Structuring the inter-individual variation in waking EEG can help to discriminate between the objective markers of sleep debt and sleep pressure

Abstract

Modern society is characterized by the steadily increasing demand and desire for wakefulness at all hours of the day. Research in the fields of sleep physiology and chronophysiology can offer instruments enabling the identification of people with and without advantageous traits, such as little need for sleep, decreased sleepiness associated with sleep loss, and rapid adaptation to changes in the workrest schedule. These instruments can also help to quantify the severity of sleep-wake disorders (i.e., excessive daytime sleepiness) and the effects of their treatment. However, inter-individual differences in sleep need, vulnerability to sleep loss, and circadian adaptation remain scientifically understudied and are rarely theoretically and practically considered [19]. At present, it remains largely unknown what may underlie and predict sleep-wake related traits, what relationship these traits may have to each other, and what functional significance may be associated with these traits [20].Van Dongen and Dinges [19] emphasized the importance of three independent parameters for any model aimed at predicting reduced alertness and performance in the conditions of sleep loss and sleep disruption. These include (1) the timing and/or rate of circadian adjustment (i.e., circadian phase), (2) the amount of sleep required per day (i.e., sleep need), and (3) the rate of impairment per hour of sleep loss (i.e., vulnerability to sleep deprivation). There is solid evidence for substantial and clearly distinguishable interindividual variation in each of these three parameters. The differences between individuals are often characterized by within-individual stability (i.e., replicability) and robustness (i.e., insensitivity to experimental manipulation). These features suggest that the inter-individual differences represent systematic trait-like variability (see [18,20] for details). Understanding the basis of this variability may yield new insight into sleep-wake regulation and sleep-wake pathology [20].Agreement exists with respect to the markers of the individual circadian phase (i.e., it can be determined by tracing daily variations in core body temperature, secretion of melatonin and cortisol), but, to date, there is no consensus on the biological markers of sleep need and vulnerability to impairment from lack of sleep. However, it is possible to identify these markers by quantification of the response of brain wave activity to sleep deprivation. The analysis of changes in spectral characteristics of the electroencephalogram (EEG) is regarded as the physiological gold standard for identifying shifts along the alertness-drowsiness continuum [1,2,9,17]. It was demonstrated that sleep loss selectively modulates the spectral power densities of the EEG signal recorded either during prolonged wakefulness [3,4] or during subsequent recovery sleep [4,5,12]. Moreover, the results of numerous studies indicate that the changes in oscillatory brain activity within certain frequency ranges can provide reliable indexes of the reduced alertn...

Principal component structure of wake-sleep transition

“…Both our previous [17,19,20] and present findings on principal component structure of EEG spectra provide strong evidence for the generality of the loading patterns of the three largest principal components of spectrum variance (. Fig.…”

“…In particular the studies employing EEG spectral analysis found that some patterns of EEG spectra might serve as markers of sleep pressure because they respond to the increase in sleepiness from sleep deprivation and other factors ( [7]). However, there is no agreement on gold standard indices for tracking changes in sleep pressure or for quantifying transitions from active waking to sleepiness ( [18,19,20] for more detail).…”

“…This study was prompted by our previous findings on principal component structure of wake EEG spectra [19,20]. It has been demonstrated that the traditional descriptions of power densities in conventional frequency bands [18] might be less informative than a more meaningful and parsimonious description of the universal three principal component structure of wake EEG spectra and that the two largest components of this structure can reflect sleep debt and sleep pressure caused by morning sleep restriction and the following night time sleep loss, respectively [19,20]. If replicated and extended on the structure of transition between wake and sleep EEG spectra, this can lead to the development of a new approach aimed at a theoretically meaningful, parsimonious, and quantitative description of alternations between substates along a sleepwake continuum.…”

What were “owls” doing in our ancestral photoperiodic environment? Chronobiological account for the evolutionary advantage of nocturnal lifestyle

“…The protocol of the experimental study has been extensively described in the previously published papers (Putilov et al 2009(Putilov et al , 2010. The experiments were conducted during early fall months (August andSeptember, 2006-2008) in accordance with the ethical standards laid down in the Declaration of Helsinki.…”

Three dimensions of individual variation in phase angle between sleep timing and timing of nocturnal rise of the feeling of sleepiness

“…The results on objective (i.e. EEG) indexes of alertness-sleepiness were reported elsewhere (Putilov et al 2009(Putilov et al , 2010. Participants also completed several questionnaires at the time intervals between the measurements of EEG and performance.…”