Sleep Identification Enabled by Supervised Training Algorithms (SIESTA): An Open-Source Platform for Automatic Sleep Staging of Rodent Electrocorticographic and Electromyographic Data

Accurately capturing the temporal distribution of polysomnographic sleep stages is critical for the study of sleep function, regulation, and disorders in higher vertebrates. In laboratory rodents, scoring of electrocorticography (ECoG) and electromyography (EMG) recordings is usually performed manua...

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Bibliographic Details
Published in:	Journal of biological rhythms Vol. 40; no. 4; p. 330
Main Authors:	Beck, Asad I, Caldart, Carlos S, Ben-Hamo, Miriam, Weil, Tenley A, Perez, Jazmine G, Kalume, Franck, Brunton, Bingni W, de la Iglesia, Horacio O, Sanchez, Raymond E A
Format:	Journal Article
Language:	English
Published:	United States 01.08.2025
Subjects:	Algorithms Animals Circadian Rhythm Electrocorticography - methods Electromyography - methods Male Mice Mice, Inbred C57BL Rats Sleep - physiology Sleep Stages - physiology Wakefulness - physiology sleep scoring automated web application machine learning rodent model
ISSN:	1552-4531, 1552-4531
Online Access:	Get more information
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