Algorithm for sleep scoring in experimental animals based on fast Fourier transform power spectrum analysis of the electroencephalogram

We developed a simple computer-based, sleep scoring algorithm that categorizes three vigilance states of rats and mice as wakefulness, rapid eye movement (REM) sleep and non-rapid eye movement (NREM) sleep, based on fast Fourier transform analyses of an electroencephalogram (EEG) classified in the frequency bands of delta (0.75-4 Hz) and theta (6-10 Hz), and other parameters such as electromyogram (EMG) integral and animal movement. This algorithm is composed of four steps. Step 1, active wakefulness, is specified when activity is detected by monitoring the animal with an infrared locomotion sensor. Step 2, NREM, is decided by an EEG delta power greater than the threshold. Step 3, REM, is specified by a higher EEG theta/(delta + theta) ratio and a lower EMG integral than the threshold values and Step 4, an undefined epoch, is classified as a state of quiet wakefulness. This algorithm was found to be in > 90% agreement with the waveform recognition procedure and decreased processing time to 40 min for 24-h recording data from eight animals. New software, SleepSign ver. 3, was designed to calculate automatically the three threshold values based on percentage of time spent in each sleep stage thus far reported in rodents.