Fundamentals of sleep regulation: Model and benchmark values for fractal and oscillatory neurodynamics.

Homeostatic, circadian and ultradian mechanisms play crucial roles in the regulation of sleep. Evidence suggests that ratios of low-to-high frequency power in the electroencephalogram (EEG) spectrum indicate the instantaneous level of sleep pressure, influenced by factors such as individual sleep-wake history, current sleep stage, age-related differences and brain topography characteristics. These effects are well captured and reflected in the spectral exponent, a composite measure of the constant low-to-high frequency ratio in the periodogram, which is scale-free and exhibits lower interindividual variability compared to slow wave activity, potentially serving as a suitable standardization and reference measure. Here we propose an index of sleep homeostasis based on the spectral exponent, reflecting the level of membrane hyperpolarization and/or network bistability in the central nervous system in humans. In addition, we advance the idea that the U-shaped overnight deceleration of oscillatory slow and fast sleep spindle frequencies marks the biological night, providing somnologists with an EEG-index of circadian sleep regulation. Evidence supporting this assertion comes from studies based on sleep replacement, forced desynchrony protocols and high-resolution analyses of sleep spindles. Finally, ultradian sleep regulatory mechanisms are indicated by the recurrent, abrupt shifts in dominant oscillatory frequencies, with spindle ranges signifying non-rapid eye movement and non-spindle oscillations - rapid eye movement phases of the sleep cycles. Reconsidering the indicators of fundamental sleep regulatory processes in the framework of the new Fractal and Oscillatory Adjustment Model (FOAM) offers an appealing opportunity to bridge the gap between the two-process model of sleep regulation and clinical somnology.

Sleep alterations as a function of 88 health indicators.

BACKGROUND: Alterations in sleep have been described in multiple health conditions and as a function of several medication effects. However, evidence generally stems from small univariate studies. Here, we apply a large-sample, data-driven approach to investigate patterns between in sleep macrostructure, quantitative sleep EEG, and health. METHODS: We use data from the MrOS Sleep Study, containing polysomnography and health data from a large sample (N = 3086) of elderly American men to establish associations between sleep macrostructure, the spectral composition of the electroencephalogram, 38 medical disorders, 2 health behaviors, and the use of 48 medications. RESULTS: Of sleep macrostructure variables, increased REM latency and reduced REM duration were the most common findings across health indicators, along with increased sleep latency and reduced sleep efficiency. We found that the majority of health indicators were not associated with objective EEG power spectral density (PSD) alterations. Associations with the rest were highly stereotypical, with two principal components accounting for 85-95% of the PSD-health association. PC1 consists of a decrease of slow and an increase of fast PSD components, mainly in NREM. This pattern was most strongly associated with depression/SSRI medication use and age-related disorders. PC2 consists of changes in mid-frequency activity. Increased mid-frequency activity was associated with benzodiazepine use, while decreases were associated with cardiovascular problems and associated medications, in line with a recently proposed hypothesis of immune-mediated circadian demodulation in these disorders. Specific increases in sleep spindle frequency activity were associated with taking benzodiazepines and zolpidem. Sensitivity analyses supported the presence of both disorder and medication effects. CONCLUSIONS: Sleep alterations are present in various health conditions.

Mobile sleep EEG suggests delayed brain maturation in adolescents with ADHD: A focus on oscillatory spindle frequency.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder. Although data show ADHD is associated with sleep problems, approaches to analyze the association between ADHD and sleep electrophysiology are limited to a few methods with circumscribed foci. AIMS: Sleep EEG was analyzed by a mixed-radix FFT routine and power spectrum parametrization in adolescents with ADHD and adolescents not at-risk for ADHD. Spectral components of sleep EEG were analyzed employing a novel, model-based approach of EEG power spectra. METHODS AND PROCEDURES: The DREEM mobile polysomnography headband was used to record home sleep EEG from 19 medication-free adolescents with ADHD and 29 adolescents not at-risk for ADHD (overall: N = 56, age range 14-19 years) and groups were compared on characteristics of NREM sleep. OUTCOMES AND RESULTS: Adolescents with ADHD exhibited lower frequency of spectral peaks indicating sleep spindle oscillations whereas adolescents not at-risk for ADHD showed lower spectral power in the slow sleep spindle and beta frequency ranges. CONCLUSIONS AND IMPLICATIONS: The observed between-groups difference might indicate delayed brain maturity unraveled during sleep in ADHD.

Temporal association between sleep spindles and ripples in the human anterior and mediodorsal thalamus.

Sleep spindles are major oscillatory components of Non-Rapid Eye Movement (NREM) sleep, reflecting hyperpolarization-rebound sequences of thalamocortical neurons. Reports suggest a link between sleep spindles and several forms of high-frequency oscillations which are considered as expressions of pathological off-line neural plasticity in the central nervous system. Here we investigated the relationship between thalamic sleep spindles and ripples in the anterior and mediodorsal nuclei (ANT and MD) of epilepsy patients. Whole-night LFP from the ANT and MD were co-registered with scalp EEG/polysomnography by using externalized leads in 15 epilepsy patients undergoing a Deep Brain Stimulation protocol. Slow (~12 Hz) and fast (~14 Hz) sleep spindles were present in the human ANT and MD and roughly, 20% of them were associated with ripples. Ripple-associated thalamic sleep spindles were characterized by longer duration and exceeded pure spindles in terms of spindle power as indicated by time-frequency analysis. Furthermore, ripple amplitude was modulated by the phase of sleep spindles within both thalamic nuclei. No signs of pathological processes were correlated with measures of ripple and spindle association, furthermore, the density of ripple-associated sleep spindles in the ANT showed a positive correlation with verbal comprehension. Our findings indicate the involvement of the human thalamus in coalescent spindle-ripple oscillations of NREM sleep.

The Semmelweis Study: a longitudinal occupational cohort study within the framework of the Semmelweis Caring University Model Program for supporting healthy aging.

The Semmelweis Study is a prospective occupational cohort study that seeks to enroll all employees of Semmelweis University (Budapest, Hungary) aged 25 years and older, with a population of 8866 people, 70.5% of whom are women. The study builds on the successful experiences of the Whitehall II study and aims to investigate the complex relationships between lifestyle, environmental, and occupational risk factors, and the development and progression of chronic age-associated diseases. An important goal of the Semmelweis Study is to identify groups of people who are aging unsuccessfully and therefore have an increased risk of developing age-associated diseases. To achieve this, the study takes a multidisciplinary approach, collecting economic, social, psychological, cognitive, health, and biological data. The Semmelweis Study comprises a baseline data collection with open healthcare data linkage, followed by repeated data collection waves every 5 years. Data are collected through computer-assisted self-completed questionnaires, followed by a physical health examination, physiological measurements, and the assessment of biomarkers. This article provides a comprehensive overview of the Semmelweis Study, including its origin, context, objectives, design, relevance, and expected contributions.

Multivariate prediction of cognitive performance from the sleep electroencephalogram.

Human cognitive performance is a key function whose biological foundations have been partially revealed by genetic and brain imaging studies. The sleep electroencephalogram (EEG) is tightly linked to structural and functional features of the central nervous system and serves as another promising biomarker. We used data from MrOS, a large cohort of older men and cross-validated regularized regression to link sleep EEG features to cognitive performance in cross-sectional analyses. In independent validation samples 2.5-10% of variance in cognitive performance can be accounted for by sleep EEG features, depending on the covariates used. Demographic characteristics account for more covariance between sleep EEG and cognition than health variables, and consequently reduce this association by a greater degree, but even with the strictest covariate sets a statistically significant association is present. Sigma power in NREM and beta power in REM sleep were associated with better cognitive performance, while theta power in REM sleep was associated with worse performance, with no substantial effect of coherence and other sleep EEG metrics. Our findings show that cognitive performance is associated with the sleep EEG (r = 0.283), with the strongest effect ascribed to spindle-frequency activity. This association becomes weaker after adjusting for demographic (r = 0.186) and health variables (r = 0.155), but its resilience to covariate inclusion suggest that it also partially reflects trait-like differences in cognitive ability.

Daily rhythms, light exposure and social jetlag correlate with demographic characteristics and health in a nationally representative survey.

The timing of daily activity in humans have been associated with various demographic and health-related factors, but the possibly complex patterns of confounding and interaction between these has not been systematically explored. We use data from Hungarostudy 2021, a nationally representative survey of 7000 Hungarian adults to assess the relationship between self-reported chronotype, social jetlag (using the Munich Chronotype Questionnaire), demographic variables and self-reported health and demographic variables, including ethnic minority membership. Supporting the validity of self-reports, participants with later chronotypes reported the lowest daytime sleepiness at a later clock time. We found that older age, female sex, a more eastward and southward geographical position, residence in a smaller settlement, less education and income, religiousness and cohabiting with small children were associated with an earlier chronotype. Younger age, higher education and income, and cohabiting with small children were associated with increased social jetlag. Of the 48 health-related variables surveyed, the relationship with both chronotype and social jetlag were mostly accounted for by age, sex, and socioeconomic effects, but we identified alcohol consumption, smoking, and physical activity as predictors of both social jetlag and chronotype, while a number of disorders were either positively or negatively associated with chronotype and social jetlag. Our findings from a large, nationally representative sample indicate that both biological and social factors influence chronotype and identified both demographic and health-related variables as risk factors for social jetlag. Our results, however, do not support a causal relationship between light exposure and mental health.

Sleep and dreaming in the light of reactive and predictive homeostasis.

Dreams are often viewed as fascinating but irrelevant mental epihenomena of the sleeping mind with questionable functional relevance. Despite long hours of oneiric activity, and high individual differences in dream recall, dreams are lost into oblivion. Here, we conceptualize dreaming and dream amnesia as inherent aspects of the reactive and predictive homeostatic functions of sleep. Mental activity during sleep conforms to the interplay of restorative processes and future anticipation, and particularly during the second half of the night, it unfolds as a special form of non-constrained, self-referent, and future-oriented cognitive process. Awakening facilitates constrained, goal-directed prospection that competes for shared neural resources with dream production and dream recall, and contributes to dream amnesia. We present the neurophysiological aspects of reactive and predictive homeostasis during sleep, highlighting the putative role of cortisol in predictive homeostasis and forgetting dreams. The theoretical and methodological aspects of our proposal are discussed in relation to the study of dreaming, dream recall, and sleep-related cognitive processes.

A questionnaire measure of adult attachment anxiety correlates with frontal hemispheric asymmetry in sleep spindle activity.

Subjects with high levels of attachment anxiety and neuroticism were proposed to be characterized by higher relative right rather than left frontal activity. Since sleep spindles are argued to reflect enhanced offline neuroplasticity, higher spindle activity measured over the right frontal areas relative to the corresponding left frontal ones could index higher attachment anxiety and neuroticism. Our aim was to explore the relationship between the lateralization patterns of frontally dominant slow sleep spindles and questionnaire measures of adult attachment anxiety and neuroticism. Thirty-four healthy subjects (male = 19; Mage = 31.64; SDage = 9.5) were enrolled in our preliminary study. Second night EEG/polysomnography records and questionnaire measures of personality (Zuckerman-Kuhlman Personality Questionnaire) and adult attachment (Relationship Scales Questionnaire) were collected. Frontal slow sleep spindles were measured by the Individual Adjustment Method (IAM), whereas hemispheric asymmetry indexes of spindle occurrence rate, duration, and amplitude were derived as normalized left-right differences (electrode pairs: Fp1-Fp2, F3-F4, and F7-F8). Relative right lateralization of frontolateral and frontopolar slow sleep spindle density and mid-frontal slow spindle duration were associated with attachment anxiety, but spindle lateralization was less closely related to neuroticism. The relationships between frontal slow spindle laterality and attachment anxiety remained statistically significant even after controlling for the effect of neuroticism, whereas attachment avoidance-independence was not correlated with frontal slow spindle lateralization. Right frontal lateralization of slow sleep spindle activity might indicate attachment status in terms of the negative view of the self. Supplementary Information: The online version contains supplementary material available at 10.1007/s41105-022-00426-0.

[The Impact of Psychostimulants on Sleep in Children with Attention Deficit Hyperactivity Disorder: A Systematic Review of Polysomnography Studies]. / A pszichostimulánsok alkalmazásának alvásra gyakorolt hatása fi gyelemhiányos hiperaktivitás zavarral élo gyerekek körében: a poliszomnográfi ás vizsgálatok szakirodalmának szisztematikus áttekintése.

OBJECTIVE: Psychostimulants are widely used pharmacotherapeutic tools in the treatment process of severe or non-responsive childhood attention-deficit/hyperactivity disorder. Despite their efficacy, stimulants can influence the quality and quantity of sleep as a side effect, but this issue remains insufficiently clarified in the existing literature, with partly contradictory findings. The aim of this review is to provide a comprehensive analysis of research results based on polysomnography, shedding light on the current state of knowledge in this area. This insight can be valuable for guiding the design of future research and optimizing therapeutic plans. METHODS: Following the PRISMA guidelines, we systematically reviewed and analyzed studies that assessed the quality of sleep using polysomnography during stimulant treatment. As a result of our search, we identified 331 potential publications, which were independently screened, and a total of 13 relevant articles were analyzed in detail. RESULTS: Based on the results of the examined studies, there were a total of 5 instances of sleep-facilitating effects reported in the context of stimulant treatments, while 5 studies indicated sleep-inhibiting effects, and in three cases, no effects were observed. CONCLUSIONS: Although it is important to consider the impact of medication on sleep in the treatment of childhood attention-deficit/hyperactivity disorder, further research is required to clarify this issue. This will enable the customization of therapeutic recommendations and plans, aligning with the principles of precision medicine, taking into account the varying research designs and sample sizes.

Overnight dynamics in scale-free and oscillatory spectral parameters of NREM sleep EEG.

Unfolding the overnight dynamics in human sleep features plays a pivotal role in understanding sleep regulation. Studies revealed the complex reorganization of the frequency composition of sleep electroencephalogram (EEG) during the course of sleep, however the scale-free and the oscillatory measures remained undistinguished and improperly characterized before. By focusing on the first four non-rapid eye movement (NREM) periods of night sleep records of 251 healthy human subjects (4-69 years), here we reveal the flattening of spectral slopes and decrease in several measures of the spectral intercepts during consecutive sleep cycles. Slopes and intercepts are significant predictors of slow wave activity (SWA), the gold standard measure of sleep intensity. The overnight increase in spectral peak sizes (amplitudes relative to scale-free spectra) in the broad sigma range is paralleled by a U-shaped time course of peak frequencies in frontopolar regions. Although, the set of spectral indices analyzed herein reproduce known age- and sex-effects, the interindividual variability in spectral slope steepness is lower as compared to the variability in SWA. Findings indicate that distinct scale-free and oscillatory measures of sleep EEG could provide composite measures of sleep dynamics with low redundancy, potentially affording new insights into sleep regulatory processes in future studies.

The sleep EEG envelope is a novel, neuronal firing-based human biomarker.

Sleep EEG reflects voltage differences relative to a reference, while its spectrum reflects its composition of various frequencies. In contrast, the envelope of the sleep EEG reflects the instantaneous amplitude of oscillations, while its spectrum reflects the rhythmicity of the occurrence of these oscillations. The sleep EEG spectrum is known to relate to demographic, psychological and clinical characteristics, but the envelope spectrum has been rarely studied. In study 1, we demonstrate in human invasive data from cortex-penetrating microelectrodes and subdural grids that the sleep EEG envelope spectrum reflects neuronal firing. In study 2, we demonstrate that the scalp EEG envelope spectrum is stable within individuals. A multivariate learning algorithm could predict age (r = 0.6) and sex (r = 0.5) from the EEG envelope spectrum. With age, oscillations shifted from a 4-5 s rhythm to faster rhythms. Our results demonstrate that the sleep envelope spectrum is a promising biomarker of demographic and disease-related phenotypes.

Analysis of slow and fast sleep spindle properties in Parkinson's disease - A comparative EEG study.

STUDY OBJECTIVES: Sleep disturbances and altered sleep macrostructure are common in Parkinson's disease (PD). Few studies have addressed the changes in sleep spindle (SS) properties in this movement disorder so far. SS seem to be fundamental of both sleep architecture and memory consolidation. The aim of our comparative study was to investigate the changes of SS characteristics in PD, and reveal the relationship between SS properties and cognitive function. METHODS: We investigated 20 PD patients and 18 age-matched controls. All participants underwent a 24-hour-long polygraphic EEG recording after extensive clinical investigation. We detected slow and fast SS properties automatically using individual adjusting method (IAM). The data were statistically evaluated. RESULTS: We found significantly lower fast spindle amplitude in PD comparing with controls. We did not find significant differences in SS densities, duration and oscillatory frequency between the groups. We detected significant positive correlation between fast SS amplitude and memory in PD, and between fast SS density and retrograde memory in controls. The total Addenbrooke's cognitive score correlated negatively with slow SS density and duration in controls. CONCLUSIONS: By the time clinical diagnosis of PD is established, the pathological process is already spreading. Changes in sleep macrostructure and SS properties might become a useful biomarker of the neurodegenerative process in PD. In addition, decreased fast SS amplitude might predict further cognitive deterioration and indicate early involvement of corresponding cortical area. Our study results strengthen the importance of EEG examination in PD, and the use of IAM method in SS analysis.

Scale-free and oscillatory spectral measures of sleep stages in humans.

Power spectra of sleep electroencephalograms (EEG) comprise two main components: a decaying power-law corresponding to the aperiodic neural background activity, and spectral peaks present due to neural oscillations. "Traditional" band-based spectral methods ignore this fundamental structure of the EEG spectra and thus are susceptible to misrepresenting the underlying phenomena. A fitting method that attempts to separate and parameterize the aperiodic and periodic spectral components called "fitting oscillations and one over f" (FOOOF) was applied to a set of annotated whole-night sleep EEG recordings of 251 subjects from a wide age range (4-69 years). Most of the extracted parameters exhibited sleep stage sensitivity; significant main effects and interactions of sleep stage, age, sex, and brain region were found. The spectral slope (describing the steepness of the aperiodic component) showed especially large and consistent variability between sleep stages (and low variability between subjects), making it a candidate indicator of sleep states. The limitations and arisen problems of the FOOOF method are also discussed, possible solutions for some of them are suggested.

Role of anterior thalamic circuitry during sleep.

Increased attention has been paid to the structure and function of anterior nucleus of the thalamus (ANT), since deep brain stimulation (DBS) treatment for epilepsy launched a decade ago. The efficacy of the treatment on seizure count varies patient from patient and we have limited information on the predictors of better outcomes. While the thalamus is considered the key brain region responsible for maintaining sleep, ANT was traditionally not involved in this function. Recent experimental and human data point to a possible role of ANT in sleep processes, although the underlying mechanisms are still ambiguous. Beside evaluating the current knowledge on sleep disturbances experienced during ANT-DBS treatment, the search for valid biomarkers primarily resides on a better understanding of sleep circuits implicating ANT and its subnuclei. Hypothetically better selectivity within the target may increase seizure outcomes and reduce psychiatric and cognitive side effects. Hence, the main scope of this review is to summarize the evidence on the activity measured in the ANT during non-REM and REM sleep. Furthermore, we aim to find shared properties of sleep processes and ANT-related functions examined more thoroughly during wakefulness, such as selective attention and memory.

Prolongation of cortical sleep spindles during hippocampal interictal epileptiform discharges in epilepsy patients.

OBJECTIVE: Memory deficits are frequent among patients with epilepsies affecting the temporal lobe. Hippocampal interictal epileptic discharges (hIEDs), the presumed epileptic exaggeration of sharp wave-ripples (SWRs), are known to contribute to memory dysfunction, but the potential underlying mechanism is unknown. The precise temporal coordination between hippocampal SWRs and corticothalamic spindles during sleep is critical for memory consolidation. Moreover, previous investigation indicated that hIEDs induce neocortical spindlelike oscillation. In the present study, we aimed to assess the influence of hIEDs on neocortical spindles. METHODS: We analyzed the spindle characteristics (duration, amplitude, frequency) of 21 epilepsy patients implanted with foramen ovale (FO) electrodes during a whole night sleep. Scalp sleep spindles were categorized based on their temporal relationship to hIEDs detected on the FO electrodes. Three groups were created: (1) spindles coinciding with hIEDs, (2) spindles "induced" by hIEDs, and (3) spindles without hIED co-occurrence. RESULTS: We found that spindles co-occurring with hIEDs had altered characteristics in all measured properties, lasted longer by 126 ± 48 ms (mean ± SD), and had higher amplitude by 3.4 ± 3.2 µV, and their frequency range shifted toward the higher frequencies within the 13-15-Hz range. Also, hIED-induced spindles had identical oscillatory properties to spindles without any temporal relationships with hIEDs. In more than half of our subjects, clear temporal coherence was revealed between hIEDs and spindles, but the direction of the coupling was patient-specific. SIGNIFICANCE: We investigated the effect of hippocampal IEDs on neocortical spindle activity and found spindle alterations in cases of spindle-hIED co-occurrence, but not in cases of hIED-initiated spindles. We propose that this is a marker of a pathologic process, where IEDs may have direct effect on spindle generation. It could mark a potential mechanism whereby IEDs disrupt memory processes, and also provide a potential therapeutic target to treat memory disturbances in epilepsy.

Thalamic activity during scalp slow waves in humans.

Slow waves are major pacemakers of NREM sleep oscillations. While slow waves themselves are mainly generated by cortical neurons, it is not clear what role thalamic activity plays in the generation of some oscillations grouped by slow waves, and to what extent thalamic activity during slow waves is itself driven by corticothalamic inputs. To address this question, we simultaneously recorded both scalp EEG and local field potentials from six thalamic nuclei (bilateral anterior, mediodorsal and ventral anterior) in fifteen epileptic patients (age-range: 17-64 years, 7 females) undergoing Deep Brain Stimulation Protocol and assessed the temporal evolution of thalamic activity relative to scalp slow waves using time-frequency analysis. We found that thalamic activity in all six nuclei during scalp slow waves is highly similar to what is observed on the scalp itself. Slow wave downstates are characterized by delta, theta and alpha activity and followed by beta, high sigma and low sigma activity during subsequent upstates. Gamma activity in the thalamus is not significantly grouped by slow waves. Theta and alpha activity appeared first on the scalp, but sigma activity appeared first in the thalamus. These effects were largely independent from the scalp region in which SWs were detected and the precise identity of thalamic nuclei. Our results suggest that while small thalamocortical neuron assemblies may initiate cortical oscillations, especially in the sleep spindle range, the large-scale neuronal activity in the thalamus which is detected by field potentials is principally driven by global cortical activity, and thus it is highly similar to what is observed on the scalp.

Topographical relocation of adolescent sleep spindles reveals a new maturational pattern in the human brain.

Current theories of human neural development emphasize the posterior-to-anterior pattern of brain maturation. However, this scenario leaves out significant brain areas not directly involved with sensory input and behavioral control. Suggesting the relevance of cortical activity unrelated to sensory stimulation, such as sleep, we investigated adolescent transformations in the topography of sleep spindles. Sleep spindles are known to be involved in neural plasticity and in adults have a bimodal topography: slow spindles are frontally dominant, while fast spindles have a parietal/precuneal origin. The late functional segregation of the precuneus from the frontoparietal network during adolescence suggests that spindle topography might approach the adult state relatively late in development, and it may not be a result of the posterior-to-anterior maturational pattern. We analyzed the topographical distribution of spindle parameters in HD-EEG polysomnographic sleep recordings of adolescents and found that slow spindle duration maxima traveled from central to anterior brain regions, while fast spindle density, amplitude and frequency peaks traveled from central to more posterior brain regions. These results provide evidence for the gradual posteriorization of the anatomical localization of fast sleep spindles during adolescence and indicate the existence of an anterior-to-posterior pattern of human brain maturation.

The heartbeat evoked potential is a questionable biomarker in nightmare disorder: A replication study.

Frequent nightmares are highly prevalent and constitute a risk factor for a wide range of psychopathological conditions. Despite its prevalence and clinical relevance however, the pathophysiological mechanisms of nightmares are poorly understood. A recent study (Perogamvros et, al 2019) examined the heart beat evoked potential (HEP) in a small group of nightmare sufferers (N = 11) and matched healthy controls (N = 11) and observed markedly different (Hedges' g = 1.42 [0.62-2.22]) HEP response across the groups during Rapid Eye Movement (REM) sleep. Moreover, the HEP correlated with depression scores in the nightmare group only. The authors concluded that the HEP in REM sleep could be used as a trait-like biomarker reflecting pathological emotional-and sleep regulation in nightmare disorder. To replicate the above study, we performed the same analyses of HEPs in two separate, and larger databases comprising the polysomnographic recordings of nightmare sufferers and matched controls (NStudy 1 = 39 ; NStudy 2 = 41). In contrast to the original findings, we did not observe significant differences in HEP across the two groups in either of the two databases. Moreover, we found no associations between depression scores and HEP amplitudes in the relevant spatiotemporal cluster. Our data cast doubts on the utility of HEP as a biomarker in the diagnostic and treatment procedures of nightmare disorder and suggests that the interpretation of HEP as a marker of impaired arousal and emotional processing during REM sleep is premature and requires further validation.

Sleep-spindle frequency: Overnight dynamics, afternoon nap effects, and possible circadian modulation.

Homeostatic and circadian processes play a pivotal role in determining sleep structure, timing, and quality. In sharp contrast with the wide accessibility of the electroencephalogram (EEG) index of sleep homeostasis, an electrophysiological measure of the circadian modulation of sleep is still unavailable. Evidence suggests that sleep-spindle frequencies decelerate during biological night. In order to test the feasibility of measuring this marker in common polysomnographic protocols, the Budapest-Munich database of sleep records (N = 251 healthy subjects, 122 females, age range: 4-69 years), as well as an afternoon nap sleep record database (N = 112 healthy subjects, 30 females, age range: 18-30 years) were analysed by the individual adjustment method of sleep-spindle analysis. Slow and fast sleep-spindle frequencies were characterised by U-shaped overnight dynamics, with highest values in the first and the fourth-to-fifth sleep cycle and the lowest values in the middle of the sleeping period (cycles two to three). Age-related attenuation of sleep-spindle deceleration was evident. Estimated phases of the nadirs in sleep-spindle frequencies were advanced in children as compared to other age groups. Additionally, nap sleep spindles were faster than night sleep spindles (0.57 and 0.39 Hz difference for slow and fast types, respectively). The fine frequency resolution analysis of sleep spindles is a feasible method of measuring the assumed circadian modulation of sleep. Moreover, age-related attenuation of circadian sleep modulation might be measurable by assessing the overnight dynamics in sleep-spindle frequency. Phase of the minimal sleep-spindle frequency is a putative biomarker of chronotype.