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Available from: Charles Czeisler, Oct 06, 2015
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    • "The physiological component of this subjective feeling has not yet been precisely defined in scientific terms, and the question of what might be a reliable physiological marker of sleepiness remains controversial (e.g., Dinges, 2004; Horne, 2004). Simple, user-friendly and efficient methods of assessing sleepiness are greatly needed for future progress of fundamental investigations in the field of chronobiological and sleep research (Mullington et al., 2011; Quan et al., 2011). "
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    • "Besides, they cannot be regarded as satisfactory indicators of sleepiness , because they measure somewhat different characteristics , i.e., sleepability and performance, respectively. Therefore, the development of easy to attain physiological markers of sleepiness is one of the most important tasks of modern investigations in the fields of chronobiology and sleep science (Czeisler, 2011; Mullington et al., 2011; Quan, 2011; Quan et al., 2011). "
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    ABSTRACT: Although circadian and sleep research has made extraordinary progress in the recent years, one remaining challenge is the objective quantification of sleepiness in individuals suffering from sleep deprivation, sleep restriction, and excessive somnolence. The major goal of the present study was to apply principal component analysis to the wake electroencephalographic (EEG) spectrum in order to establish an objective measure of sleepiness. The present analysis was led by the hypothesis that in sleep-deprived individuals, the time course of self-rated sleepiness correlates with the time course score on the 2nd principal component of the EEG spectrum. The resting EEG of 15 young subjects was recorded at 2-h intervals for 3250h. Principal component analysis was performed on the sets of 16 single-Hz log-transformed EEG powers (116Hz frequency range). The time course of self-perceived sleepiness correlated strongly with the time course of the 2nd principal component score, irrespective of derivation (frontal or occipital) and of analyzed section of the 7-min EEG record (2-min section with eyes open or any of the five 1-min sections with eyes closed). This result indicates the possibility of deriving an objective index of physiological sleepiness by applying principal component analysis to the wake EEG spectrum. (Author correspondence: [email protected] /* */)
    Chronobiology International 04/2012; 29(4):509-22. DOI:10.3109/07420528.2012.667029 · 3.34 Impact Factor
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    ABSTRACT: 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.
    Somnologie - Schlafforschung und Schlafmedizin 06/2012; 16(2). DOI:10.1007/s11818-012-0561-1
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