A Deep Learning Approach for Automated Sleep-Wake Scoring in Pre-Clinical Animal Models.
Journal:
Journal of neuroscience methods
Published Date:
Mar 2, 2020
Abstract
BACKGROUND: Experimental investigation of sleep-wake dynamics in animals is an important part of pharmaceutical development. Typically, it involves recording of electroencephalogram, electromyogram, locomotor activity, and electrooculogram. Visual identification, or scoring, of the sleep-wake states from these recordings is time-consuming. We sought to develop software for automated sleep-wake scoring capable of processing large databases of multi-channel signal recordings in a range of species.