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Updated: Jun 5, 2026

Establishing a Device for Sleep Deprivation in Mice
Published on: September 22, 2023
Development of an automated REM sleep deprivation device for mice in neuroscience research
Ruilin Yang1, Wyatt D Morse1, Peng Zhong1
1Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, NE 68106, USA.
Abstract:
Rapid eye movement (REM) sleep deprivation paradigms are widely used to investigate the functional role of REM sleep, yet conventional methods often disrupt natural housing conditions and introduce stress-related confounds. Here, we present an open-source, home-cage-compatible system for automated REM sleep deprivation in mice that integrates physiological monitoring with real-time closed-loop motor control. Electroencephalography (EEG) and electromyography (EMG) signals are acquired using an Open Ephys acquisition board coupled to an Intan RHD-series headstage (Intan Technologies, USA). Real-time REM detection relies solely on EEG-derived spectral features, whereas offline brain-state annotation is performed using combined EEG and EMG recordings. The real-time classifier discriminates REM, wake, and non-rapid eye movement (NREM) states with accuracies of 88.6%, 80.4%, and 89.1%, respectively. Upon REM detection, the Open Ephys board outputs a Transistor-Transistor Logic (TTL) signal to a servo motor controller (Maxon ESCON 50/5), which drives a gently moving platform to selectively disrupt REM episodes. During a continuous 48 h deprivation protocol, REM sleep was robustly suppressed. At 24 h, the baseline-to-deprivation ratio for REM was approximately 15.9x, while wake and NREM ratios were approximately 0.66x and 1.46x, respectively. Sustained REM suppression remained evident at 48 h (∼7.9x), demonstrating stable closed-loop performance. All hardware design files and source code are publicly available.
