The clinical effectiveness of the Mind/Body Program for Infertility on wellbeing and assisted reproduction outcomes: a randomized controlled trial in search for active ingredients.

STUDY QUESTION: Does the Mind/Body Program for Infertility (MBPI) perform better, due to certain distinctive elements, than a partly matched support group in improving the wellbeing and medically assisted reproduction (MAR) outcomes of women with elevated distress levels in a clinical setting? SUMMARY ANSWER: While robust enhancements occurred in the wellbeing overall, the cognitive behavioural and formalized stress management elements of the MBPI allowed a significantly stronger improvement in trait anxiety, but not in other mental health and MAR outcomes, compared with a support group. WHAT IS KNOWN ALREADY: Mind-body psychological programmes adjacent to MAR have been found to improve women's mental states and possibly increase chances of pregnancy. However, not enough is known about the programme's effectiveness among patients with elevated distress levels in routine clinical settings, nor is it clear which of its particular ingredients are specifically effective. STUDY DESIGN, SIZE, DURATION: A pre-post design, single-centre, randomized controlled trial was performed between December 2019 and October 2022 (start and end of recruitment, respectively). The sample size (n = 168) was calculated to detect superiority of the MBPI in improving fertility-related quality of life. Randomization was computer-based, with random numbers concealing identities of patients until after allocation. PARTICIPANTS/MATERIALS, SETTING, METHODS: The trial was conducted at a large university teaching hospital. A total of 168 patients were randomly assigned to the mind-body (MBPI) group (n = 84) and the fertility support (FS) control group (n = 84). Patients received a 10-week, 135-min/week group intervention, with the FS group following the same format as the MBPI group, but with a less restricted and systematic content, and without the presumed effective factors. The number of patients analysed was n = 74 (MBPI) and n = 68 (FS) for post-intervention psychological outcomes, and n = 54 (MBPI) and n = 56 (FS) for pregnancy outcomes at a 30-month follow-up. MAIN RESULTS AND THE ROLE OF CHANCE: Significant improvements occurred in both groups in all psychological domains (adjusted P < 0.001), except for treatment-related quality of life. Linear mixed-model regression analysis did not reveal significantly greater pre-post improvements in the MBPI group than in the FS group in fertility-related quality of life (difference in differences (DD) = 4.11 [0.42, 7.80], d = 0.32, adjusted P = 0.124), treatment-related quality of life (DD = -3.08 [-7.72, 1.55], d = -0.20, adjusted P = 0.582), infertility-specific stress (DD = -2.54 [-4.68, 0.41], d = -0.36, adjusted P = 0.105), depression (DD = -1.16 [3.61, 1.29], d = -0.13, adjusted P = 0.708), and general stress (DD = -0.62 [-1.91, 0.68], d = -0.13, adjusted P = 0.708), but it did show a significantly larger improvement in trait anxiety (DD = -3.60 [-6.16, -1.04], d = -0.32, adjusted P = 0.042). Logistic regression showed no group effect on MAR pregnancies, spontaneous pregnancies, or live births. LIMITATIONS, REASONS FOR CAUTION: The follow-up only covered MAR-related medical outcomes and no psychological variables, and their rates were not equal in the two groups. Biological factors other than age, aetiology, and duration of infertility may have confounded the study results. Loss to follow-up was between 5% and 10%, which may have led to some bias. WIDER IMPLICATIONS OF THE FINDINGS: The psychologically and medically heterogeneous sample, the normal clinical setting and the low attrition rate all raise the external validity and generalizability of our study. The MBPI works not only in controlled conditions, but also in routine MAR practice, where it can be introduced as a cost-effective, low-intensity psychological intervention, within the framework of stepped care. More studies are needed to further identify its active ingredients. STUDY FUNDING/COMPETING INTEREST(S): The authors received no financial support for the research, authorship, and/or publication of this article. The authors have no conflict of interest to disclose. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov NCT04151485. TRIAL REGISTRATION DATE: 5 November 2019. DATE OF FIRST PATIENT'S ENROLMENT: 15 December 2019.

The SCREENIVF Hungarian version is a valid and reliable measure accurately predicting possible depression in female infertility patients.

Infertility patients, often in high distress, are entitled to being informed about their mental status compared to normative data. The objective of this study was to revalidate and test the accuracy of the SCREENIVF, a self-reported tool for screening psychological maladjustment in the assisted reproduction context. A cross-sectional, questionnaire-based online survey was carried out between December 2019 and February 2023 in a consecutive sample of female patients (N = 645, response rate 22.9%) in a university-based assisted reproduction center in Hungary. Confirmatory factor analysis and cluster and ROC analyses were applied to test validity, sensitivity and specificity in relation to Beck Depression Inventory (BDI) scores. Model fit was optimal (chi-square = 630.866, p < 0.001; comparative fit index = 0.99; root-mean-square error of approximation = 0.018 (90% CI 0.013-0.023); standardized-root-mean-square-residual = 0.044), and all dimensions were reliable (α > 0.80). A specific combination of cutoffs correctly predicted 87.4% of BDI-scores possibly indicative of moderate-to-severe depression (χ2(1) = 220.608, p < 0.001, Nagelkerke R2 = 0.462, J = 66.4). The Hungarian version of the SCREENIVF is a valid and reliable tool, with high accuracy in predicting BDI-scores. Low response rate may affect generalizability. The same instrument with different cutoffs can serve various clinical goals.

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.

Objective sleep quality predicts subjective sleep ratings.

In both clinical and observational studies, sleep quality is usually assessed by subjective self-report. The literature is mixed about how accurately these self-reports track objectively (e.g. via polysomnography) assessed sleep quality, with frequent reports of little to no association. However, previous research on this question focused on between-subject designs, which may be confounded by trait-level variables. In the current study, we used the novel Budapest Sleep, Experiences and Traits Study (BSETS) dataset to investigate if within-subject differences in subjectively reported sleep quality are related to sleep macrostructure and quantitative EEG variables assessed using a mobile EEG headband. We found clear evidence that self-reported sleep quality in the morning is influenced by within-subject variations in sleep onset latency, wake after sleep onset, total sleep time, and sleep efficiency. These effects were replicated if detailed sleep composition metrics (percentage and latency of specific vigilance states) or two alternative measures of subjective sleep quality were used instead. We found no effect of the number of awakenings or relative EEG delta and sigma power. Between-subject effects (relationships between individual mean values of sleep metrics and subjective sleep quality) were also found, highlighting that analyses focusing only on these may be erroneous. Our findings show that while previous investigations of this issue may have been confounded by between-subject effects, objective sleep quality is indeed reflected in subjective sleep ratings.

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.

Protocol of the Budapest sleep, experiences, and traits study: An accessible resource for understanding associations between daily experiences, individual differences, and objectively measured sleep.

Sleep is both a neurophysiological state and a biologically necessary behavior that performs a variety of indispensable roles for human health, development, and cognitive functioning. Despite this, comparatively little is known about the relationships between daily experiences and sleep features. Importantly, these relationships are bidirectional in nature, may be differently associated with subjectively and objectively assessed sleep, and may also be modulated by individual differences To address this challenge, we created the Budapest Sleep, Experiences, and Traits Study (BSETS), a multidisciplinary observational sleep study utilizing novel remote EEG devices. BSETS was designed to establish a dataset for future use in investigating the relationships between sleep features and daily experiences. In this paper we describe the protocol of the currently ongoing BSETS, which examines a community-dwelling sample of over 250 healthy participants who are studied in a naturalistic setting using a large questionnaire assessing psychological, demographic, and anthropometric information, as well as evening/morning diaries of sleep and daily experiences, and mobile EEG recordings over a period of 7 days. This dataset will become an accessible resource to the wider scientific community and can be utilized to investigate the complex multidirectional relationships between objectively and subjectively measured sleep, daily experiences, and individual differences, bestowing it with significant value for sleep researchers as well as practitioners working in clinical settings with patients suffering from disordered sleep.

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.

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.

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.

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.

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.

Genetic effects on educational attainment in Hungary.

INTRODUCTION: Educational attainment is a substantially heritable trait, and it has recently been linked to specific genetic variants by genome-wide association studies (GWASs). However, the effects of such genetic variants are expected to vary across environments, including countries and historical eras. METHODS: We used polygenic scores (PGSs) to assess molecular genetic effects on educational attainment in Hungary, a country in the Central Eastern European region where behavioral genetic studies are in general scarce and molecular genetic studies of educational attainment have not been previously published. RESULTS: We found that the PGS is significantly associated with the attainment of a college degree as well as the number of years in education in a sample of Hungarian study participants (N = 829). PGS effect sizes were not significantly different when compared to an English (N = 976) comparison sample with identical measurement protocols. In line with previous Estonian findings, we found higher PGS effect sizes in Hungarian, but not in English participants who attended higher education after the fall of Communism, although we lacked statistical power for this effect to reach significance. DISCUSSION: Our results provide evidence that polygenic scores for educational attainment have predictive value in culturally diverse European populations.

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.

The overlapping geography of cognitive ability and chronotype.

Chronotype and cognitive ability are two human phenotypes with an uneven geographic distribution due to both selective migration and causal environmental effects. In our study, we aimed to examine the relationship between geographic variables, cognitive ability and chronotype. We used a large anonymized sample (n = 25,700, mostly from the USA, UK, Canada and Australia) of dating site users to estimate chronotype and cognitive ability from questionnaire responses using item response theory. We matched each user to geographic coordinates and city size using the reported locations and geographic databases. In line with previous research we found that male sex, younger age, residence in a more populous locale, higher cognitive ability and more westward position within the same time zone were associated with later chronotype. Male sex, younger age, residence in a more populous locale, later chronotype and higher latitude were associated with higher cognitive ability, but the effect of population on chronotype and latitude on cognitive ability was only present in the USA. The relationship between age and chronotype was stronger in males, and the relationship between chronotype and cognitive ability was stronger in males and in older participants. Population density had an independent association with cognitive ability, but not chronotype. Our results confirm the uneven geographic distribution of chronotype and cognitive ability. These findings generalize across countries, but they are moderated by age and sex, suggesting both biological and cultural effects.

Circadian preference and intelligence - an updated meta-analysis.

A large number of previous studies reported a link between circadian preference and psychometric intelligence with mixed results and various hypotheses about the source of this correlation. In this study, we aimed to update a previous meta-analysis about the correlation between circadian preference and intelligence. Our literature search identified a large number of new studies, resulting in an increase of over 100% in the number of studies and over 400% in the number of involved participants (total k = 30, total N = 11160) over the previous meta-analysis, sampling a much wider age range from children to adults in late middle age. Our meta-analysis revealed no significant link between morningness and intelligence (r = -0.008) when the entire sample was studied, and no evidence for publication bias. This overall effect, however, obscured the moderating effect of age. The morningness-intelligence correlation decreased with mean sample age (R2 = 54%), ranging from a non-significant positive trend in children and adolescents to a significant negative correlation after young adulthood. Eveningness was positively correlated with intelligence (r = 0.056), but this finding is based on a more age-restricted sample and only reached significance with some model specifications. We hypothesize that the age-moderated correlation between circadian preference and intelligence reflects social effects, where more intelligent individuals are more able to adjust their daily schedules to their natural circadian rhythm.

REM Sleep Microstates in the Human Anterior Thalamus.

Rapid eye movement (REM) sleep is an elusive neural state that is associated with a variety of functions from physiological regulatory mechanisms to complex cognitive processing. REM periods consist of the alternation of phasic and tonic REM microstates that differ in spontaneous and evoked neural activity. Although previous studies indicate, that cortical and thalamocortical activity differs across phasic and tonic microstates, the characterization of neural activity, particularly in subcortical structures that are critical in the initiation and maintenance of REM sleep is still limited in humans. Here, we examined electric activity patterns of the anterior nuclei of the thalamus as well as their functional connectivity with scalp EEG recordings during REM microstates and wakefulness in a group of epilepsy patients (N = 12, 7 females). Anterothalamic local field potentials (LFPs) showed increased high-α and ß frequency power in tonic compared with phasic REM, emerging as an intermediate state between phasic REM and wakefulness. Moreover, we observed increased thalamocortical synchronization in phasic compared with tonic REM sleep, especially in the slow and fast frequency ranges. Wake-like activity in tonic REM sleep may index the regulation of arousal and vigilance facilitating environmental alertness. On the other hand, increased thalamocortical synchronization may reflect the intrinsic activity of frontolimbic networks supporting emotional and memory processes during phasic REM sleep. In sum, our findings highlight that the heterogeneity of phasic and tonic REM sleep is not limited to cortical activity, but is also manifested by anterothalamic LFPs and thalamocortical synchronization.SIGNIFICANCE STATEMENT REM sleep is a heterogeneous sleep state that features the alternation of two microstates, phasic and tonic rapid eye movement (REM). These states differ in sensory processing, awakening thresholds, and cortical activity. Nevertheless, the characterization of these microstates, particularly in subcortical structures is still limited in humans. We had the unique opportunity to examine electric activity patterns of the anterior nuclei of the thalamus (ANTs) as well as their functional connectivity with scalp EEG recordings during REM microstates and wakefulness. Our findings show that the heterogeneity of phasic and tonic REM sleep is not limited to cortical activity, but is also manifested in the level of the thalamus and thalamocortical networks.