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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 Hungarians 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 and sexual 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.

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 β 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.

Sleep is an inherent feature of human neurobehavioral functioning. However, clinical and research practices largely rely on consensual criteria of sleep-wake characterization. In turn, quantitative EEG measures were shown to be largely redundant and non-standardizable. We aim to transcend this issue by relying on the parametrization of NREM sleep EEG based on the power law scaling of the Fourier spectra (scale-free and oscillatory measures). We hypothesize that spectral slopes are characterized by sufficient convergent and criterion validity in order to be considered as alternative and more standardizable measures of sleep intensity, whereas spectral peak frequencies reveal a U-shaped overnight distribution indicating putative circadian influences. Findings indicate that spectral slopes flatten over successive sleep cycles, reproduce known age and region-effects, correlating reliably with slow wave activity (SWA). Furthermore, its interindividual variability was proven to be less than of SWA. Frequency of the largest peak was shown to roughly correspond to spindle frequency as the known age, sex, and regional effects were evident. Besides, the peak frequencies in the frontopolar region were compatible with an assumed circadian modulation. In conclusion, the appropriate parameterization of the NREM sleep EEG Fourier spectra reliably reflects processes proposed in the two-process model of sleep regulation.

General cognitive ability — or intelligence — is a key psychological phenotype. Individual differences in intelligence may either cause or be a consequence of individual differences in the macrostructure of sleep, such as timing or duration. Furthermore, biological measures of sleep, especially highly trait-like sleep EEG oscillations may provide insights about the biological underpinnings of intelligence. Here we review the current state of research on the association between sleep measures and intelligence. We concluded that the macrostructure of sleep has a small but consistent correlation with intelligence, which is possibly moderated by age. Sleep spindle amplitude and possibly other sleep EEG measures are biomarkers of intelligence. We close by discussing methodological pitfalls of the field, and give recommendations for future directions.

Sleep-wake patterns show substantial biological determination, but they are also subject to individual choice and societal pressure. Some evidence suggests that high IQ is associated with later sleep patterns. However, it is unclear whether the relationship between IQ and later sleep is due to biological or social effects, such as the timing of working hours. We investigated the association between habitual sleep timing during work days and work-free days, working time and membership in Mensa, an organization of highly intelligent individuals (IQ ≥130) using a sample of 1,172 adults split between Mensa members and age- and sex-matched volunteers from a large web-based database. We found no difference in chronotype, and the later sleep timing of Mensa members on work days was fully accounted for by later work start times. Our results indicate that later sleep timing in those with higher IQs is not due to physiological differences, but rather due to later work schedules. Later working times and the resulting lower social jetlag may be one of the reasons why higher IQ is associated with lower prospective morbidity and mortality.

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.

Sleep EEG reflects instantaneous voltage differences relative to a reference, while its spectrum reflects the degree to which it is comprised of oscillations at various frequencies. In contrast, the envelope of the sleep EEG reflects the instantaneous amplitude of oscillations at specific frequencies, and its spectrum reflects the rhythmicity of the occurrence of these oscillations. The ordinary sleep EEG and its spectrum have been extensively studied and its individual stability and relationship to various demographic characteristics, psychological traits and pathologies is well known. In contrast, the envelope spectrum has not been extensively studied before. In two studies, we explored the generating mechanisms and utility of studying the envelope of the sleep EEG. First, we used human invasive data from cortex-penetrating microelectrodes and subdural grids to demonstrate that the sleep EEG envelope spectrum reflects local neuronal firing. Second, we used a large database of healthy volunteers to demonstrate that the scalp EEG envelope spectrum is highly stable within individuals, especially in NREM sleep, and that it is affected by age and sex. Multivariate models based on a learning algorithm could predict both age (r=0.6) and sex (r=0.5) with considerable accuracy from the EEG envelope spectrum. With age, oscillations characteristically shifted from a 4-5 second rhythm to higher rhythms. The envelope spectrum was not associated with general cognitive ability (IQ). Our results demonstrate that the sleep envelope spectrum is a promising, neuronal firing-based biomarker of various demographic and disease-related phenotypes.

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., We found that polygenic scores (PGS) associated with educational attainment (EA) in an international genome‐wide association study are also associated with EA in Hungary, despite historic, societal and economic differences between this country and those in which the PGS was discovered. Our results demonstrate the general validity of the PGS.

We report on a peculiar way of chronic cognitive impairment associated with interictal epileptic activity during NREM sleep. We review three major groups of epilepsy: mesiotemporal epilepsy (MTLE) involving the epileptic derailment of the hippocampal declarative memory system; childhood developmental epileptic encephalopathies; and the spectrum disorders of the perisylvian communication network with the centrotemporal spike phenomenon, overarching child- and adulthood epilepsies, totaling up the majority of epilepsies in childhood. We outline high impact research-lines on the cognitive harm of epilepsy; causing specific or global cognitive decline through its interference with sleep plastic functions. We highlight the key role of interictal activity in the development of cognitive impairment and the fact that we are unarmed against this harm, antiepileptic pharmaco-therapy being ineffective against the interictal process marked by spikes and high frequency oscillations.

Sleep spindles are major oscillatory components of Non-Rapid Eye Movement (NREM) sleep, reflecting hyperpolarization-rebound sequences of thalamocortical neurons, the inhibition of which is caused by the NREM-dependent activation of GABAergic neurons in the reticular thalamic nucleus. Reports suggest a link between sleep spindles and several forms of interictal epileptic discharges (IEDs) 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, IEDs 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 Deep Brain Stimulation protocol. Slow (∼12 Hz) and fast (∼14 Hz) sleep spindles were present in the human ANT and MD. Roughly, one third of thalamic sleep spindles were associated with IEDs or ripples. Both IED- and ripple-associated spindles were longer than pure spindles. IED-associated thalamic sleep spindles were characterized by broadband increase in thalamic and cortical activity, both below and above the spindle frequency range, whereas ripple-associated thalamic spindles exceeded pure spindles in terms of 80–200 Hz thalamic, but not cortical activity as indicated by time-frequency analysis. These result show that thalamic spindles coupled with IEDs are reflected at the scalp slow and beta-gamma oscillation as well. IED density during sleep spindles in the MD, but not in the ANT was identified as correlates of years spent with epilepsy, whereas 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 general intelligence. Our findings indicate the complex and multifaceted role of the human thalamus in sleep spindle-related physiological and pathological neural plasticity.

Homeostatic and circadian processes play a pivotal role in determining sleep structure, timing and quality. In sharp contrast with the wide accessibility of the EEG index of sleep homeostasis, an electrophysological measure of the circadian modulation of sleep is still non-available. 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 characterized 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 2–3). 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.

Chronotype and cognitive ability are two psychological phenotypes with an uneven geographical distribution due to both selective migration and causal environmental effects. In our study we aimed to unravel the relationship between geographical variables, cognitive ability and chronotype. We used a large anonymized sample (N=25700) of dating site users to estimate chronotype and cognitive ability from questionnaire responses using item response theory. We matched each user to geographical coordinates and city size using the reported locations and geographical databases. In line with previous research we found that male sex (β=0.029), younger age (β=-0.178), residence in a more populous locale (β=0.02), higher cognitive ability (β=0.05) and more westward position within the same time zone (β=-0.04) was associated with later chronotype. Male sex (β=0.065), younger age (β=-0.04), residence in a more populous locale (β=0.149), later chronotype (β=0.051) and higher latitude (β=0.03) was associated with higher cognitive ability, but the effect of population on chronotype and latitude on cognitive ability was only present in the United States. 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 geographical distribution of chronotype and cognitive ability. Country-wise analyses distinguish universal cultural/biological and country-specific effects. The moderating effect of age on the cognitive ability-chronotype relationship suggests that cultural rather than biological effects underlie this relationship.

Features of sleep were shown to reflect aging, typical sex differences and cognitive abilities of humans. However, these measures are characterized by redundancy and arbitrariness. Our present approach relies on the assumptions that the spontaneous human brain activity as reflected by the scalp-derived electroencephalogram (EEG) during non-rapid eye movement (NREM) sleep is characterized by arrhythmic, scale-free properties and is based on the power law scaling of the Fourier spectra with the additional consideration of the rhythmic, oscillatory waves at specific frequencies, including sleep spindles. Measures derived are the spectral intercept and slope, as well as the maximal spectral peak amplitude and frequency in the sleep spindle range, effectively reducing 191 spectral measures to 4, which were efficient in characterizing known age-effects, sex-differences and cognitive correlates of sleep EEG. Future clinical and basic studies are supposed to be significantly empowered by the efficient data reduction provided by our approach.

In two recent reviews (Geary 2018, 2019), Geary attributed a substantial role in generating individual differences in the general factor of intelligence, g, to mitochondrial functioning [...]

The aim of this review is to summarize and discuss the strong bond between NREM sleep and epilepsy underlain by the shared link and effect on brain plasticity. Beyond the seizure occurrence rate, sleep relatedness may manifest in the enhancement of interictal epileptic discharges (spikes and pathological ripples). The number of the discharges as well as their propagation increase during NREM sleep, unmasking the epileptic network that is hidden during wakefulness. The interictal epileptic discharges associate with different sleep constituents (sleep slow waves, spindling and high frequency oscillations); known to play essential role in memory and learning. We highlight three major groups of epilepsies, in which sleep-related plastic functions suffer an epileptic derailment. In absence epilepsy mainly involving the thalamo-cortical system, sleep spindles transform to generalized spike-wave activity. In mesio-temporal epilepsy affecting the hippocampal declarative memory system, the sharp wave ripples derail to dysfunctional epileptic oscillations (spikes and pathological ripples). Idiopathic childhood epilepsies affecting the perisylvian network may progress to catastrophic status electricus during NREM sleep. In these major epilepsies, NREM sleep has a pivotal role in the development and course of the disorder. Epilepsy is born in-, and exhibits its pathological properties during NREM sleep. Interictal discharges are important causative agents in this process.

Sleep spindles are EEG oscillations in NREM sleep which are implicated in sleep-related cerebral plasticity. Several studies indicate that sleep spindle characteristics are correlates of general cognitive ability with a possible sexual dimorphism, but most of the literature consists of small studies with heterogeneous results. In order to clarify these findings, we conducted the largest study into this topic (N = 176) in a birth cohort of 17 year old adolescents using all-night polysomnography and two different sleep spindle detectors. We failed to find significant associations between sleep spindle parameters and general cognitive ability. There was no evidence for a sexual dimorphism. Our findings suggest that previous small studies with limited statistical power and probability to sampling error may have detected sporadic associations which were not confirmed in this study. Large studies and meta-analyses, still somewhat uncommon in the quantitative EEG studies of psychological phenotypes, are necessary to evaluate the existing literature.

Variations in the anatomical and functional connectivity between brain areas underlie both healthy and pathological variation in psychological measures. Largely independent from external stimuli, the sleep EEG is particularly well suited to measure individual variations in functional brain connectivity. In this study of 172 healthy individuals (17–69 years old), we show that functional connectivity between distant brain areas—reflected by the weighted phase lag index of the sleep EEG—is strongly affected by the age and sex of participants. Both NREM and REM connectivity in the theta and beta range increased with age, whereas a decrease was seen in the sigma range. Connectivity was substantially greater in females than in males in the high sigma frequency range, but an opposite pattern was seen in the alpha/low sigma and beta range. General intelligence was not significantly associated with connectivity in either sex. Our results confirm strong age effects on sleep spindle-frequency activity, which loses synchrony as a function of aging. Furthermore, we found support for a vigilance state–independent age-related increase in high beta power, previously demonstrated in waking EEG studies. The results highlight that future studies establishing sleep EEG connectivity measures as psychological or psychiatric biomarkers should take into account that sleep EEG synchronization is strongly affected by age and sex, and clinical thresholds must be adjusted accordingly.

Slow waves recorded with EEG in NREM sleep are indicative of the strength and spatial extent of synchronized firing in neuronal assemblies of the cerebral cortex. Slow waves often appear in the A1 part of the cyclic alternating patterns (CAP), which correlate with a number of behavioral and biological parameters, but their physiological significance is not adequately known. We automatically detected slow waves from the scalp recordings of 37 healthy patients, visually identified CAP A1 events and compared slow waves during CAP A1 with those during NCAP. For each slow wave, we computed the amplitude, slopes, frequency, synchronization (synchronization likelihood) between specific cortical areas, as well as the location of origin and scalp propagation of individual waves. CAP A1 slow waves were characterized by greater spatial extent and amplitude, steeper slopes and greater cortical synchronization, but a similar prominence in frontal areas and similar propagation patterns to other areas on the scalp. Our results indicate that CAP A1 represents a period of highly synchronous neuronal firing over large areas of the cortical mantle. This feature may contribute to the role CAP A1 plays in both normal synaptic homeostasis and in the generation of epileptiform phenomena in epileptic patients.

Females and males differ in several features of their spindle oscillations, as well as in the hemispheric lateralization of their neurocognitive processes. In addition, the hemispheric lateralization of cognitive functions was shown to vary in an age-dependent manner. In spite of the above knowledge, data on the hemispheric lateralization of these oscillatory phenomena are scarce and no sex differences or age effects in the hemispheric lateralization of sleep spindles were reported. Here, we aim to fill this gap by the description of the hemispheric lateralization of sleep spindles in healthy human subjects. Data sets from three research groups were unified (N = 251, age range: 4−69 years, 122 females) in this retrospective multicenter study. The amplitude, density, and duration of slow (frontally dominant) and fast (centroparietally dominant) spindles were analyzed using the individual adjustment method. Hemispheric lateralization was quantified by the (L − R)/mean (L, R) index. Orbitofronto-temporo-occi...

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. 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. We found that the PGS is significantly associated with highest educational level attained as well as the number of years in education in a sample of Hungarian volunteers (N=829). In an English (N=976) comparison sample with identical measurement protocols the same PGS had a stronger association with educational level, but not with years in education. 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. Our results provide evidence that polygenic scores for educational attainment are valid in diverse European populations.

Sleep-wake patterns show substantial biological determination, but they are also subject to individual choice and societal pressure. Some evidence suggests that high IQ is associated with later sleep patterns. However, t is therefore unclear whether the relationship between IQ and later sleep is due to biological or social effects, such as timing and flexibility of working hours. We investigated the association between habitual sleep timing during work days and work-free days, working time and intelligence in a sample of 1,172 adults. We found no difference in chronotype, and the later sleep timing of high-IQ individuals on work days was fully accounted for by later work start times.Our results indicate that later sleep timing in those with higher IQs is not due to physiological differences, but rather due to later or more flexible work schedules. Later working times and the resulting lower social jetlag may be one of the reasons why higher IQ is associated with lower prospective morbidity and mortality.Statement of significanceSome evidence shows that higher intelligence is associated with sleep characteristics, but it is unclear if this is because of biological or social mechanisms. We provide evidence for a social mechanism. We found that high IQ individuals indeed sleep later, but only on working days, and this difference is fully accounted for by later work timing. Our evidence is consistent with a view that highly intelligent individuals sleep later because they can afford to, consequently experience lower social jetlag, and this may partially account for better health outcomes.

Sleep spindles are generated in thalamocortical, corticothalamic and possibly cortico-cortical circuits. Previous hypotheses suggested that slow and fast spindles or spindles with various spatial extent may be generated in different circuits with various cortical laminar innervation patterns. We used NREM sleep EEG data recorded from four human epileptic patients undergoing presurgical electrophysiological monitoring with subdural electrocorticographic grids (ECoG) and implanted laminar microelectrodes penetrating the cortex (IME). The position of IME electrodes within cortical layers was confirmed using postsurgical histological reconstructions. Many micro-domain spindles detected on the IME occurred only in one layer and were absent from the ECoG, but with increasing amplitude simultaneous detection in other layers and on the ECoG became more likely. Macro-domain spindles sufficiently large to be detected on the ECoG were in contrast usually accompanied by IME spindles. Neither micro-domain nor macro-domain spindle cortical profiles were strongly associated with sleep spindle frequency or globality. Multiple-unit and single-unit activity during spindles, however, was heterogeneous across spindle types, but also across layers and subjects. Our results indicate that extremely local spindles may occur in any cortical layer, but co-occurrence at other locations becomes likelier with increasing amplitude and the relatively large spindles detected on ECoG channels have a stereotypical laminar profile. We found no compelling evidence that different spindle types are associated with different laminar profiles, suggesting that they are generated in cortical and thalamic circuits with similar cortical innervation patterns. Local neuronal activity is a stronger candidate mechanism for driving functional differences between spindles subtypes.

Slow wave sleep (SWS) is characterized by the predominance of delta waves and slow oscillations, reflecting the synchronized activity of large cortical neuronal populations. Amongst other functions, SWS plays a crucial role in the restorative capacity of sleep. Rhythmic acoustic stimulation (RAS) during SWS has been shown a cost-effective method to enhance slow wave activity. Slow wave activity can be expressed in a region-specific manner as a function of previous waking activity. However, it is unclear whether slow waves can be enhanced in a region-specific manner using RAS. We investigated the effects of unilaterally presented rhythmic acoustic sound patterns on sleep electroencephalographic (EEG) oscillations. Thirty-five participants received during SWS 12-second long rhythmic bursts of pink noise (at a rate of 1 Hz) that alternated with non-stimulated, silent periods, unilaterally delivered into one of the ears of the participants. As expected, RAS enhanced delta power, especially in its low-frequency components between 0.75 and 2.25 Hz. However, increased slow oscillatory activity was apparent in both hemispheres regardless of the side of the stimulation. The most robust increases in slow oscillatory activity appeared during the first 3-4 seconds of the stimulation period. Furthermore, a short-lasting increase in theta and sigma power was evidenced immediately after the first pulse of the stimulation sequences. Our findings indicate that lateralized RAS has a strong potential to globally enhance slow waves during daytime naps. The lack of localized effects suggests that slow waves are triggered by the ascending reticular system and not directly by specific auditory pathways.

Slow-wave activity is a hallmark of deep non-rapid eye movement sleep. Scalp slow wave morphology is stereotypical and it is highly correlated with the synchronized onset and cessation of cortical neuronal firing measured from the surface or depth of the cortex. It is also strongly affected by aging, and these changes are causally associated with age-related cognitive decline. We investigated how normal aging affects the individual morphology of the slow wave and whether these changes are captured by the summary slow wave parameters generally used in the literature. We recorded full-night polysomnography in 176 participants (age 17–69 years) and automatically detected slow waves. We established individual slow morphologies using average amplitude at 501 data points for each participant and also calculated the individual average slow-wave amplitude, average ascending and descending slope steepness, halfwave duration, and the total number of slow waves (gross parameters). Using least absolute shrinkage and selection operator penalized regression, we found that SW gross parameters explain up to 60% of age variance but using fine morphology up to 80% of age variance can be accounted for. This predictive power was greatest when data from multiple channels were averaged, in midline derivations and in the first quarter of the night. Young participants had faster slow-wave polarity reversals, suggesting a more efficient initiation and termination of slow-wave downstate and upstate. Our results demonstrate the superiority of the high-resolution slow wave morphology as a biomarker of aging and highlight downstate-upstate transitions as promising targets of restorative stimulation-based interventions.

Epileptiform activity in various but not all epilepsy and recording types and cerebral areas is more frequent in NREM sleep, and especially during sleep periods with high-amplitude EEG slow waves. Slow waves synchronize high-frequency oscillations: physiological activity from the theta through the gamma band usually appears during scalp-positive upstates while epileptiform activity occurs at transitory phases and the scalp-negative downstate. It has been proposed that interictal discharges (IIDs) are facilitated by the high degree of neuronal firing synchrony during slow wave transitory and downstates. This would suggest that their occurrence increases as a function of slow wave synchronization, indicated by greater amplitude, steeper slopes and higher EEG signal synchronization. We investigated the occurrence of IIDs during NREM sleep slow waves in epileptic patients undergoing presurgical electrophysiological monitoring. Intracranially registered IIDs preferentially occurred during the scalp-negative downstates of frontal scalp slow waves in all subjects. IID occurrence was more frequent during larger slow waves in the pooled sample and a subset of subjects. However, slow wave slope steepness and EEG signal synchronization between two frontal scalp channels was not significantly associated with IID occurrence. Our results indicate that IIDs indeed do not occur at the same slow wave phase as physiological rhythms, but contrary to previous hypotheses their occurrence is not strongly affected by EEG synchronization.

Non-rapid eye movement (NREM) sleep is characterized by recurring transient events (Cyclic Alternating Patterns, CAP), some of which consist of increased slow wave activity (A1 subtype). Such transient slow-wave events may play an important role in NREM sleep regulation and are known to facilitate epileptiform activity. In our study we investigated the relationship between interictal spike activity and Cyclic Alternating Patterns in three epileptic patients, using simultaneous scalp electroencephalogram (EEG) recording and intracranial electrocorticography. A significant increase of interictal activity was found during CAP A1 subtypes. A positive correlation between scalp EEG delta power and spike activity was found only in CAP A1 subtypes, but not during other events. These results show that transient (but not subcontinuous) delta activity has a facilitating effect on epileptoform activity, also suggesting a functional dissociation between morphologically similar delta activities.

The shape of the EEG spectrum in sleep relies on genetic and anatomical factors and forms an individual “EEG fingerprint”. Spectral components of EEG were shown to be connected to mental ability both in sleep and wakefulness. EEG sleep spindle correlates of intelligence, however, exhibit a sexual dimorphism, with a more pronounced association to intelligence in females than males. In a sample of 151 healthy individuals, we investigated how intelligence is related to spectral components of full-night sleep EEG, while controlling for the effects of age. A positive linear association between intelligence and REM anterior beta power was found in females but not males. Transient, spindle-like “REM beta tufts” are described in the EEG of healthy subjects, which may reflect the functioning of a recently described cingular-prefrontal emotion and motor regulation network. REM sleep frontal high delta power was a negative correlate of intelligence. NREM alpha and sigma spectral power correlations with intelligence did not unequivocally remain significant after multiple comparisons correction, but exhibited a similar sexual dimorphism. These results suggest that the neural oscillatory correlates of intelligence in sleep are sexually dimorphic, and they are not restricted to either sleep spindles or NREM sleep.

Sleep spindles act as a powerful marker of individual differences in cognitive ability. Sleep spindle parameters correlate with both age-related changes in cognitive abilities and with the age-independent concept of IQ. While some studies have specifically demonstrated the relationship between sleep spindles and intelligence in young children, our previous work in older subjects revealed sex differences in the sleep spindle correlates of IQ, which was never investigated in small children before. We investigated the relationship between age, Raven Colored Progressive Matrices (CPM) scores and sleep spindles in 28 young children (age 4-8 years, 15 girls). We specifically investigated sex differences in the psychometric correlates of sleep spindles. We also aimed to separate the correlates of sleep spindles that are because of age-related maturation from other effects that reflect an age-independent relationship between sleep spindles and general intelligence. Our results revealed a modest positive correlation between fast spindle amplitude and age. Raven CPM scores positively correlated with both slow and fast spindle amplitude, but this effect remained a tendency in males and vanished after correcting for the effects of age. Age-corrected correlations between Raven CPM scores and both slow and fast spindle amplitude were only significant in females. Overall, our results show that in male children sleep spindles are a maturational marker, but in female children they indicate trait-like intelligence, in line with previous studies in adolescent and adult subjects. Thalamocortical white matter connectivity may be the underlying mechanism behind both higher spindle amplitude and higher intelligence in female, but not male subjects. (PsycINFO Database Record

The Pittsburgh Sleep Quality Index is used to evaluate subjective sleep quality, and it is commonly used in clinical research. Subjective sleep quality is also an important clinical measure in patients with psychiatric disorders. The aim of the present study was to evaluate the reliability and validity of the Hungarian version of the Pittsburgh Sleep Quality Index (PSQI-HUN) in both clinical and non-clinical samples. The original version of PSQI was translated into Hungarian according to standard guidelines. The PSQI-HUN and the Athens Insomnia Scale (AIS) were subsequently administered to 53 psychiatric patients (schizophrenia, recurrent depressive disorder, mixed anxiety, and depressive disorder) and 178 healthy controls. Internal consistency as measured by Cronbach’s alpha in the whole sample was 0.79. Pearson’s product-moment correlations between component scores and the global scores were high (0.59–0.88) in the PSQI-HUN indicating the homogeneity of the scale. PSQI-HUN global and component scores differed significantly between psychiatric patients and control subjects. In the psychiatric patient subsample, schizophrenics had lower global scores compared to the other two patient groups. The analysis of convergent validity showed significant correlations between the AIS and the global as well as the component scores of the PSQI-HUN (except the component of sleep latency). The present study concludes that the PSQI-HUN is a reliable, valid, and standardized measure for assessment of the subjective sleep quality in clinical and research settings.

Sleep spindles are frequently studied for their relationship with state and trait cognitive variables, and they are thought to play an important role in sleep-related memory consolidation. Due to their frequent occurrence in NREM sleep, the detection of sleep spindles is only feasible using automatic algorithms, of which a large number is available. We compared subject averages of the spindle parameters computed by a fixed frequency (FixF) (11-13 Hz for slow spindles, 13-15 Hz for fast spindles) automatic detection algorithm and the individual adjustment method (IAM), which uses individual frequency bands for sleep spindle detection. Fast spindle duration and amplitude are strongly correlated in the two algorithms, but there is little overlap in fast spindle density and slow spindle parameters in general. The agreement between fixed and manually determined sleep spindle frequencies is limited, especially in case of slow spindles. This is the most likely reason for the poor agreement between the two detection methods in case of slow spindle parameters. Our results suggest that while various algorithms may reliably detect fast spindles, a more sophisticated algorithm primed to individual spindle frequencies is necessary for the detection of slow spindles as well as individual variations in the number of spindles in general.

Contains fulltext : 152518.pdf (Publisher’s version ) (Open Access) Sleep spindles are thalamocortical oscillations in non-rapid eye movement (NREM) sleep, that play an important role in sleep-related neuroplasticity and offline information processing. Several studies with full-night sleep recordings have reported a positive association between sleep spindles and fluid intelligence scores, however more recently it has been shown that only few sleep spindle measures correlate with intelligence in females, and none in males. Sleep spindle regulation underlies a circadian rhythm, however the association between spindles and intelligence has not been investigated in daytime nap sleep so far. In a sample of 86 healthy male human subjects, we investigated the correlation between fluid intelligence and sleep spindle parameters in an afternoon nap of 100 minutes. Mean sleep spindle length, amplitude and density were computed for each subject and for each derivation for both slow and fast spindles. A positive association was found between intelligence and slow spindle duration, but not any other sleep spindle parameter. As a positive correlation between intelligence and slow sleep spindle duration in full-night polysomnography has only been reported in females but not males, our results suggest that the association between intelligence and sleep spindles is more complex than previously assumed.

Sleep spindles are generated in thalamocortical circuits. Thalamocortical projections can be classified as one of two main types: a “core” network consisting of spatially concentrated projections terminating in cortical layer IV, and a “matrix” network with more diffuse projections, terminating in the superficial cortical layers. It has been hypothesized that sleep spindles can be generated in both systems, but localized spindles are preferentially generated in the “core” system and global spindles in the “matrix system”. Our analysis of laminar microelectrode recordings during ECoG spindles indeed reveals that current source density (CSD) is maximal in layer I-II and IV, consistent with the anatomy of the hypothesized “core” and “matrix” networks. However, CSD is prominent at both depths in both local and global spindles, and CSD magnitude is strongly correlated between superficial layers and layer IV (although less so in local spindles). Fast spindles slow relatively greater CSD in layer IV and slow spindles in superficial layers. Sleep spindles are associated with several neurobehavioral markers, such as memory consolidation, cognitive ability and disease phenotypes. These associations, however, were mainly found with fast spindles. Centroparietal fast spindles also appear more prominently in EEG recordings and leave more prominent spectral peaks. While neither slow nor fast spindles rely exclusively on both “core” and “matrix” thalamocortical projections, it is likely that spatially focused “core” projections to layer IV are especially significant for sleep spindle function due to their role in fast spindle generation.

NREM sleep slow waves reflect both the temporal dynamics of the synchronized onset and cessation of cortical neuron firing and the spatial extent of this synchronized firing pattern. This synchronization is crucially dependent on synaptic strength, and the renormalization of synaptic changes occurring in wakefulness is thought to be one of the main functions of NREM sleep. In line with this hypothesis, slow waves are more frequent, larger and steeper in cases when the synaptic load is high and the need for homeostatic synaptic renormalization is strong: early in the night, in younger subjects with greater neural plasticity and after prolonged or more intensive wakefulness. Slow waves exhibit substantial heterogeneity and may contribute to these processes to a differing degree. In NREM sleep, series of large-amplitude slow waves (Cyclic Alternating Pattern [CAP] A1) sometimes appear, either spontaneously with predictably cyclicity or after sensory stimulation. Slow waves in CAP A1 resemble slow waves normally recorded under high homeostatic sleep pressure: they are characterized by a greater spatial extent, larger amplitude, steeper slopes (even when correcting for amplitude) and higher EEG synchronization, even though their topography and propagation patterns are similar to ordinary (non-CAP) slow waves. These results indicate that CAP A1 represents a period of highly synchronous neuronal firing over large areas of the cortical mantle. This feature may contribute to the role CAP A1 plays in both normal synaptic homeostasis and – through greater synchronization – in the generation of epileptiform phenomena in epileptic patients.

Introduction Sleep spindles are generated in thalamo-cortical networks. Thalamo-cortical projections include core projections to middle and matrix projections to superficial cortical layers. It has been proposed that sleep spindles can be generated in either of these networks. Materials and methods We used electrophysiological data recorded with subdural grid and intracortical multielectrodes in five therapy-resistant epileptic patients undergoing invasive monitoring. Spindles were detected automatically in electrocorticography channels and detection-triggered laminar microelectrode recordings were analyzed. The second spatial derivative of spindle-band filtered (band pass 10–16 Hz, 96 dB) local field potential data allowed to approximate the laminar distribution of the transmembrane generators (current source density, CSD) of spindles. The information regarding the concurrent population cellular activity was obtained by applying a high frequency band filter (500–5000 Hz, 48 dB) on epoched data. Based on the histological reconstructions of laminar electrode tracks, we could identify the precise laminar localization of current sources and sinks. Results Results indicate highly heterogeneous intracortical local field potentials during sleep spindles, and maximum CSD in layer I, II and IV. Multi-unit activity was increased in spindle troughs as it was identified based on the spindle band filtered local field potentials. The single unit analyis revealed preferential firing of most neurons during the positive-negative phase transition of spindles. Conclusions The results confirm that both core and matrix thalamocortical projections contribute to spindle generation, but most spindles appear to be generated by a combination of the two and only a small minority by only one or the other. Neuronal firing tracks the phase of spindles in corticographic channels. Supported by KTIA_NAP_13-1-2013-0001.

Introduction Deep brain stimulation of anterior nucleus of the thalamus (ANT-DBS) is an approved therapeutic approach for drug resistant epilepsy. Little is known about the participation of ANT in epileptic and sleep EEG processes. The appearance of the sleep spindles (SS) is related to interictal discharges (IID), and thalamus is considered as the generator of SSs, however, according to animal data, ANT do not participate in the genesis of sleep spindles. Methods In this present study we included 10 ANT-DBS bitemporal epilepsy patients with externalised leads and surface electrodes undergoing 2 days video-EEG monitoring (VEM). We investigated IIDs, ictal events (IE) and SSs in ANT and also in surface EEG recordings. IIDs and IEs were analysed by visual inspection, SSs were detected according to the patient own special spindle frequency, separately on the scalp (Fp1-2, F3-4, F7-8) and thalamus both sides. SS spectral peak frequency and synchronization between scalp and ANT was measured. Results IIDs appeared in the thalamus and on the scalp both dependent and independent manner. Three patients had seizures during VEM. Seizures did not start but start spread to the ANT electrodes. The slow, frontal type of SSs were prevailing in the ANT. Conclusion ANT participates in both sleep and epileptogenic processes. It seems that IIDs and IE spread to the ANT. Frontal, slow frequency SSs has local sources int he ANT indication its participation in sleep processes. Further evaluation for seizure outcome of ANT-DBS therapy and correlation with ANT recordings are underway.

Abnormal arousal processes, sympathetic influences, as well as wake-like alpha activity during sleep were reported as pathophysiological features of Nightmare Disorder. We hypothesized that in Nightmare Disorder, wake-like cortical activity and peripheral measures linked to arousals would be triggered by physiological processes related to the initiation of REM periods. Therefore, we examined electroencephalographic (EEG), motor and autonomous (cardiac) activity in a group of nightmare (NM) and healthy control (CTL) subjects during sleep-state-transitions while controlling for the confounding effects of trait anxiety. Based on the second-nights’ polysomnographic recordings of 19 Nightmare Disordered (NM) and 21 control (CTL) subjects, we examined the absolute power spectra focusing on the alpha range, measures of heart rate variability (HRV) and motor (muscle tone) activity during pre-REM and post-REM periods, separately. According to our results, the NM group exhibited increased alpha power during pre-REM, but not in post-REM, or stable, non-transitory periods. While CTL subjects showed increased HRV during pre-REM periods in contrast to post-REM ones, NM subjects did not exhibit such sleep state-specific differences in HRV, but showed more stable values across the examined sleep stages and less overall variability reflecting generally attenuated parasympathetic activity during sleep-state-transitions and during stable, non-transitory NREM states. These differences were not mediated by waking levels of trait anxiety. Moreover, in both groups, significant differences emerged regarding cortical and motor (muscle tone) activity between pre-REM and post-REM conditions, reflecting the heterogeneity of NREM sleep. Our findings indicate that NM subjects’ sleep is compromised during NREM–REM transitions, but relatively stabilized after REM periods. The coexistence of sleep-like and wake-like cortical activity in NM subjects seems to be triggered by REM/WAKE promoting neural activity. We propose that increased arousal-related phenomena in NREM–REM transitions might reflect altered emotional processing in NM subjects.

Contains fulltext : 136083.pdf (Publisher’s version ) (Open Access) Sleep spindles are thalamocortical oscillations in nonrapid eye movement sleep, which play an important role in sleep-related neuroplasticity and offline information processing. Sleep spindle features are stable within and vary between individuals, with, for example, females having a higher number of spindles and higher spindle density than males. Sleep spindles have been associated with learning potential and intelligence; however, the details of this relationship have not been fully clarified yet. In a sample of 160 adult human subjects with a broad IQ range, we investigated the relationship between sleep spindle parameters and intelligence. In females, we found a positive age-corrected association between intelligence and fast sleep spindle amplitude in central and frontal derivations and a positive association between intelligence and slow sleep spindle duration in all except one derivation. In males, a negative association between intelligence and fast spindle density in posterior regions was found. Effects were continuous over the entire IQ range. Our results demonstrate that, although there is an association between sleep spindle parameters and intellectual performance, these effects are more modest than previously reported and mainly present in females. This supports the view that intelligence does not rely on a single neural framework, and stronger neural connectivity manifesting in increased thalamocortical oscillations in sleep is one particular mechanism typical for females but not males. 11 p.

Although a growing body of research indicates that frequent nightmares are related to impaired sleep regulation, the pathophysiology of nightmare disorder is far from being fully understood. We examined the relative spectral power values for NREM and REM sleep separately in 19 individuals with nightmare disorder and 21 healthy controls, based on polysomnographic recordings of the second nights' laboratory sleep. Nightmare subjects compared to controls exhibited increased relative high alpha (10-14.5. Hz) and fronto-central increases in high delta (3-4. Hz) power during REM sleep, and a trend of increased fronto-central low alpha (7.75-9. Hz) power in NREM sleep. These differences were independent of the confounding effects of waking emotional distress. High REM alpha and low NREM alpha powers were strongly related in nightmare but not in control subjects. The topographical distribution and spectral components of REM alpha activity suggest that nightmare disordered subjects are characterized by wake-like electroencephalographic features during REM sleep. © 2013 Elsevier B.V.