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Abstract Background Sleep homeostasis refers to the increase of sleep pressure during waking and the decrease of sleep intensity during sleep. Electroencephalography (EEG) slow-wave activity (SWA; EEG power in the 0.75-4.5 Hz range) is a marker of non-rapid eye movement (NREM) sleep intensity and can be used to model sleep homeostasis (Process S). SWA shows a frontal predominance, and its increase after sleep deprivation is most pronounced in frontal areas. The question arises whether the dynamics of the homeostatic Process S also show regional specificity. Furthermore, the spatial distribution of SWA is characteristic for an individual and may reflect traits of functional anatomy. The aim of the current study was to quantify inter-individual variation in the parameters of Process S and investigate their spatial distribution. Polysomnographic recordings obtained with 27 EEG derivations of a baseline night of sleep and a recovery night of sleep after 40 h of sustained wakefulness were analyzed. Eight healthy young subjects participated in this study. Process S was modeled by a saturating exponential function during wakefulness and an exponential decline during sleep. Empirical mean SWA per NREM sleep episode at episode midpoint served for parameter estimation at each derivation. Time constants were restricted to a physiologically meaningful range. Results For both, the buildup and decline of Process S, significant topographic differences were observed: The decline and buildup of Process S were slowest in fronto-central areas while the fastest dynamics were observed in parieto-occipital (decrease) and frontal (buildup) areas. Each individual showed distinct spatial patterns in the parameters of Process S and the parameters differed significantly between individuals. Conclusions For the first time, topographical aspects of the buildup of Process S were quantified. Our data provide an additional indication of regional differences in sleep homeostasis and support the notion of local aspects of sleep regulation.

The capacity to integrate information across brain regions and sufficient diversity of neural activity is necessary for consciousness. In patients in a post-hypoxic ischemic coma, the integrity of the auditory processing network is indicative of chances of regaining consciousness. However, our understanding of how measures of integration and differentiation of auditory responses manifest across time of coma is limited. We investigated the temporal evolution of neural synchrony of auditory-evoked electroencephalographic (EEG) responses, measured via their phase-locking value (PLV), and of their neural complexity in unconscious post-hypoxic ischemic comatose patients. Our results show that the PLV was predictive of chances to regain consciousness within the first 40 h post-cardiac arrest, while its predictive value diminished over subsequent time after coma onset. This was due to changing trajectories of PLV over time of coma for non-survivors, while survivors had stable PLV. The complexity of EEG responses was not different between patients who regained consciousness and those who did not, but it significantly diminished over time of coma, irrespective of the patient's outcome. Our findings provide novel insights on the optimal temporal window for assessing auditory functions in post-hypoxic ischemic coma. They are of particular importance for guiding the implementation of quantitative techniques for prognostication and contribute to an evolving understanding of neural functions within the acute comatose state., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: “AT and FA are mentioned as co-inventor in a patent application No. EP22386068.5 owned by University of Bern. The patent is currently not licensed. All other authors have declared no conflict of interest, financial or otherwise.”., (Copyright © 2025 The Author(s). Published by Elsevier B.V. All rights reserved.)

The sleep homeostatic process in adults is moderately stable over time and unique to an individual. Work in transgenic mice has suggested a role of genes in sleep homeostasis. The current study quantified the genetic contribution to sleep homeostasis in adolescence. We use slow wave energy (SWE) as a metric for sleep pressure dissipation during sleep. This measure reflects both sleep intensity and duration. High-density (58 derivations) sleep electroencephalogram (EEG) was recorded in 14 monozygotic and 12 dizygotic adolescent twin pairs (mean age = 13.2 years; standard deviation [SD] = 1.1; 20 females). SWE at the end of sleep was quantified as the cumulative delta power (1-4.6 Hz) over the night. We also examined the time constant of the decay and the level of slow wave activity (SWA) at the beginning of the sleep episode. Structural equation modelling was used to quantify the amount of variance in SWE and the dissipation of sleep pressure due to genes. We found that most (mean = 76% across EEG derivations) of the variance in SWE was due to genes. In contrast, genes had a small (mean = 33%) influence on the rate of dissipation of sleep pressure, and this measure was largely (mean = 67%) driven by environmental factors unique to each twin. Our results show that the amount of dissipated sleep pressure is largely under genetic control; however, the rate of sleep pressure dissipation is largely due to unique environmental factors. Our findings are in line with research in animals and suggest that the heritability of the rate of sleep pressure dissipation is limited., (© 2024 The Author(s). European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

Early Alzheimer's disease (AD) is associated with hippocampal hyperactivity and decreased sleep quality. Here we show that homeostatic mechanisms transiently counteract the increased excitatory drive to CA1 neurons in App NL-G-F mice, but that this mechanism fails in older mice. Spatial transcriptomics analysis identifies Pmch as part of the adaptive response in App NL-G-F mice. Pmch encodes melanin-concentrating hormone (MCH), which is produced in sleep-active lateral hypothalamic neurons that project to CA1 and modulate memory. We show that MCH downregulates synaptic transmission, modulates firing rate homeostasis in hippocampal neurons and reverses the increased excitatory drive to CA1 neurons in App NL-G-F mice. App NL-G-F mice spend less time in rapid eye movement (REM) sleep. App NL-G-F mice and individuals with AD show progressive changes in morphology of CA1-projecting MCH axons. Our findings identify the MCH system as vulnerable in early AD and suggest that impaired MCH-system function contributes to aberrant excitatory drive and sleep defects, which can compromise hippocampus-dependent functions., (© 2023. The Author(s).)

The interplay between the medial prefrontal cortex and hippocampus during non-rapid eye movement (NREM) sleep contributes to the consolidation of contextual memories. To assess the role of the thalamic nucleus reuniens (Nre) in this interaction, we investigated the coupling of neuro-oscillatory activities among prelimbic cortex, Nre, and hippocampus across sleep states and their role in the consolidation of contextual memories using multi-site electrophysiological recordings and optogenetic manipulations. We showed that ripples are time-locked to the Up state of cortical slow waves, the transition from UP to DOWN state in thalamic slow waves, the troughs of cortical spindles, and the peaks of thalamic spindles during spontaneous sleep, rebound sleep and sleep following a fear conditioning task. In addition, spiking activity in Nre increased before hippocampal ripples, and the phase-locking of hippocampal ripples and thalamic spindles during NREM sleep was stronger after acquisition of a fear memory. We showed that optogenetic inhibition of Nre neurons reduced phase-locking of ripples to cortical slow waves in the ventral hippocampus whilst their activation altered the preferred phase of ripples to slow waves in ventral and dorsal hippocampi. However, none of these optogenetic manipulations of Nre during sleep after acquisition of fear conditioning did alter sleep-dependent memory consolidation. Collectively, these results showed that Nre is central in modulating hippocampus and cortical rhythms during NREM sleep., (© 2022 University of Bern. European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

Schizophrenia is associated with alterations of sensory integration, cognitive processing and both sleep architecture and sleep oscillations in mouse models and human subjects, possibly through changes in thalamocortical dynamics. Oxidative stress (OxS) damage, including inflammation and the impairment of fast-spiking gamma-aminobutyric acid neurons have been hypothesized as a potential mechanism responsible for the onset and development of schizophrenia. Yet, the link between OxS and perturbation of thalamocortical dynamics and sleep remains unclear. Here, we sought to investigate the effects of OxS on sleep regulation by characterizing the dynamics of thalamocortical networks across sleep-wake states in a mouse model with a genetic deletion of the modifier subunit of glutamate-cysteine ligase (Gclm knockout, KO) using high-density electrophysiology in freely-moving mice. We found that Gcml KO mice exhibited a fragmented sleep architecture and impaired sleep homeostasis responses as revealed by the increased NREM sleep latencies, decreased slow-wave activities and spindle rate after sleep deprivation. These changes were associated with altered bursting activity and firing dynamics of neurons from the thalamic reticularis nucleus, anterior cingulate and anterodorsal thalamus. Administration of N-acetylcysteine (NAC), a clinically relevant antioxidant, rescued the sleep fragmentation and spindle rate through a renormalization of local neuronal dynamics in Gclm KO mice. Collectively, these findings provide novel evidence for a link between OxS and the deficits of frontal TC network dynamics as a possible mechanism underlying sleep abnormalities and impaired homeostatic responses observed in schizophrenia., (© 2022. The Author(s).)

Rapid eye movement (REM) sleep is associated with the consolidation of emotional memories. Yet, the underlying neocortical circuits and synaptic mechanisms remain unclear. We found that REM sleep is associated with a somatodendritic decoupling in pyramidal neurons of the prefrontal cortex. This decoupling reflects a shift of inhibitory balance between parvalbumin neuron-mediated somatic inhibition and vasoactive intestinal peptide-mediated dendritic disinhibition, mostly driven by neurons from the central medial thalamus. REM-specific optogenetic suppression of dendritic activity led to a loss of danger-versus-safety discrimination during associative learning and a lack of synaptic plasticity, whereas optogenetic release of somatic inhibition resulted in enhanced discrimination and synaptic potentiation. Somatodendritic decoupling during REM sleep promotes opposite synaptic plasticity mechanisms that optimize emotional responses to future behavioral stressors.

Background: Depression is highly prevalent among adolescents, and depressive symptoms rise rapidly during early adolescence. Depression is often accompanied by subjective sleep complaints and alterations in sleep neurophysiology. In this study, we examine whether depressive symptoms, measured on a continuum, are associated with subjective and objective (sleep architecture and neurophysiology) measures of sleep in early adolescence., Methods: High-density sleep EEG, actigraphy, and self-reported sleep were measured in 52 early adolescents (12.31 years; SD: 1.121; 25 female). Depressive symptoms were measured on a continuum using the Center for Epidemiological Studies Depression Scale (CES-D). The association between depressive symptoms and 2 weeks of actigraphy, self-reported sleep, sleep architecture, and sleep neurophysiology (slow wave activity and sigma power) was determined via multiple linear regression with factors age, sex, and pubertal status., Results: Despite no association between polysomnography measures of sleep quality and depressive symptoms, individuals with more depressive symptoms manifested worse actigraphically measured sleep. Less sleep spindle activity, as reflected in nonrapid eye movement sleep sigma power, was associated with more depressive symptoms over a large cluster encompassing temporal, parietal, and occipital regions. Furthermore, worse subjectively reported sleep quality was also associated with less sigma power over these same areas. Puberty, age, and sex did not impact this association., Conclusions: Sleep spindles have been hypothesized to protect sleep against environmental disturbances. Thus, diminished spindle power may be a subtle sign of disrupted sleep and its association with depressive symptoms in early adolescence may signal vulnerability for depression., (© 2019 Association for Child and Adolescent Mental Health.)

Falling asleep is a gradually unfolding process. We investigated the role of various oscillatory activities including sleep spindles and alpha and delta oscillations at sleep onset (SO) by automatically detecting oscillatory events. We used two datasets of healthy young males, eight with four baseline recordings, and eight with a baseline and recovery sleep after 40 h of sustained wakefulness. We analyzed the 2-min interval before SO (stage 2) and the five consecutive 2-min intervals after SO. The incidence of delta/theta events reached its maximum in the first 2-min episode after SO, while the frequency of them was continuously decreasing from stage 1 onwards, continuing over SO and further into deeper sleep. Interestingly, this decrease of the frequencies of the oscillations were not affected by increased sleep pressure, in contrast to the incidence which increased. We observed an increasing number of alpha events after SO, predominantly frontally, with their prevalence varying strongly across individuals. Sleep spindles started to occur after SO, with first an increasing then a decreasing incidence and a continuous decrease in their frequency. Again, the frequency of the spindles was not altered after sleep deprivation. Oscillatory events revealed derivation dependent aspects. However, these regional aspects were not specific of the process of SO but rather reflect a general sleep related phenomenon. No individual traits of SO features (incidence and frequency of oscillations) and their dynamics were observed. Delta/theta events are important features for the analysis of SO in addition to slow waves., (© Sleep Research Society 2019. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.)

Ambient temperature (T a ) warming toward the high end of the thermoneutral zone (TNZ) preferentially increases rapid eye movement (REM) sleep over non-REM (NREM) sleep across species. The control and function of this temperature-induced REM sleep expression have remained unknown. Melanin-concentrating hormone (MCH) neurons play an important role in REM sleep control. We hypothesize that the MCH system may modulate REM sleep as a function of T a . Here, we show that wild-type (WT) mice dynamically increased REM sleep durations specifically during warm T a pulsing within the TNZ, compared to both the TNZ cool and baseline constant T a conditions, without significantly affecting either wake or NREM sleep durations. However, genetically engineered MCH receptor-1 knockout (MCHR1-KO) mice showed no significant changes in REM sleep as a function of T a , even with increased sleep pressure following a 4-h sleep deprivation. Using MCH-cre mice transduced with channelrhodopsin, we then optogenetically activated MCH neurons time locked with T a warming, showing an increase in REM sleep expression beyond what T a warming in yellow fluorescent protein (YFP) control mice achieved. Finally, in mice transduced with archaerhodopsin-T, semi-chronic optogenetic MCH neuronal silencing during T a warming completely blocked the increase in REM sleep seen in YFP controls. These data demonstrate a previously unknown role for the MCH system in the dynamic output expression of REM sleep during T a manipulation. These findings are consistent with the energy allocation hypothesis of sleep function, suggesting that endotherms have evolved neural circuits to opportunistically express REM sleep when the need for thermoregulatory defense is minimized., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Sleep-specific oscillations of spindles and slow waves are generated through thalamocortical and corticocortical loops, respectively, and provide a unique opportunity to measure the integrity of these neuronal systems. Understanding the relative contribution of genetic factors to sleep oscillations is important for determining whether they constitute useful endophenotypes that mark vulnerability to psychiatric illness. Using high-density sleep EEG recordings in human adolescent twin pairs ( n = 60; 28 females), we find that over posterior regions 80-90% of the variance in slow oscillations, slow wave, and spindle activity is due to genes. Surprisingly, slow (10-12 Hz) and fast (12-16 Hz) anterior spindle amplitude and σ power are largely driven by environmental factors shared among the twins. To our knowledge this is the first example of a neural phenotype that exhibits a strong influence of nature in one brain region, and nurture in another. Overall, our findings highlight the utility of the sleep EEG as a reliable and easy to measure endophenotype during adolescence. This measure may be used to measure disease risk in development before the onset of a psychiatric disorder; the location within the brain of deficits in sleep neurophysiology may suggest whether the ultimate cause is genetic or environmental. SIGNIFICANCE STATEMENT Two cardinal oscillations of sleep, slow waves and sleep spindles, play an important role in the core functions of sleep including memory consolidation, synaptic plasticity, and the recuperative function of sleep. In this study, we use a behavioral genetics approach to examine the heritability of sleep neurophysiology using high-density EEG in a sample of early adolescent twins. Our findings reveal a strong influence of both environmental and genetic factors in shaping these oscillations, dependent on brain region. Thus, during a developmental period when brain structure and function is in flux, we find that the sleep EEG is among the most heritable of human traits over circumscribed brain regions., (Copyright © 2018 the authors 0270-6474/18/389275-11$15.00/0.)

The topographic distribution of sleep EEG power is a reflection of brain structure and function. The goal of this study was to examine the degree to which genes contribute to sleep EEG topography during adolescence, a period of brain restructuring and maturation. We recorded high-density sleep EEG in monozygotic (MZ; n = 28) and dizygotic (DZ; n = 22) adolescent twins (mean age = 13.2 ± 1.1 years) at two time points 6 months apart. The topographic distribution of normalized sleep EEG power was examined for the frequency bands delta (1-4.6 Hz) to gamma 2 (34.2-44 Hz) during NREM and REM sleep. We found highest heritability values in the beta band for NREM and REM sleep (0.44 ≤ h 2  ≤ 0.57), while environmental factors shared amongst twin siblings accounted for the variance in the delta to sigma bands (0.59 ≤ c 2  ≤ 0.83). Given that both genetic and environmental factors are reflected in sleep EEG topography, our results suggest that topography may provide a rich metric by which to understand brain function. Furthermore, the frequency specific parsing of the influence of genetic from environmental factors on topography suggests functionally distinct networks and reveals the mechanisms that shape these networks.

Background: Investigating functional connectivity between brain networks has become an area of interest in neuroscience. Several methods for investigating connectivity have recently been developed, however, these techniques need to be applied with care. We demonstrate that global field synchronization (GFS), a global measure of phase alignment in the EEG as a function of frequency, must be applied considering signal processing principles in order to yield valid results., New Method: Multichannel EEG (27 derivations) was analyzed for GFS based on the complex spectrum derived by the fast Fourier transform (FFT). We examined the effect of window functions on GFS, in particular of non-rectangular windows., Results: Applying a rectangular window when calculating the FFT revealed high GFS values for high frequencies (>15Hz) that were highly correlated (r=0.9) with spectral power in the lower frequency range (0.75-4.5Hz) and tracked the depth of sleep. This turned out to be spurious synchronization. With a non-rectangular window (Tukey or Hanning window) these high frequency synchronization vanished. Both, GFS and power density spectra significantly differed for rectangular and non-rectangular windows., Comparison With Existing Method(s): Previous papers using GFS typically did not specify the applied window and may have used a rectangular window function. However, the demonstrated impact of the window function raises the question of the validity of some previous findings at higher frequencies., Conclusions: We demonstrated that it is crucial to apply an appropriate window function for determining synchronization measures based on a spectral approach to avoid spurious synchronization in the beta/gamma range., (Copyright © 2017 Elsevier B.V. All rights reserved.)

The sleep homeostatic Process S reflects the build-up of sleep pressure during waking and its dissipation during sleep. Process S is modelled as a saturating exponential function during waking and a decreasing exponential function during sleep. Slow wave activity is a physiological marker for non-rapid eye movement (non-REM) sleep intensity and serves as an index of Process S. There is considerable interindividual variability in the sleep homeostatic responses to sleep and sleep deprivation. The aim of this study was to investigate whether interindividual differences in Process S are trait-like. Polysomnographic recordings of 8 nights (12-h sleep opportunities, 22:00-10:00 hours) interspersed with three 36-h periods of sustained wakefulness were performed in 11 healthy young adults. Empirical mean slow wave activity per non-REM sleep episode at episode mid-points were used for parameter estimation. Parameters of Process S were estimated using different combinations of consecutive sleep recordings, resulting in two to three sets of parameters per subject. Intraclass correlation coefficients were calculated to assess whether the parameters were stable across the study protocol and they showed trait-like variability among individuals. We found that the group-average time constants of the build-up and dissipation of Process S were 19.2 and 2.7 h, respectively. Intraclass correlation coefficients ranged from 0.48 to 0.56, which reflects moderate trait variability. The time constants of the build-up and dissipation varied independently among subjects, indicating two distinct traits. We conclude that interindividual differences in the parameters of the dynamics of the sleep homeostatic Process S are trait-like., (© 2016 European Sleep Research Society.)

Motor activity recording by a wrist-worn device is a common method to monitor the rest-activity cycle. The first author wore an actimeter continuously for more than three decades, starting in 1982 at the age of 43.5 years. Until November 2006 analysis was performed on a 15-min time base, and subsequently on a 2-min time base. The timing of night-time sleep was determined from the cessation and re-occurrence of daytime-level activity. Sleep duration declined from an initial 6.8 to 6 h in 2004. The declining trend was reversed upon retirement, whereas the variance of sleep duration declined throughout the recording period. Before retirement, a dominant 7-day rhythm of sleep duration as well as an annual periodicity was revealed by spectral analysis. These variations were attenuated or vanished during the years after retirement. We demonstrate the feasibility of continuous long-term motor activity recordings to study age-related variations of the rest-activity cycle. Here we show that the embeddedness in a professional environment imparts a temporal structure to sleep duration., (© 2017 European Sleep Research Society.)

Background: Recent studies have claimed a positive effect of physical activity and body composition on vagal tone. In pediatric populations, there is a pronounced decrease in heart rate with age. While this decrease is often interpreted as an age-related increase in vagal tone, there is some evidence that it may be related to a decrease in intrinsic heart rate. This factor has not been taken into account in most previous studies. The aim of the present study was to assess the association between physical activity and/or body composition and heart rate variability (HRV) independently of the decline in heart rate in young children. Methods: Anthropometric measurements were taken in 309 children aged 2-6 years. Ambulatory electrocardiograms were collected over 14-18 h comprising a full night and accelerometry over 7 days. HRV was determined of three different night segments: (1) over 5 min during deep sleep identified automatically based on HRV characteristics; (2) during a 20 min segment starting 15 min after sleep onset; (3) over a 4-h segment between midnight and 4 a.m. Linear models were computed for HRV parameters with anthropometric and physical activity variables adjusted for heart rate and other confounding variables (e.g., age for physical activity models). Results: We found a decline in heart rate with increasing physical activity and decreasing skinfold thickness. HRV parameters decreased with increasing age, height, and weight in HR-adjusted regression models. These relationships were only found in segments of deep sleep detected automatically based on HRV or manually 15 min after sleep onset, but not in the 4-h segment with random sleep phases. Conclusions: Contrary to most previous studies, we found no increase of standard HRV parameters with age, however, when adjusted for heart rate, there was a significant decrease of HRV parameters with increasing age. Without knowing intrinsic heart rate correct interpretation of HRV in growing children is impossible.

Although quantitative analysis of the sleep electroencephalogram (EEG) has uncovered important aspects of brain activity during sleep in adolescents and adults, similar findings from preschool-age children remain scarce. This study utilized our time-frequency method to examine sleep oscillations as characteristic features of human sleep EEG. Data were collected from a longitudinal sample of young children ( n = 8; 3 males) at ages 2, 3, and 5 years. Following sleep stage scoring, we detected and characterized oscillatory events across age and examined how their features corresponded to spectral changes in the sleep EEG. Results indicated a developmental decrease in the incidence of delta and theta oscillations. Spindle oscillations, however, were almost absent at 2 years but pronounced at 5 years. All oscillatory event changes were stronger during light sleep than slow-wave sleep. Large interindividual differences in sleep oscillations and their characteristics (e.g., "ultrafast" spindle-like oscillations, theta oscillation incidence/frequency) also existed. Changes in delta and spindle oscillations across early childhood may indicate early maturation of the thalamocortical system. Our analytic approach holds promise for revealing novel types of sleep oscillatory events that are specific to periods of rapid normal development across the lifespan and during other times of aberrant changes in neurobehavioral function.

Although all young children nap, the neurophysiological features and associated developmental trajectories of daytime sleep remain largely unknown. Longitudinal studies of napping physiology are fundamental to understanding sleep regulation during early childhood, a sensitive period in brain and behaviour development and a time when children transition from a biphasic to a monophasic sleep-wakefulness pattern. We investigated daytime sleep in eight healthy children with sleep electroencephalography (EEG) assessments at three longitudinal points: 2 years (2.5-3.0 years), 3 years (3.5-4.0 years) and 5 years (5.5-6.0 years). At each age, we measured nap EEG during three randomized conditions: after 4 h (morning nap), 7 h (afternoon nap) and 10 h (evening nap) duration of prior wakefulness. Developmental changes in sleep were most prevalent in the afternoon nap (e.g. decrease in sleep duration by 30 min from 2 to 3 years and by 20 min from 3 to 5 years). In contrast, nap sleep architecture (% of sleep stages) remained unchanged across age. Maturational changes in non-rapid eye movement sleep EEG power were pronounced in the slow wave activity (SWA, 0.75-4.5 Hz), theta (4.75-7.75 Hz) and sigma (10-15 Hz) frequency ranges. These findings indicate that the primary marker of sleep depth, SWA, is less apparent in daytime naps as children mature. Moreover, our fundamental data provide insight into associations between sleep regulation and functional modifications in the central nervous system during early childhood., Competing Interests: None., (© 2016 European Sleep Research Society.)

Sleep is characterized by a loss of consciousness, which has been attributed to a breakdown of functional connectivity between brain regions. Global field synchronization (GFS) can estimate functional connectivity of brain processes. GFS is a frequency-dependent measure of global synchronicity of multi-channel EEG data. Our aim was to explore and extend the hypothesis of disconnection during sleep by comparing GFS spectra of different vigilance states. The analysis was performed on eight healthy adult male subjects. EEG was recorded during a baseline night, a recovery night after 40 h of sustained wakefulness and at 3 h intervals during the 40 h of wakefulness. Compared to non-rapid eye movement (NREM) sleep, REM sleep showed larger GFS values in all frequencies except in the spindle and theta bands, where NREM sleep showed a peak in GFS. Sleep deprivation did not affect GFS spectra in REM and NREM sleep. Waking GFS values were lower compared with REM and NREM sleep except for the alpha band. Waking alpha GFS decreased following sleep deprivation in the eyes closed condition only. Our surprising finding of higher synchrony during REM sleep challenges the view of REM sleep as a desynchronized brain state and may provide insight into the function of REM sleep.

The shift from a biphasic to a monophasic sleep schedule is a fundamental milestone in early childhood. This transition, however, may result in periods of acute sleep loss as children may nap on some but not all days. Although data indicating the behavioral consequences of nap deprivation in young children are accumulating, little is known about changes to sleep neurophysiology following daytime sleep loss. This study addresses this gap in knowledge by examining the effects of acute nap deprivation on subsequent nighttime sleep electroencephalographic (EEG) parameters in toddlers. Healthy children (n=25; 11 males; ages 30-36 months) followed a strict sleep schedule for ≥5 days before sleep EEG recordings performed on 2 non-consecutive days: one after 13 h of prior wakefulness and another at the same clock time but preceded by a daytime nap. Total slow-wave energy (SWE) was computed as cumulative slow-wave activity (SWA; EEG power in 0.75-4.5 Hz range) over time. Nap and subsequent night SWE were added and compared to SWE of the night after a missed nap. During the night following a missed nap, children fell asleep faster (11.9 ± 8.7 versus 37.3 ± 22.1 min; d=1.6, p=0.01), slept longer (10.1 ± 0.7 versus 9.6 ± 0.6 h; d=0.7, p<0.01) and exhibited greater SWA (133.3 ± 37.5 versus 93.0 ± 4.7 %; d=0.9, p<0.01) compared to a night after a daytime nap. SWE for combined nap and subsequent night sleep did not significantly differ from the night following nap deprivation (12141.1 ± 3872.9 versus 11588 ± 3270.8 µV 2* h; d=0.6, p=0.12). However, compared to a night following a missed nap, children experienced greater time in bed (13.0±0.8 versus 10.9±0.5; d=3.1, p<0.01) and total sleep time (11.2±0.8 versus 10.1±0.7; d=1.4, p<0.01). Shorter sleep latency, longer sleep duration, and increased SWA in the night following a missed nap indicate that toddlers experience a physiologically meaningful homeostatic challenge after prolonged wakefulness. Whether toddlers fully recover from missing a daytime nap in the subsequent night necessitates further examination of daytime functioning., Competing Interests: The authors have none to declare.

The sleep electroencephalogram (EEG) spectrum is unique to an individual and stable across multiple baseline recordings. The aim of this study was to examine whether the sleep EEG spectrum exhibits the same stable characteristics after acute total sleep deprivation. Polysomnography (PSG) was recorded in 20 healthy adults across consecutive sleep periods. Three nights of baseline sleep [12 h time in bed (TIB)] following 12 h of wakefulness were interleaved with three nights of recovery sleep (12 h TIB) following 36 h of sustained wakefulness. Spectral analysis of the non-rapid eye movement (NREM) sleep EEG (C3LM derivation) was used to calculate power in 0.25 Hz frequency bins between 0.75 and 16.0 Hz. Intraclass correlation coefficients (ICCs) were calculated to assess stable individual differences for baseline and recovery night spectra separately and combined. ICCs were high across all frequencies for baseline and recovery and for baseline and recovery combined. These results show that the spectrum of the NREM sleep EEG is substantially different among individuals, highly stable within individuals and robust to an experimental challenge (i.e. sleep deprivation) known to have considerable impact on the NREM sleep EEG. These findings indicate that the NREM sleep EEG represents a trait., (© 2015 European Sleep Research Society.)

Sleep has beneficial effects on brain function and learning, which are reflected in plastic changes in the cortex. Early childhood is a time of rapid maturation in fundamental skills-e.g., language, cognitive control, working memory-that are predictive of future functioning. Little is currently known about the interactions between sleep and brain maturation during this developmental period. We propose coherent electroencephalogram (EEG) activity during sleep may provide unique insight into maturational processes of functional brain connectivity. Longitudinal sleep EEG assessments were performed in eight healthy subjects at ages 2, 3 and 5 years. Sleep EEG coherence increased across development in a region- and frequency-specific manner. Moreover, although connectivity primarily decreased intra-hemispherically across a night of sleep, an inter-hemispheric overnight increase occurred in the frequency range of slow waves (0.8-2 Hz), theta (4.8-7.8 Hz) and sleep spindles (10-14 Hz), with connectivity changes of up to 20% across a night of sleep. These findings indicate sleep EEG coherence reflects processes of brain maturation-i.e., programmed unfolding of neuronal networks-and moreover, sleep-related alterations of brain connectivity during the sensitive maturational window of early childhood.

The electric light is one of the most important human inventions. Sleep and other daily rhythms in physiology and behavior, however, evolved in the natural light-dark cycle [1], and electrical lighting is thought to have disrupted these rhythms. Yet how much the age of electrical lighting has altered the human circadian clock is unknown. Here we show that electrical lighting and the constructed environment is associated with reduced exposure to sunlight during the day, increased light exposure after sunset, and a delayed timing of the circadian clock as compared to a summer natural 14 hr 40 min:9 hr 20 min light-dark cycle camping. Furthermore, we find that after exposure to only natural light, the internal circadian clock synchronizes to solar time such that the beginning of the internal biological night occurs at sunset and the end of the internal biological night occurs before wake time just after sunrise. In addition, we find that later chronotypes show larger circadian advances when exposed to only natural light, making the timing of their internal clocks in relation to the light-dark cycle more similar to earlier chronotypes. These findings have important implications for understanding how modern light exposure patterns contribute to late sleep schedules and may disrupt sleep and circadian clocks., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Previous studies have observed increases in electroencephalographic power during sleep in the spindle frequency range (approximately 11-15 Hz) after exposure to mobile phone-like radio frequency electromagnetic fields (RF EMF). Results also suggest that pulse modulation of the signal is crucial to induce these effects. Nevertheless, it remains unclear which specific elements of the field are responsible for the observed changes. We investigated whether pulse-modulation frequency components in the range of sleep spindles may be involved in mediating these effects. Thirty young healthy men were exposed, at weekly intervals, to three different conditions for 30 min directly prior to an 8-h sleep period. Exposure consisted of a 900-MHz RF EMF, pulse modulated at 14 Hz or 217 Hz, and a sham control condition. Both active conditions had a peak spatial specific absorption rate of 2 W kg(-1) . During exposure subjects performed three different cognitive tasks (measuring attention, reaction speed and working memory), which were presented in a fixed order. Electroencephalographic power in the spindle frequency range was increased during non-rapid eye movement sleep (2nd episode) following the 14-Hz pulse-modulated condition. A similar but non-significant increase was also observed following the 217-Hz pulse-modulated condition. Importantly, this exposure-induced effect showed considerable individual variability. Regarding cognitive performance, no clear exposure-related effects were seen. Consistent with previous findings, our results provide further evidence that pulse-modulated RF EMF alter brain physiology, although the time-course of the effect remains variable across studies. Additionally, we demonstrated that modulation frequency components within a physiological range may be sufficient to induce these effects., (© 2011 European Sleep Research Society.)

Study Objectives: The two-process model posits that sleep is regulated by 2 independent processes, a circadian Process C and a homeostatic Process S. EEG slow-wave activity (SWA) is a marker of NREM sleep intensity and is used as an indicator of sleep homeostasis. So far, parameters of the two-process model have been derived mainly from average data. Our aim was to quantify inter-individual differences., Design: Polysomnographic recordings (analysis of existing data)., Setting: Sound attenuated sleep laboratory., Patients or Participants: Eight healthy young males., Interventions: 40-h sustained wakefulness., Measurements and Results: Process S was modeled by a saturating exponential function during wakefulness and an exponential decline during sleep. Empirical mean SWA (derivation C3A2) per NREM sleep episode at episode midpoint were used for parameter estimation. Parameters were estimated simultaneously by minimizing the mean square error between data and simulations of Process S. This approach was satisfactory for average data and most individual data. We further improved our methodological approach by limiting the time constants to a physiologically meaningful range. This allowed a satisfactory fit also for the one individual whose parameters were beyond a physiological range. The time constants of the buildup of Process S ranged from 14.1 h to 26.4 h and those of the decline from 1.2 h to 2.9 h with similar inter-individual variability of the buildup and decline of Process S., Conclusions: We established a robust method for parameter estimation of Process S on an individual basis.

Individual patterns of the electroencephalogram (EEG) in wakefulness and sleep are among the most heritable traits in humans, yet distinct genetic and neurochemical mechanisms underlying EEG phenotypes are largely unknown. A functional polymorphism in the gene encoding catechol-O-methyltransferase (COMT), an enzyme playing an important role in cortical dopamine metabolism, causes a common substitution of methionine (Met) for valine (Val) at codon 158 of COMT protein. Val allele homozygotes exhibit higher COMT activity and lower dopaminergic signaling in prefrontal cortex than Met/Met homozygotes. Evidence suggests that this polymorphism affects executive functions in healthy individuals. We hypothesized that it also modulates functional aspects of EEG in wakefulness and sleep. EEG recordings were conducted twice on separate occasions in 10 Val/Val and 12 Met/Met allele carriers (all men) in wakefulness, and in baseline and recovery sleep before and after 40 h prolonged waking. During sleep deprivation, subjects received placebo and modafinil in randomized, cross-over manner. We show that the Val158Met polymorphism predicts stable and frequency-specific, interindividual variation in brain alpha oscillations. Alpha peak frequency in wakefulness was 1.4 Hz slower in Val/Val genotype than in Met/Met genotype. Moreover, Val/Val allele carriers exhibited less 11-13 Hz activity than Met/Met homozygotes in wakefulness, rapid-eye-movement (REM) sleep, and non-REM sleep. This difference was resistant against the effects of sleep deprivation and modafinil. The data demonstrate that mechanisms involving COMT contribute to interindividual differences in brain alpha oscillations, which are functionally related to executive performance such as counting tendency on a random number generation task in young adults.