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Methods of evaluation of substates of sleep and sleepiness differ in, at least, two respects. Although sleepiness has not been separated from other wake and sleep substates using yes-or-no criteria for sleep scoring, it would be consciously perceived and, therefore, assessed with a questionary. However, such subjective method was challenged by the finding suggesting a disconnect between two most widely used subjective and objective indicators of excessive daytime sleepiness (EDS), a score on the Epworth sleepiness scale (ESS) > 10 and a reduced latency to sleep onset (SOL), respectively. We examined whether these two EDS indicators differ in their association with physiological sleepiness, i.e., the polysomnographic indexes of elevated sleep pressure. In the afternoon hours, polysomnographic recordings were obtained throughout 54 50-min and 56 90-min napping attempts of 27 and 28 university students, respectively. Within some but not all 10-min intervals of the 50- or 90-min naps, each EDS indicator was validated against different objective polysomnographic indexes suggesting an association of EDS with elevated sleep pressure. Significant differences in sleep indexes were found between participants with short and longer SOL, but they disappeared right before the appearance of such differences between participants with higher and lower ESS score (usually at the 4th 10-min interval). This mismatch in timing of appearance of significant differences might be a plausible explanation for the lack of significant association between the ESS and SOL. Therefore, the physiologic underpinnings of the ESS can be uncovered despite such a disconnect between these two EDS indicators. Graphical abstract

The circadian phase difference between morning and evening types is a fundamental aspect of chronotype. However, results of categorizations into chronotypes based on reported sleep times show low concordance with those based on measurements of the hormonal or physiological or molecular rhythm–markers of the circadian phase. This might be partially explained by the profound individual differences in the phase angle between the sleep–wake cycle and these rhythms that depends on chronotype, age, sex, and other factors. Here, we examined the possibility of using self-reported sleep times in the condition of 5-days-on/2-days-off school/work schedule to estimate circadian phase differences between various chronotypes. In an in silico study, we determined that, for such an estimation, similarities of the compared chronotypes in weekend sleep duration and weekend–weekday gap and in risetime are required. In the following empirical and simulation studies of sleep times reported by 4940 survey participants, we provided examples of the estimation of circadian differences between chronotypes, and the model-based simulations of sleep times in morning and evening types exemplified a way to confirm such estimations. The results of in silico, empirical, and simulation studies underscore the possibility of using bedtimes and risetimes for direct estimation of the circadian phase differences between individuals in real-life situations, such as a 5-days-on/2-days-off school/work schedule. Additionally, the results of these studies on different chronotypes provided further mathematical modeling and empirical evidence for our failure to sleep more on weekends to recover/compensate/pay back/ catch up on lost sleep.

Morningness-eveningness is usually assessed as either a trait or a state using either a morning–evening preference scale or sleep timing reported for free days, respectively. These assessments were implemented in numerous studies exploring the associations between morningness-eveningness and health, mood, and sleep problems. Evening types almost always had more problems than morning types. We examined these associations in university students with conflicting results of trait and state assessments of morningness-eveningness and tried to confirm their chronotype using a multidimensional chronotyping approach that recognizes four types other than morning and evening (lethargic, vigilant, napping, and afternoon). The conflicting trait and state assessments of morningness-eveningness were found in 141 of 1582 students. Multidimensional chronotyping supported morningness of morning types with late weekend sleep timing, and the associations with health, mood, and sleep problems resembled the associations of other morning types (i.e., these associations persisted despite late sleep timing). In contrast, evening types with early weekend sleep timing were more likely classified as lethargic or napping types rather than evening types. They did not resemble evening types in their associations with health, mood, and sleep problems (i.e., early sleep timing did not change these associations). Model-based simulations of the sleep–wake cycles of students with conflicting trait and state assessments suggested that their bedtimes cannot be solely determined by their biological clocks. On weekdays or weekends, mind-bedtime procrastination can lead to missing the bedtime signal from their biological clocks (i.e., self-deprivation of sleep or, in other words, voluntary prolongation of the wake phase of the sleep–wake cycle).

Background: Our work/study culture is biased towards the circadian clocks of “morning types”, whereas “evening types” are forced to advance their weekday waking times relative to weekend waking times. Since the experimental research consistently reveals a >2 h difference between these two chronotypes in the positions of their endogenous circadian phases, we hypothesized the necessity to permit a >2 h difference between them in weekday waking times to equalize their irrecoverable loss in sleep on weekdays. Methods: A total of 659 and 1106 participants of online surveys identified themselves as morning and evening types, respectively. The hypothesis was tested by applying a model of sleep–wake regulation for simulating sleep times reported by 245 lecturers of these two types, and by comparison of sleep times of these types among these lecturers and 1520 students. Results: The hypothesis was supported by results showing that, if, on weekdays, an “average” morning type wakes at 6 a.m., the equalization of the weekday sleep loss of the two chronotypes would require the waking time of an “average” evening type to be no earlier than 8 a.m. Conclusions: These results may be implemented in a model-based methodology for the correction of weekday waking times to equalize weekday sleep loss.

Awakening is a transitional process from sleep to wakefulness. There is a certain restructuring in the work of brain structures during this period, which further allows a person to perform conscious activity. The study of interhemispheric asymmetry of amplitude–amplitude couplings of EEG rhythms was carried out. A psychomotor test was used in experiments. This test allows us to observe the moments of falling asleep and waking up when performing monotonous work. Multichannel EEG was recorded simultaneously with the test. The data of 14 subjects who reached the second stage of sleep during the experiment were analyzed. The selected 20 s EEG segments prior to awakening were processed using a continuous wavelet transform based on the “mother” complex Morlet wavelet. The Kendall correlation coefficient was used to evaluate the measure of EEG rhythms coupling. Quantitative changes in the couplings of EEG rhythms were revealed as the moment of awakening approached: in the two most distant time intervals, the total number of asymmetric connections was five to three, and in the two closest segments, there was only one coupling of EEG rhythms. This is not just a decrease in the number of connections, but also a change of EEG rhythms coupling throughout the entire 20-s segment. The dynamic nature of the EEG rhythms coupling in the hemispheres before awakening to resume the task is shown, which may indicate the dynamic relationship of structural and functional associations of the brain.

The aim of the study was to evaluate psychophysiological predictors of the quality of monotonous activity performance against the background of partial sleep deprivation. Fourteen subjects aged 18–22 years with partial sleep deprivation participated in the experiments. Each subject participated in four experimental sessions with a computer driving simulator: 1—without sleep deprivation, 2—with sleep deprivation, 3—with sleep deprivation and periodic exposure to a massage vibration seat cover, 4—with sleep deprivation and periodic spraying of peppermint oil from an aroma diffuser. Periodically, the subject was required to respond to two types of stimuli. Driving simulator data, 19-channel electroencephalogram (EEG), electrocardiogram (ECG) and videotape of the subject's face were recorded. Subjects took questionnaires for drowsiness and general well-being, and their reaction time was also tested before the experiment. A statistically significant increase in eye closure percentage and heart rate variability spectral features were detected before the driving errors. High-stress levels and chronic sleep deprivation were detected in the subjects. Against this background, peppermint oil and massage vibration seat cover had no statistically significant effect on the number of errors. The values of physiological indices before errors indicate different causes of errors in experiments. Neither peppermint oil or massage vibration sit cover were effective in preventing errors in case of high stress and chronic sleep deprivation.

Objective measures of activity recovery performance in monotonous psychomotor task after brief episodes of daytime sleep were investigated. We used a psychomotor test in which the partially sleep-deprived subjects had to press the button 10 times with alternating left and right hands for 70 min. The task-induced short episodes of sleep, after which subjects had to resume the task. EEG of the anterior and central lead areas was studied when resuming the task after awakening from the first stage of sleep. We compared the situations of resumption of the pattern with left and right hands. The power of beta- and gamma-EEG oscillations during preparation and beginning of psychomotor activity was found to be higher when the subject starts to press the button with the left (nondominant) hand which may be a manifestation of sleep inertia. We attribute this to the fact that in this case the strategy for resuming activity interrupted by the short sleep is suboptimal and energy intensive, requiring greater cognitive activity. We also assume that this situation is preceded by a lower level of consciousness, in which the subject correctly remembers the instruction, but does reliably start with the dominant hand. However, the subject fully recovers and correctly performs the motor and synchronized cognitive account task immediately after awakening. This study contributes to an objective assessment of fluctuations in the human condition in monotonous work, which can lead to loss of concentration, reduced response time, drowsiness and negatively affect work safety.

Complex systems are occasionally switching between several qualitatively different modes of behavior, even in the absence of external influences. An example of such mode-switching behavior of a complex system is a sequence of changes in sleep stages observed on approximately 90-min interval of sleep cycle. We examined whether relatively stable stages and relatively rapid transitions between them can be linked to the observed markers of underlying processes of sleep–wake regulation. Using data on two napping attempts of each of 28 university students, we described how scores on principal components of the EEG spectrum and rates of transitions between stages can serve as objective markers of interaction between three underlying on–off switching mechanisms that, in turn, can reflect strengths of the mutually inhibiting drives for sleep, wake, and REM sleep. A sequence of transitions between five stages over sleep cycle can be viewed as representing a sequence of episodes of the “struggle” between these three permanently competing mechanisms. Each of typical stage transitions in sleep cycle can be interpreted as a relatively rapid change in state of one or two of these three on–off switchers. It seems that only one of them is capable to maintain the switch on state during a stage with the exception of transient stage 1 sleep during which all switches remain in switch off state. An aim of future research of stages and their transitions during normal and disturbed sleep can be aimed on identification of a switching mechanism involved into a certain disturbance of sleep. Graphical Abstract

The efforts to link the individual differences in personality to the individual differences in sleep-wake behavior have a long history. One of the topics of such research might be to determine the strength of association between these two domains of individual variation. This requires the implementation of several inventories designed for integrative multidimensional assessments of a set of broad personality traits and a set of sleep-wake behavioral traits. Four independent samples were collected (in total, 759 individuals) for estimating general overlap between the domains of individual variation in personality psychology and chronobiology. Canonical correlation analyses provided the estimates of general overlap of six broad personality traits assessed with the 172-word RCIP (Rugby Cake Inventory of Personality) with six distinct sleep-wake adaptabilities assessed with the 72-item SWPAQ (Sleep-Wake Pattern Assessment Questionnaire) and the SWAT (Sleep-Wake Adaptability Test) in two, the 60- and 168-item, versions. It was demonstrated that general overlap between individual variation in two domains was significant and replicable albeit rather weak (6%–8%). Moreover, regression analyses of specific overlaps of each of six scales for assessing sleep-wake adaptability with a set of six scales for personality assessment suggested that a score on any of adaptability scales seemed to be a significant predictor of, at least, one of six scores on personality trait scales. Studies in other tongues are desired for the replication of the results indicating the statistically significant general and specific overlaps between personality traits and sleep-wake adaptabilities.

The article presents the results of a pilot study of the perception of the demotivator and meme genres. It was a part of an experimental study of psychophysiological and psycholinguistic features of perception and understanding of multimodal extremist texts. The aim of the study is to develop and test the hypothesis about the influence of genre on perception of multimodal texts. To test the hypothesis, we analyze the respondents' eye movement data from the main experimental study (n = 60; 31 forensic linguists with anti-extremism practice, 29 non-experts). Research methods were eye-tracking and quantitative data processing. The following statistically reliable data were obtained: compared to memes, respondents looked at demotivators (1) for a longer time, made (2) shorter fixations, (3) with more of them, and also made (4) faster and (5) shorter saccades. These parameters may indicate a denser scanning pattern of viewing demotivators compared to memes and greater cognitive expenditure in assessing the semantic content of demotivator texts. The results of the study suggest a connection between genre and the degree of multimodal texts perception complexity. This provides an opportunity for further research in this direction and, in the future, will enable the development of norms of cognitive load of judicial linguists who analyse multimodal extremist texts.