Development of a rule-based automatic five-sleep-stage scoring method for rats

Abstract

Background Sleep problem or disturbance often exists in pain or neurological/psychiatric diseases. However, sleep scoring is a time-consuming tedious labor. Very few studies discuss the 5-stage (wake/NREM1/NREM2/transition sleep/REM) automatic fine analysis of wake–sleep stages in rodent models. The present study aimed to develop and validate an automatic rule-based classification of 5-stage wake–sleep pattern in acid-induced widespread hyperalgesia model of the rat. Results The overall agreement between two experts’ consensus and automatic scoring in the 5-stage and 3-stage analyses were 92.32% ( κ = 0.88) and 94.97% ( κ = 0.91), respectively. Standard deviation of the accuracy among all rats was only 2.93%. Both frontal–occipital EEG and parietal EEG data showed comparable accuracies. The results demonstrated the performance of the proposed method with high accuracy and reliability. Subtle changes exhibited in the 5-stage wake–sleep analysis but not in the 3-stage analysis during hyperalgesia development of the acid-induced pain model. Compared with existing methods, our method can automatically classify vigilance states into 5-stage or 3-stage wake–sleep pattern with a promising high agreement with sleep experts. Conclusions In this study, we have performed and validated a reliable automated sleep scoring system in rats. The classification algorithm is less computation power, a high robustness, and consistency of results. The algorithm can be implanted into a versatile wireless portable monitoring system for real-time analysis in the future.

Sleep scoring in rodents: Criteria, automatic approaches and outstanding issues

“…Although the method was unique and used a quite advanced system in classification, which might represent the future of sleep classification in rodents, they only managed to classify the three main sleep stages in rodents (W, N and R). On the other hand, Wei et al (2019) managed to detect five sleep stages in rats by using a decision tree automated sleep scoring method that was based on different roles considering several features of the signal. The former study was the only recent study during that was able to identify two NREM states and the TS state.…”

Neonatal Ketamine Alters High-Frequency Oscillations and Synaptic Plasticity in the Subiculum But Does not Affect Sleep Macrostructure in Adolescent Rats

“…N1 stages were characterized by low frequency, high amplitude EEG and minimal signal in the EMG ( Figure 1C). N2 was differentiated from N1 in that it contained a larger proportion of lower frequency oscillations (1-4 Hz) in at least 50% or more of the epoch (Neckelmann and Ursin, 1993;Wei et al, 2019; Figure 1C). We confirmed the presence of low frequency oscillations by dominance of slow and delta power in the epoch's power spectral plot.…”

Neonatal exposure to a neuroactive steroid alters low-frequency oscillations in the subiculum

“…N2 was differentiated from N1 by a substantial amount (at least 50% of the epoch) containing delta (1–4 Hz) oscillations. 24 –26 This was confirmed by the slow (<1 Hz) and delta (1–4 Hz) power being dominant in the epoch’s spectral plot. Finally, REM sleep was categorized by having a very similar visual appearance (high frequency) to that of wake in the cortical EEG, but the EMG signal is flatlined, and when the spectral plot is looked at theta waves (4–8 Hz) are the prominent waves found (Figure 1(D)).…”