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 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. 0022-3077/21 Copyright © 2021 the American Physiological Society

Sleep latency in poor nappers under exposure to weak 2-Hz and 8-Hz electromagnetic fields

It was hypothesized that human sleep might respond to the fields emitted by such natural sources as magnetic activity of the sun and the earth’s magnetic fields. However, the experiments aimed on testing this hypothesis remain scarce. Previously, we found an increase in the amounts of stages N2 or N3 during napping of good sleepers under exposure to low-level (0.004 μT) electromagnetic fields of frequencies 1 Hz or 2 Hz. It remains unexplored whether these fields might additionally decrease latency to stage N1. In this study, we selected 13 people with falling asleep problems to examine the effects of low-level electromagnetic fields on sleep latency. Sleep of these study participants was polysomnographically recorded during three 50-min afternoon napping attempts, either with exposure to either 2 Hz/0.004 μT or 8 Hz/0.004 μT electromagnetic fields or without exposure. We did not find that the sham exposure differed from the 2 Hz and 8 Hz exposures in latency to N1, while latency to N2 after the sham exposure was even shorter than after either the 2 Hz or 8 Hz exposure. We concluded that, although the effects of tested fields might be beneficial for sleep intensity (e.g., due to prolongation of N3), they might not be additionally effective against the falling asleep problems. © 2021 Informa UK Limited, trading as Taylor & Francis Group

Effects of exposures to weak 2-Hz vs. 8-Hz electromagnetic fields on spectral characteristics of the electroencephalogram in afternoon nap

The human brain seems to be able to respond to low-level extremely low-frequency electromagnetic fields. Controlled laboratory studies of human sleep under exposure to such fields are scarce, especially on the effects of 1 Hz–16 Hz fields overlapping with the frequencies of the electroencephalographic (EEG) signal (e.g., delta, theta, alpha, and sigma activities). In a double-blind placebo-controlled study, we examined the effects of exposure to low-level electromagnetic fields of frequencies 2 Hz and 8 Hz on the EEG power density spectra in the range from 1 Hz to 16 Hz and sleep structure. Sleep of 14 young healthy volunteers was polysomnographically recorded during three 50-min afternoon naps (either without exposure or with 2 Hz/0.004 μT or 8 Hz/0.004 μT electromagnetic field). During the first 30 min of a nap the sham, 2 Hz or 8 Hz/0.004 μT exposures had the same effect. For the remaining 20 min, amount of stage 3 sleep and powers in 1 Hz-8 Hz range continued to build up under the 8 Hz/0.004μT and, especially, under the 2 Hz/0.004 μT exposure, whereas they did not change in the sham condition. Therefore, the low-level 2 Hz electromagnetic fields might stimulate deep sleep in the afternoon nap. © 2020 Informa UK Limited, trading as Taylor & Francis Group

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. © 2021 The Foundation for Professionals in Services for Adolescent

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

Single-Item Chronotyping (SIC), a method to self-assess diurnal types by using 6 simple charts

Research on individual differences in the fields of chronobiology and chronopsychology mostly focuses on two – morning and evening – chronotypes. However, recent developments in these fields pointed at a possibility to extend chronotypology beyond just two chronotypes. We examined this possibility by implementing the Single-Item Chronotyping (SIC) as a method for self-identification of chronotype among six simple chart options illustrating the daily change in alertness level. Of 2283 survey participants, 2176 (95%) chose one of these options. Only 13% vs. 24% chose morning vs. evening type (a fall vs. a rise of alertness from morning to evening), while the majority of participants chose four other types (with a peak vs. a dip of alertness in the afternoon and with permanently high vs. low alertness levels throughout the day, 15% vs. 18% and 9% vs. 16%, respectively). The same 6 patterns of diurnal variation in sleepiness were yielded by principal component analysis of sleepiness curves. Six chronotypes were also validated against the assessments of sleep timing, excessive daytime sleepiness, and abilities to wake or sleep on demand at different times of the day. We concluded that the study results supported the feasibility of classification with the 6 options provided by the SIC. © 2020 Elsevier Lt