The first and second principal components of the EEG spectrum as the correlates of sleepiness

Purpose Quantitative EEG measurement of sleepiness must be regarded both as fundamentally and practically important. In a search for the markers of physiological sleepiness, we tested whether the time course of self-perceived sleepiness/alertness correlates with the time courses of scores on principal components of the EEG spectrum. Subjects and methods The resting EEG was recorded in 15 healthy subjects with 2 h intervals in frontal and occipital derivations for the last 32–50 h of 44–61 h wakefulness. The correlation coefficients were calculated to test associations of the time course of self-perceived sleepiness/alertness with the time courses of spectral powers and scores on the two largest principal components of the EEG spectrum. Results and conclusion The results demonstrate that objective markers of sleepiness can be derived by means of principal component analysis of the EEG spectrum. A score on the 2nd principal component appears to be the most reliable correlate of sleepiness, because it exhibits the fastest decline at the boundary between wakefulness and sleep. A score on the 1st principal component was characterized by a decline before sleep onset followed by a rapid rise after it. These two scores were interpreted as the pure representatives of the wake and sleep drives, respectively, while spectral powers in separate frequency bands appear to reflect simultaneous influences of both drives.