Search bioRxiv⌕ Search

Biology subjects

Ujma, P. P.

Publications and source records attributed to Ujma, P. P..

13 recordsLinked to original sources

Bidirectional links between food intake and sleep: a naturalistic mobile EEG study

Sleep and nutrition are cornerstones of health, with likely reciprocal links between the two. The bidirectional link between sleep and food intake has been extensively studied, however, this literature relies almost completely on interventional and epidemiological studies. In the current study, we studied this link under naturalistic conditions, using data from a large sample of healthy participants. We investigated the bidirectional, time-lagged, within-person covariation between sleep, recorded by mobile EEGs and morning questionnaires; and food intake, recorded by retrospective evening questionnaires about the timing, content and satiation of previous-day meals. The findings supported links between sleep and food intake in both temporal directions. Later timing of the last meal was associated with later sleep onset, while a longer fasting period between the last meal and sleep was associated with reduced total sleep time, and reduced sleep efficiency. Sleep efficiency was higher following higher total daily energy intake. Later sleep was associated with a shift of next-day food intake to later hours. Overall, this naturalistic study suggests that the bidirectional relationship between sleep and food intake is primarily related to timing, not quality or composition. Contrary to some recommendations, we found no negative effect of reduced sleep quality after large, late, or satiating last meals.

physiology↗

Sleep complaints in alexithymia reflect non-specific negative affectivity

Alexithymia is the inability to identify and describe emotions, associated with an increased risk of somatic and psychiatric disease. Alexithymia is also characterized by reduced subjective sleep quality. However, it is not well-known if this reduction in sleep quality reflects physiological changes in sleep, a specific alteration in perceived sleep quality not captured by objective metrics, or a non-specific spillover of the negative affective style which characterizes alexithymia. In BSETS, a large (N=228) EEG study of naturalistic sleep, we found that alexithymia symptoms are associated with worse habitual (AIS) and current (GSQS) subjective sleep quality ({beta}AIS=0.207, pAIS=0.002, {beta}GSQS=0.203, pGSQS=0.002). However, we observed no significant association between alexithymia and EEG-based sleep efficiency ({beta}=- 0.017, p=0.791). The association with subjective sleep quality was almost completely attenuated when controlling for either depressive symptoms (PHQ-9, {beta}AIS=0.001, pAIS=0.982, {beta}GSQS=0.044, pGSQS=0.486) or trait neuroticism (ZKPQ, BFI-44, {beta}AIS=0.057, pAIS=0.442, {beta}GSQS=0.048, pGSQS=0.514). A possible exception is the Difficulty Identifying Feelings alexithymia dimension, reflecting complaints about the labeling of interoceptive experiences, which was associated with lower subjective sleep quality even after covariate control. This pattern of findings suggests that alexithymia is characterized only by alterations of subjective sleep quality, and even these reflect a non-specific increase in negative affect which influences self-reports of sleep quality, rather than a specific reduction in perceived sleep quality itself.

neuroscience↗

Sleep homeostasis in a naturalistic setting

Sleep, especially NREM sleep depth is homeostatically regulated, as sleep pressure builds up during wakefulness and diminishes during deep sleep. Previous evidence from this phenomenon, however, mainly stems from experimental studies which may not generalize to an ecologically valid setting. In the current study, we used a dataset of 246 individuals sleeping for at least seven nights each with a mobile EEG headband according to their ordinary daily schedule to investigate the effect of time spent in wakefulness on sleep characteristics. Increased time in wakefulness prior to sleep was associated with decreased sleep onset latency, increased sleep efficiency, a larger percentage of N3 sleep, and higher delta activity. Moreover, increased sleep pressure resulted in an increase in both the slope and the intercept of the sleep EEG spectrum. As predicted, PSD effects were most prominent in the earliest hours of sleep. Our results demonstrate that experimental findings showing increased sleep depth after extended wakefulness generalize to ecologically valid settings, and that time spent awake is an important determinant of sleep characteristics on the subsequent night. Our findings are evidence for the efficacy of sleep restriction, a behavioral technique already widely used in clinical settings, as a simple but powerful method to improve the objective quality of sleep in those with sleep problems.

neuroscience↗

Daily rhythms, demographics and health: findings from 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 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.

neuroscience↗

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 accounted for more covariance between sleep EEG and cognition than health variables, and consequently reduced this association by a greater degree, but even with the strictest covariate sets a statistically significant association was 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.

neuroscience↗

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 & 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.

bioinformatics↗

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

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.

neuroscience↗

Sleep spindles, ripples, and interictal epileptiform discharges 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, 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.

neuroscience↗

Circadian modulation of human sleep spindle frequency

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.

neuroscience↗

Educational attainment polygenic scores in Hungary: evidence for validity and a historical gene-environment interaction

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.

genetics↗

Sleep time, social jetlag and intelligence: biology or work timing?

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.

physiology↗

The laminar profile of sleep spindles in humans

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.

neuroscience↗

Individual slow wave morphology is a marker of ageing

Slow wave activity is a hallmark of deep NREM sleep. Scalp slow wave morphology is stereotypical, it is highly correlated with the synchronized onset and cessation of cortical neuronal firing measured from the surface or depth of the cortex, strongly affected by ageing, and these changes are causally associated with age-related cognitive decline. We investigated how normal ageing 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 159 subjects (age 17-69 years) and automatically detected slow waves using six different detection methods to ensure methodological robustness. We established individual slow morphologies at 501 data points for each subject and also calculated the individual average slow wave amplitude, average ascending and descending slope steepness and the total number of slow waves (gross parameters). Using LASSO penalized regression we found that fine-grained slow wave morphology is associated with age beyond gross parameters, with young subjects having faster slow wave polarity reversals, suggesting a more efficient initiation and termination of slow wave down- and upstates. Our results demonstrate the superiority of the high-resolution slow wave morphology as a biomarker of ageing, and highlights state transitions as promising targets of restorative stimulation-based interventions.

neuroscience↗