The yin and yang of two opponent processes of sleep-wake regulation: Sex-associated differences in the spectral EEG markers of the drives for sleep and wake.

Although objectively measured characteristics of sleep efficiency and quality were found to be better in women than men, women more frequently than men suffer from poor or insufficient or non-restorative sleep. We explored this apparent paradox by testing the sex-associated differences in electroencephalographic (EEG) indicators of two opponent processes of sleep-wake regulation, the drives for sleep and wake. We tried to provide empirical support for the hypothesis that a stronger women's sleep drive can explain better objective characteristics of sleep quality in women than men, while a stronger women's wake drive can be an explanation of a higher frequency of sleep-related complaints in women than men. To our knowledge, this was the first attempt to examine the associations of sex with scores on the 1st and 2nd principal components of the EEG spectrum that can serve as objective spectral EEG markers of the opponent drives for sleep and wake, respectively. The particular prediction was that, in women compared to men, not only the 1st principal component score but also the 2nd principal component score could be higher (i.e. both drives could be stronger). In a sample of 80 university students (40 females), the EEG signals were recorded during 160 afternoon napping attempts (50 min or longer). The difference between male and female students in sleep latencies did not reach a statistically significant level. In accordance with our prediction, both principal component scores were found to be higher in female than in male students irrespective of sleep stage. It is likely that the influence of the wake drive is entirely overlooked in the polysomnographic studies due to the predominant contribution of the indicators of the sleep drive to the conventional objective characteristics of sleep quality. Therefore, a stronger women's sleep drive can be an explanation of women's better sleep quality in the results of polysomnographic studies. On the other hand, if a stronger women's wake drive can influence the perception of their sleep quality, this can explain their more frequent sleep-related complaints.

Evening chronotype, insufficient weekday sleep, and weekday-weekend gap in sleep times: What is really to blame for a reduction in self-perceived health among university students?

The association of insufficient sleep with reduced self-perceived health was previously well established. Moreover, it was sometimes shown that the indicators of poorer health were significantly related to chronotype and weekday-weekend gaps in sleep timing and duration. It remains to be elucidated, however, whether chronotype and these gaps can contribute to the reduced health self-ratings independently from shortened sleep duration or, alternatively, their relationship with health can be simply explained by their association with insufficient sleep on weekdays. In an online survey, we tested whether the self-rated health of university students can be predicted by several individual characteristics of the sleep-wake cycles, such as chronotype, weekday and weekend sleep times, weekday-weekend gap in sleep times, sleepability and wakeability at different times of the day, etc. Responses to a question about general health and to items of several questionnaires for chronobiological assessment were collected from smartphones of 1582 university students (mean age ± standard deviation was 19.5 ± 1.7 y). The results of regression analyses suggested that lower odds of having good self-rated health were significantly associated with an earlier weekday risetime, a later weekday bedtime, and, consequently, a shorter weekday time in bed. After accounting for weekday sleep, self-rated health showed significant association with neither chronotype nor weekday-weekend differences in sleep duration and timing. Besides, the adverse health effects of reduced weekday sleep were independent from the significant adverse effects of several other individual sleep-wake characteristics including poorer nighttime sleepability and lower daytime wakeability. We concluded that university students perceive the negative health impacts of losing sleep by waking up early on weekdays irrespective of their night sleep quality and daytime level of alertness. Their chronotype and weekday-weekend difference in sleep times might not be among significant contributors to this perception. It is of practical importance to consider the reduction of weekday sleep losses among the interventions aimed at preventing sleep and health problems.

When early and late risers were left to their own devices: six distinct chronotypes under "lockdown" remained dissimilar on their sleep and health problems.

Under national "lockdown," the habitual late risers need not wake up early, and, similarly to the early risers, they don't lose much sleep on weekdays. We tested whether, despite a decrease in weekday sleep loss, the difference between distinct chronotypes in health and sleep problems persisted during "lockdown." Two online surveys were conducted from 10th to 20th of May, 2020 and 2021, one of them after 6 non-working weeks and another after 14 working weeks (during and after "lockdown," respectively). Participants were students of the same grade at the same university department (572 and 773, respectively). The self-assessments included the Single-Item Chronotyping (SIC) designed for self-choosing chronotype among several their short descriptions and several questions about general health, mood state, outdoors and physical activity, and sleep concerns. The results suggested that the responses to each of the questions were not randomly distributed over 6 distinct chronotypes. Such a nonrandomness was identified within each of three pairs of these chronotypes, evening vs. morning types (with a rising throughout the day vs. a falling level of alertness, respectively), afternoon vs. napping types (with a peak vs. a dip of alertness in the afternoon, respectively), and vigilant vs. lethargic types (with the levels of alertness being permanently high vs. low, respectively). Morning, afternoon, and vigilant types reported healthier sleep/mood/behavior/habits than three other types. The most and the least healthy sleep/mood/behavior/habits were reported by morning and evening types, respectively. These relationships with health and sleep problems and the frequencies of 6 chronotypes remained unchanged after "lockdown." Such results, in particular, suggested that the association of evening types with poorer health and sleep might not be attributed to a big amount of weekday sleep loss. The accounting for this association might help in designing interventions purposed on reduction of sleep and health problems.

Linking stages of non-rapid eye movement sleep to the spectral EEG markers of the drives for sleep and wake.

The conventional staging classification reduces all patterns of sleep polysomnogram signals to a small number of yes-or-no variables labeled wake or a stage of sleep (e.g., W, N1, N2, N3, and R for wake, the first, second, and third stages of non-rapid eye movement sleep and rapid eye movement sleep, respectively). However, the neurobiological underpinnings of such stages remained to be elucidated. We tried to evaluate their link to scores on the first and second principal components of the EEG spectrum (1PCS and 2PCS), the markers of two major groups of promoters/inhibitors of sleep/wakefulness delineated as the drives for sleep and wake, respectively. On two occasions, polysomnographic records were obtained from 69 university students during 50-min afternoon naps and 30-s stage epochs were assigned to 1PCS and 2PCS. Results suggested two dimensionality of the structure of individual differences in amounts of stages. Amount of N1 loaded exclusively on one of two dimensions associated with 1PCS, amounts of W and N2 loaded exclusively on another dimension associated with 2PCS, and amount of N3 was equally loaded on both dimensions. Scores demonstrated stability within each stage, but a drastic change in just one of two scores occurred during transitions from one stage to another on the way from wakefulness to deeper sleep (e.g., 2PCS changed from >0 to <0 during transition W→N1, 1PCS changed from <0 to >0 during transition N1→N2). Therefore, the transitions between stages observed during short naps might be linked to rapid changes in the reciprocal interactions between the promoters/inhibitors of sleep/wakefulness.NEW & NOTEWORTHY In the present nap study, two dimensionality of the structure of individual differences in sleep stages was revealed. These results also suggested that individual variation in the sleep and wake drives associated with the first and second principal components of the EEG spectrum might underlie this structure. It seemed that each stage might be related to a certain, stage-specific combination of wake-sleep promoting/inhibiting influences associated with these drives for sleep and wake.

Differences between male and female university students in sleepiness, weekday sleep loss, and weekend sleep duration.

INTRODUCTION: Women and men experience sleep differently and the difference in intrinsic desire for sleep might underlie some of the observed male-female differences. The objective of this cross-sectional questionnaire study of university students was to determine male-female differences in self-reported sleepiness and sleep-wake patterns. METHODS: Five questionnaires were completed by 1650 students at four Russian universities. RESULTS: Compared to male students, female students reported a lower subjective sleep quality score, had a higher morning sleepability score and lower nighttime and daytime wakeability scores. They more often reported excessive daytime sleepiness and expected to be sleepier at any time of the day with the largest male-female difference around the times of sleep onset and offset. On free days, they reported a longer sleep duration and an earlier sleep onset. Free-weekday difference was larger for sleep duration and smaller for sleep onset. Such male-female differences showed similarity to the differences observed in university and high school students from different countries around the globe. There was no significant male-female difference in weekly averaged sleep duration, weekday sleep duration, hours slept, midpoint of sleep on free days, free-weekday difference in sleep offset, social jetlag, and morningness-eveningness score. Therefore, when studies rely on these self-reports, the most salient male-female differences might not be immediately evident. CONCLUSIONS: It seems that the intrinsic desire for longer sleep duration might contribute to a higher susceptibility of female students to weekday sleep loss. Among these students, negative effects of reduced sleep duration might be more common and more detrimental.

Differential relationship of two measures of sleepiness with the drives for sleep and wake.

PURPOSE: Since disagreement has been found between an objective sleep propensity measured by sleep onset latency (SOL) and subjective sleepiness assessment measured by the Epworth sleepiness scale (ESS) score, distinct underlying causes and consequences were suggested for these two sleepiness measures. We addressed the issue of validation of the ESS against objective sleepiness and sleep indexes by examining the hypothesis that these two sleepiness measures are disconnected due to their differential relationship with the antagonistic drives for sleep and wake. METHODS: The polysomnographic records of 50-min napping attempts were collected from 27 university students on three occasions. Scores on the first and second principal components of the electroencephalographic (EEG) spectrum were calculated to measure the sleep and wake drives, respectively. Self-assessments of subjective sleepiness and sleep were additionally collected in online survey of 633 students at the same university. RESULTS: An ESS score was disconnected with the polysomnographic and self-assessed SOL in the nap study and online survey, respectively. An ESS score but not SOL was significantly linked to the spectral EEG measure of the sleep drive, while SOL but not ESS showed a significant association with the spectral EEG measure of the opposing wake drive. CONCLUSIONS: Each of two sleepiness measures was validated against objective indicators of the opposing sleep-wake regulating processes, but different underlying causes were identified for two distinct aspects of sleepiness. A stronger sleep drive and a weaker opposing drive for wake seem to contribute to a higher ESS score and to a shorter SOL, respectively.

Age- and gender-associated differences in the sleepy brain's electroencephalogram.

Background. With the eyes closed, an increase in sleepiness is associated with a decrease of spectral electroencephalographic (EEG) power in the high-frequency rage (i.e. alpha activity) and an increase of the power in the low-frequency range (i.e. theta activity). It has been suggested that the changes in the high- and low-frequency ranges might determine the two (earlier and later) drowsiness stages that precede sleep onset, respectively.Objective. We tested whether such spectral EEG signatures of sleepiness vary with age or gender.Approach. The EEG signal was recorded at 2 h intervals in 48 volunteers (15-67 years, 27 females) deprived of sleep between Friday evening and Sunday evening. The EEG signatures of sleepiness were calculated by expressing each EEG spectrum as a deviation from the initial (Friday evening) EEG spectrum.Main results. An age- and gender-specific variation was found in the signatures. Only the pattern of age-associated variation changed with an increase in the sleepiness level. A two-stage response to the increase of sleepiness was confirmed, but only in younger study participants. Subjective sleepiness was associated with neither age nor gender.Significance. In sleep-deprivation research, accounting for age- and gender-specific variations in the spectral EEG measures of drowsiness might be recommended. The results did not reveal any disturbance of the motivational function of subjective sleepiness in older study participants.

Evening chronotype, late weekend sleep times and social jetlag as possible causes of sleep curtailment after maintaining perennial DST: ain't they as black as they are painted?

People sleep less in response to setting social clocks earlier relative to the sun clocks. We proposed here a model-based approach for estimating sleep loss as the difference between weekend and weekday risetimes divided on the difference between weekend risetime and weekday bedtime. We compared this approach with a traditional approach to estimating sleep curtailment as the difference in weekly average sleep duration in two conditions. Weekday and weekend sleep times reported for 320 samples provided possibility of testing whether evening types with later weekend sleep times and larger social jetlag differ from morning types with earlier weekend sleep times and smaller social jetlag on amount of sleep lost (1) throughout the week and (2) in response to an advance of weekday wakeups, for instance, after the expected installation of perennial Daylight Saving Time (DST). We found that (1) an amount of sleep lost due to advancing shift of weekday wakeups depends upon neither chronotype nor weekend sleep times nor social jetlag, (2) a very large amount of sleep is usually lost by evening types with later weekend sleep times and larger social jetlag and (3) an essential sleep loss is caused by our usual work/school schedules, even in morning types with early weekend sleep times and small social jetlag. As compared to such permanent sleep losses experienced by any types, an additional loss due to switching from Standard Time (ST) to perennial DST are expected to be relatively small. We also found that the traditional way of calculation of sleep curtailment leads to paradoxical conclusions, such as (1) sleep loss is larger when social jetlag is smaller, not larger, (2) sleep loss is larger when weekend sleep times are earlier, not later, (3) despite 1-h difference between two student samples in weekday wakeups, their sleep losses can be identical.

How have our clocks evolved? Adaptive and demographic history of the out-of-African dispersal told by polymorphic loci in circadian genes.

The mechanism of the molecular circadian clocks is currently understood as a transcription/translation feedback loop involving more than ten genes. Genetic variation at some of loci in these genes has been shaped by adaptation to environmental factors. In particular, latitudinal clines in allele frequency were documented in several animal species, but the contradictory conclusions were drawn from the results of rare human studies. Here we tested whether the out-of-African dispersal of human populations to higher latitudes of the Eurasian continent was associated with latitude-dependent shifts in allele frequency at polymorphic loci in genes of three (reference, circadian and skin pigmentation) groups. In order to detect the genetics-based signatures left by latitude-driven adaptation and to distinguish them from the confounding effects of population demographic history, we analyzed allele frequencies in 1594 individuals from 5 African and 11 Eurasian populations of the 1000 Genomes Project Phase 3. Up to 80 polymorphisms with global minor allele frequency > 0.2 were sampled from each of 36 genes (1665 polymorphisms in total). As expected, percentage of polymorphisms demonstrating both significantly enlarged differentiation of Eurasian populations on allele frequency and significant correlation between latitude and allele frequency was significantly higher in pigmentation genes compared to circadian genes and in circadian genes compared to reference genes. We also showed that the latitude-driven adaptation can be separated from genetic consequences of demographic perturbations by comparison of results obtained for the whole set of 16 African and Eurasian populations with results for only Eurasian populations that share the common demographic history. The revealed latitudinal clines in allele frequency seemed to be shaped by polygenic selection occurring by small allele frequency shifts spread across many loci in circadian and non-circadian genes. The present results provided a rationale for necessity to facilitate candidate gene studies by prioritizing genetic markers of chronotype.