high-resolution video and EEG/EMG data in 16 male C57BL/6J mice. We extracted features from the video that are time and frequency-based and used the human expert-scored EEG/EMG data to train a visual classifier. We investigated several classifiers and data augmentation methods.
resultsOur visual sleep classifier proved to be highly accurate in classifying wake, non-rapid eye movement sleep (NREM), and rapid eye movement sleep (REM) states, and achieves an overall accuracy of 0.92 ± 0.05 (mean ± SD). We discover and genetically validate video features that correlate with breathing rates, and show low and high variability in NREM and REM sleep, respectively. Finally, we apply our methods to noninvasively detect that sleep stage disturbances induced by amphetamine administration.
conclusionsWe conclude that machine learning-based visual classification of sleep is a viable alternative to EEG/EMG based scoring. Our results will enable noninvasive high-throughput sleep studies and will greatly reduce the barrier to screening mutant mice for abnormalities in sleep.
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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 OpenQuestion graph.