A large scale, high resolution, automated system for rat sleep staging. I. Methodology and technical aspects.

An automatic rat sleep classification system is described which records and analyses bioelectrical signals from 32 rats over extended periods of time. At present this system is used routinely for the screening of drug effects on sleep. The analysis is based on 3 signals, the parieto-occipital EEG, nuchal EMG and a movement indicator signal. The on-line analysis is done per epoch of 2 sec and involves power spectral analysis of the EEG and rectification and integration of the EMG and movement signals. The automatic sleep staging into 6 stages (active and quiet waking; quiet, deep, pre-REM and REM sleep) is performed off-line. Parameters derived from a discriminant analysis of visually scored tracings of individual rats constitute the basis for the automatic scoring procedure. The movement index is used to discriminate between active and quiet waking, while the use of the EMG level improves the separation of waking and REM sleep. After the construction of hypnograms from these computer scorings a set of parameters can be extracted which characterizes the sleep-waking behavior of each individual rat. These parameters are then used to compare statistically the 2-4 treatment groups which make up each experiment of 32 rats. Experimental validation of the system is reported in an accompanying paper.

A large scale, high resolution, automated system for rat sleep staging. II. Validation and application.

An automated rat sleep staging system was used to describe sleep-waking behaviour in a large number of rats. The computer scorings were validated by visual analysis of a limited set of data by two human raters and the agreement varied between 82 and 100% for homogeneous segments of the different sleep-waking stages. The automated system proved to be very consistent in view of the small variation in placebo values over 110 experiments. The data show that classification of rat sleep waking behaviour into 6 different stages is both advisable and feasible. The experiments further show that rat age (over a range from 0.5 to 2 years) does not greatly affect rat sleep-waking behaviour.