A real-time sleep scoring framework for closed-loop sleep manipulation in mice.

A real-time sleep scoring framework for closed-loop sleep manipulation in mice. J Sleep Res. 2021 Jan 06;:e13262 Authors: Huffman D, Ajwad A, Yaghouby F, O'Hara BF, Sunderam S Abstract Subtle changes in sleep architecture can accompany and be symptomatic of many diseases or disorders. In order to probe and understand the complex interactions between sleep and health, the ability to model, track, and modulate sleep in preclinical animal models is vital. While various methods have been described for scoring experimental sleep recordings, few are designed to work in real time - a prerequisite for closed-loop sleep manipulation. In the present study, we have developed algorithms and software to classify sleep in real time and validated it on C57BL/6 mice (n = 8). Hidden Markov models of baseline sleep dynamics were fitted using an unsupervised algorithm to electroencephalogram (EEG) and electromyogram (EMG) data for each mouse, and were able to classify sleep in a manner highly concordant with manual scoring (Cohen's Kappa >75%) up to 3 weeks after model construction. This approach produced reasonably accurate estimates of common sleep metrics (proportion, mean duration, and number of bouts). After construction, the models were used to track sleep in real time and accomplish selective rapid eye movement (REM) sleep restriction by triggering non-invasive somatosensory stimulation. During REM restriction trials, REM bout duration was...
Source: Journal of Sleep Research - Category: Sleep Medicine Authors: Tags: J Sleep Res Source Type: research