Sleep scoring made easy—Semi-automated sleep analysis software and manual rescoring tools for basic sleep research in mice

Abstract

Studying sleep behavior in animal models demands clear separation of vigilance states. Pure manual scoring is time-consuming and commercial scoring software is costly. We present a LabVIEW-based, semi-automated scoring routine using recorded EEG and EMG signals. This scoring routine is • designed to reliably assign the vigilance/sleep states wakefulness (WAKE), non-rapid eye movement sleep (NREMS) and rapid eye movement sleep (REMS) to defined EEG/EMG episodes. • straightforward to use even for beginners in the field of sleep research. • freely available upon request. Chronic recordings from mice were used to design and evaluate the scoring routine consisting of an artifact-removal, a scoring- and a rescoring routine. The scoring routine processes EMG and different EEG frequency bands. Amplitude-based thresholds for EEG and EMG parameters trigger a decision tree assigning each EEG episode to a defined vigilance/sleep state automatically. Using the rescoring routine individual episodes or particular state transitions can be re-evaluated manually. High agreements between auto-scored and manual sleep scoring could be shown for experienced scorers and for beginners quickly and reliably. With small modifications to the software, it can be easily adapted for sleep analysis in other animal models.

Keywords

• Semi-automated sleep scoring