Article

Somnotate: A probabilistic sleep stage classifier for studying vigilance state transitions

2021-10-08

Abstract excerpt

Electrophysiological recordings from freely behaving animals are a widespread and powerful mode of investigation in sleep research. These recordings generate large amounts of data that require sleep stage annotation (polysomnography), in which the data is parcellated according to three vigilance states: awake, rapid eye movement (REM) sleep, and non-REM (NREM) sleep. Manual and computational annotation methods cur...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 7ed50270-e732-5961-9fc0-b92177714bac
DOI: 10.1101/2021.10.06.463356

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Somnotate: A probabilistic sleep stage classifier for studying vigilance state transitionsDOI 10.1101/2021.10.06.463356Read

Nyx: a flexible framework for sleep scoring across species, lifespan and modalitiesSemantic proximity Read

Lack of Consensus for Manual Mouse Sleep Scoring Limits Implementation of Automatic Deep Learning ModelsSemantic proximity Read

Pupil dynamics-derived sleep stage classification of a head-fixed mouse using a recurrent neural networkSemantic proximity Read

Sleep-Deep-Net learns sleep wake scoring from the end-user and completes each record in their styleSemantic proximity Read

Automated Sleep Stage and Event Detection Algorithms Using Quality-Controlled PSG AnnotationsSemantic proximity Read

A novel unsupervised analysis of electrophysiological signals reveals new sleep substages in mice.Semantic proximity Read

GI-SleepNet: A Highly Versatile Image-based Sleep Classification using a Deep Learning AlgorithmSemantic proximity Read

Temporally Continuous Automated Sleep-Wake Classification Using Deep LearningSemantic proximity Read

Multimodal sleep stage classification and label-free abnormality scoring in mid-to-older adultsSemantic proximity Read

Postprocessing-Enhanced Machine Learning for Reliable Real-Time Sleep Staging in Closed-Loop NeuromodulationSemantic proximity Read

Local REM sleep-N1-wake sleep stage mixing in narcolepsy type 1Semantic proximity Read

Machine learning approaches reveal subtle differences in breathing and sleep fragmentation in Phox2b-derived astrocytes ablated mice.Semantic proximity Read