ArticleScientific reports2023
Discriminating rapid eye movement sleep from wakefulness by analyzing high frequencies from single-channel EEG recordings in mice.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 10 citations in OpenAlex.
- Improving Function and Quality of Life in Patients with Chronic Neck Pain, Tension-Type Headache, and Forward Head Posture: The Role of Eyeball Exercise and Cervical Stabilization Programs.Medical science monitor : international medical journal of experimental and clinical research · 2024Trial
- Role of gamma-aminobutyric acid-ergic neurons in the thalamic reticular nucleus in regulating sleep-wake cycles in mice treated with acupuncture for insomnia.Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan · 2026Article
- Early-life maternal care is required for the typical development of calming responses to back stroking.Communications biology · 2026Article
- Sleep and circadian rhythm disruptions in animal models of temporal lobe epilepsy.Frontiers in neuroscience · 2026Review
- Characterizing transition state in mouse vigilance with electroencephalogram-electromyogram hypnodensity.Sleep advances : a journal of the Sleep Research Society · 2026Article
- The Application of an Ultra-Thin, High-Density μECoG Array in Dissecting Caffeine-Induced Cortical Dynamics in Mice.Sensors (Basel, Switzerland) · 2025Article
- Open-Source Algorithm for Automated Vigilance State Classification Using Single-Channel Electroencephalogram in Rodents.Sensors (Basel, Switzerland) · 2025Article
- Isoflurane anesthesia and sleep deprivation trigger delayed and selective sleep alterations.Scientific reports · 2024Article
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Authors and funding
7 authors at 3 institutions in 3 countries.
Funding
Abstract
Rapid eye movement sleep (REMS) is characterized by the appearance of fast, desynchronized rhythms in the cortical electroencephalogram (EEG), similar to wakefulness. The low electromyogram (EMG) amplitude during REMS distinguishes it from wakefulness; therefore, recording EMG signal seems to be imperative for discriminating between the two states. The present study evaluated the high frequency components of the EEG signal from mice (80-500 Hz) to support REMS detection during sleep scoring without an EMG signal and found a strong positive correlation between waking and the average power of 80-120 Hz, 120-200 Hz, 200-350 Hz and 350-500 Hz. A highly negative correlation was observed with REMS. Furthermore, our machine learning approach demonstrated that simple EEG time-series features are enough to discriminate REMS from wakefulness with sensitivity of roughly 98 percent and specificity of around 92 percent. Interestingly, assessing only the higher frequency bands (200-350 Hz as well as 350-500 Hz) gives significantly greater predictive power than assessing only the lower end of the EEG frequency spectrum. This paper proposes an approach that can detect subtle changes in REMS reliably, and future unsupervised sleep-scoring approaches could greatly benefit from it.
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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.