Discriminating rapid eye movement sleep from wakefulness by analyzing high frequencies from single-channel EEG recordings in mice.

Rapid eye movement sleep (REMS) is characterized by the appearance of fast, desynchronized rhythms in the cortical electroencephalogram (EEG), similar to wakefulness. The low electromyogram (EMG) amplitude during REMS distinguishes it from wakefulness; therefore, recording EMG signal seems to be imperative for discriminating between the two states. The present study evaluated the high frequency components of the EEG signal from mice (80-500 Hz) to support REMS detection during sleep scoring without an EMG signal and found a strong positive correlation between waking and the average power of 80-120 Hz, 120-200 Hz, 200-350 Hz and 350-500 Hz.

A New Spike Sorting Algorithm Based on Continuous Wavelet Transform and Investigating Its Effect on Improving Neural Decoding Accuracy.

Spike sorting is an essential step in extracting neuronal discharge patterns which help to decode different activities in the neural system. Therefore, improving the spike sorting accuracy can improve neural decoding performance subsequently. Although many methods are suggested for spike sorting, few studies have evaluated their effect on neural decoding performance.