EEG Microstate Dynamics Associated with Dream-Like Experiences During the Transition to Sleep.

Consciousness always requires some representational content; that is, one can only be conscious about something. However, the presence of conscious experience (awareness) alone does not determine whether its content is in line with the external and physical world. Dreams, apart from certain forms of hallucinations, typically consist of non-veridical percepts, which are not recognized as false, but rather considered real. This type of experiences have been described as a state of dissociation between phenomenal and reflective awareness. Interestingly, during the transition to sleep, reflective awareness seems to break down before phenomenal awareness as conscious experience does not immediately fade with reduced wakefulness but is rather characterized by the occurrence of uncontrolled thinking and perceptual images, together with a reduced ability to recognize the internal origin of the experience. Relative deactivation of the frontoparietal and preserved activity in parieto-occipital networks has been suggested to account for dream-like experiences during the transition to sleep. We tested this hypothesis by investigating subjective reports of conscious experience and large-scale brain networks using EEG microstates in 45 healthy young subjects during the transition to sleep. We observed an inverse relationship between cognitive effects and physiological activation; dream-like experiences were associated with an increased presence of a microstate with sources in the superior and middle frontal gyrus and precuneus. Additionally, the presence of a microstate associated with higher-order visual areas was decreased. The observed inverse relationship might therefore indicate a disengagement of cognitive control systems that is mediated by specific, inhibitory EEG microstates.

BizarreVR: Dream-like bizarreness in immersive virtual reality induced changes in conscious experience of reality while leaving spatial presence intact.

Differences in conscious experience of reality occur between waking, dreaming, and psychotic states. Between these states, there are systematic differences in the judgment about the reality of the experience when being confronted with bizarre breaks. However, the mechanisms underlying experience of reality in these different states are still unknown. To investigate the effect of bizarre breaks on experience of reality during the wake state, we propose a new paradigm using dream-like bizarreness and immersive virtual reality. Results showed that the realistic non-bizarre virtual environment induced high levels of reality judgment and spatial presence, whereas the confrontation with bizarre breaks induced high levels of experienced bizarreness. Moreover, experienced bizarreness significantly reduced reality judgment in both the bizarre and the realistic condition. Further, there was no effect of bizarre breaks on spatial presence. These results provide proof of concept for the new method to elicit natural bizarre experience within a realistic scenario.

Naps not as effective as a night of sleep at dissipating sleep pressure.

The two-process model of sleep posits that two processes interact to regulate sleep and wake: a homeostatic (Process S) and a circadian process (Process C). Process S compensates for sleep loss by increasing sleep duration and intensity. Process C gates the timing of sleep/wake favouring sleep during the circadian night in humans. In this study, we examined whether taking six naps throughout a 24-hr period would result in the same amount of dissipation of homeostatic pressure at the end of the day as a night of sleep, when time in bed is equivalent. Data from 46 participants (10-23 years; mean = 14.5 [±â€…2.9]; 25 females) were analysed. Slow-wave energy, normalized to account for individual differences in slow-wave activity, was used as a measure of sleep homeostasis. In the nap condition, slow-wave energy of six naps distributed equally during a 24-hr period was calculated. In the baseline condition, slow-wave energy was measured after 9-hr time in bed. A paired t-test was used to compare nap and baseline conditions. A linear regression was used to examine whether slow-wave energy varied as a function of age. Slow-wave energy was greater during baseline than the nap condition (p < .001). No association between age and slow-wave energy was found for baseline or nap conditions. Our findings indicate that multiple naps throughout the day are not as effective at dissipating sleep pressure as a night of sleep. This is likely due to the influence of the circadian system, which staves off sleep during certain times of the day.

Validation of Fitbit Charge 2 Sleep and Heart Rate Estimates Against Polysomnographic Measures in Shift Workers: Naturalistic Study.

BACKGROUND: Multisensor fitness trackers offer the ability to longitudinally estimate sleep quality in a home environment with the potential to outperform traditional actigraphy. To benefit from these new tools for objectively assessing sleep for clinical and research purposes, multisensor wearable devices require careful validation against the gold standard of sleep polysomnography (PSG). Naturalistic studies favor validation. OBJECTIVE: This study aims to validate the Fitbit Charge 2 against portable home PSG in a shift-work population composed of 59 first responder police officers and paramedics undergoing shift work. METHODS: A reliable comparison between the two measurements was ensured through the data-driven alignment of a PSG and Fitbit time series that was recorded at night. Epoch-by-epoch analyses and Bland-Altman plots were used to assess sensitivity, specificity, accuracy, the Matthews correlation coefficient, bias, and limits of agreement. RESULTS: Sleep onset and offset, total sleep time, and the durations of rapid eye movement (REM) sleep and non-rapid-eye movement sleep stages N1+N2 and N3 displayed unbiased estimates with nonnegligible limits of agreement. In contrast, the proprietary Fitbit algorithm overestimated REM sleep latency by 29.4 minutes and wakefulness after sleep onset (WASO) by 37.1 minutes. Epoch-by-epoch analyses indicated better specificity than sensitivity, with higher accuracies for WASO (0.82) and REM sleep (0.86) than those for N1+N2 (0.55) and N3 (0.78) sleep. Fitbit heart rate (HR) displayed a small underestimation of 0.9 beats per minute (bpm) and a limited capability to capture sudden HR changes because of the lower time resolution compared to that of PSG. The underestimation was smaller in N2, N3, and REM sleep (0.6-0.7 bpm) than in N1 sleep (1.2 bpm) and wakefulness (1.9 bpm), indicating a state-specific bias. Finally, Fitbit suggested a distribution of all sleep episode durations that was different from that derived from PSG and showed nonbiological discontinuities, indicating the potential limitations of the staging algorithm. CONCLUSIONS: We conclude that by following careful data processing processes, the Fitbit Charge 2 can provide reasonably accurate mean values of sleep and HR estimates in shift workers under naturalistic conditions. Nevertheless, the generally wide limits of agreement hamper the precision of quantifying individual sleep episodes. The value of this consumer-grade multisensor wearable in terms of tackling clinical and research questions could be enhanced with open-source algorithms, raw data access, and the ability to blind participants to their own sleep data.

Gentle rocking movements during sleep in the elderly.

Vestibular stimulation in the form of rocking movements could be a promising non-pharmacological intervention for populations with reduced sleep quality, such as the elderly. We hypothesized that rocking movements influence sleep by promoting comfort. We assessed whether gentle rocking movements can facilitate the transition from wake to sleep, increase sleep spindle density and promote deep sleep in elderly people. We assessed self-reported comfort using a pilot protocol including translational movements and movements along a pendulum trajectory with peak linear accelerations between 0.10 and 0.20 m/s2 . We provided whole-night stimulation using the settings rated most comfortable during the pilot study (movements along a pendulum trajectory with peak linear acceleration of 0.15 m/s2 ). Sleep measures (polysomnography) of two baseline and two movement nights were compared. In our sample (n = 19; eight female; mean age: 66.7 years, standard deviation: 3 years), vestibular stimulation using preferred stimulation settings did not improve sleep. A reduction of delta power was observed, suggesting reduced sleep depth during rocking movements. Sleep fragmentation was similar in both conditions. We did not observe a sleep-promoting effect using settings optimized to be comfortable. This finding could imply that comfort is not the underlying mechanism. At frequencies below 0.3 Hz, the otoliths cannot distinguish tilt from translation. Translational movement trajectories, such as used in previous studies reporting positive effects of rocking, could have caused sensory confusion due to a mismatch between vestibular and other sensory information. We propose that this sensory confusion might be essential to the sleep-promoting effect of rocking movements described in other studies.

Nature and Nurture: Brain Region-Specific Inheritance of Sleep Neurophysiology in Adolescence.

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.

Automatic artefact detection in single-channel sleep EEG recordings.

Quantitative electroencephalogram analysis (e.g. spectral analysis) has become an important tool in sleep research and sleep medicine. However, reliable results are only obtained if artefacts are removed or excluded. Artefact detection is often performed manually during sleep stage scoring, which is time consuming and prevents application to large datasets. We aimed to test the performance of mostly simple algorithms of artefact detection in polysomnographic recordings, derive optimal parameters and test their generalization capacity. We implemented 14 different artefact detection methods, optimized parameters for derivation C3A2 using receiver operator characteristic curves of 32 recordings, and validated them on 21 recordings of healthy participants and 10 recordings of patients (different laboratory) and considered the methods as generalizable. We also compared average power density spectra with artefacts excluded based on algorithms and expert scoring. Analyses were performed retrospectively. We could reliably identify artefact contaminated epochs in sleep electroencephalogram recordings of two laboratories (healthy participants and patients) reaching good sensitivity (specificity 0.9) with most algorithms. The best performance was obtained using fixed thresholds of the electroencephalogram slope, high-frequency power (25-90 Hz or 45-90 Hz) and residuals of adaptive autoregressive models. Artefacts in electroencephalogram data can be reliably excluded by simple algorithms with good performance, and average electroencephalogram power density spectra with artefact exclusion based on algorithms and manual scoring are very similar in the frequency range relevant for most applications in sleep research and sleep medicine, allowing application to large datasets as needed to address questions related to genetics, epidemiology or precision medicine.

Mapping Slow Waves by EEG Topography and Source Localization: Effects of Sleep Deprivation.

Slow waves are a salient feature of the electroencephalogram (EEG) during non-rapid eye movement (non-REM) sleep. The aim of this study was to assess the topography of EEG power and the activation of brain structures during slow wave sleep under normal conditions and after sleep deprivation. Sleep EEG recordings during baseline and recovery sleep after 40 h of sustained wakefulness were analyzed (eight healthy young men, 27 channel EEG). Power maps were computed for the first non-REM sleep episode (where sleep pressure is highest) in baseline and recovery sleep, at frequencies between 0.5 and 2 Hz. Power maps had a frontal predominance at all frequencies between 0.5 and 2 Hz. An additional occipital focus of activity was observed below 1 Hz. Power maps ≤ 1 Hz were not affected by sleep deprivation, whereas an increase in power was observed in the maps ≥ 1.25 Hz. Based on the response to sleep deprivation, low-delta (0.5-1 Hz) and mid-delta activity (1.25-2 Hz) were dissociated. Electrical sources within the cortex of low- and mid-delta activity were estimated using eLORETA. Source localization revealed a predominantly frontal distribution of activity for low-delta and mid-delta activity. Sleep deprivation resulted in an increase in source strength only for mid-delta activity, mainly in parietal and frontal regions. Low-delta activity dominated in occipital and temporal regions and mid-delta activity in limbic and frontal regions independent of the level of sleep pressure. Both, power maps and electrical sources exhibited trait-like aspects.

Intrinsic excitability measures track antiepileptic drug action and uncover increasing/decreasing excitability over the wake/sleep cycle.

Pathological changes in excitability of cortical tissue commonly underlie the initiation and spread of seizure activity in patients suffering from epilepsy. Accordingly, monitoring excitability and controlling its degree using antiepileptic drugs (AEDs) is of prime importance for clinical care and treatment. To date, adequate measures of excitability and action of AEDs have been difficult to identify. Recent insights into ongoing cortical activity have identified global levels of phase synchronization as measures that characterize normal levels of excitability and quantify any deviation therefrom. Here, we explore the usefulness of these intrinsic measures to quantify cortical excitability in humans. First, we observe a correlation of such markers with stimulation-evoked responses suggesting them to be viable excitability measures based on ongoing activity. Second, we report a significant covariation with the level of AED load and a wake-dependent modulation. Our results indicate that excitability in epileptic networks is effectively reduced by AEDs and suggest the proposed markers as useful candidates to quantify excitability in routine clinical conditions overcoming the limitations of electrical or magnetic stimulation. The wake-dependent time course of these metrics suggests a homeostatic role of sleep, to rebalance cortical excitability.

Three decades of continuous wrist-activity recording: analysis of sleep duration.

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.

Interindividual differences in the dynamics of the homeostatic process are trait-like and distinct for sleep versus wakefulness.

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.

Resisting Sleep Pressure: Impact on Resting State Functional Network Connectivity.

In today's 24/7 society, sleep restriction is a common phenomenon which leads to increased levels of sleep pressure in daily life. However, the magnitude and extent of impairment of brain functioning due to increased sleep pressure is still not completely understood. Resting state network (RSN) analyses have become increasingly popular because they allow us to investigate brain activity patterns in the absence of a specific task and to identify changes under different levels of vigilance (e.g. due to increased sleep pressure). RSNs are commonly derived from BOLD fMRI signals but studies progressively also employ cerebral blood flow (CBF) signals. To investigate the impact of sleep pressure on RSNs, we examined RSNs of participants under high (19 h awake) and normal (10 h awake) sleep pressure with three imaging modalities (arterial spin labeling, BOLD, pseudo BOLD) while providing confirmation of vigilance states in most conditions. We demonstrated that CBF and pseudo BOLD signals (measured with arterial spin labeling) are suited to derive independent component analysis based RSNs. The spatial map differences of these RSNs were rather small, suggesting a strong biological substrate underlying these networks. Interestingly, increased sleep pressure, namely longer time awake, specifically changed the functional network connectivity (FNC) between RSNs. In summary, all FNCs of the default mode network with any other network or component showed increasing effects as a function of increased 'time awake'. All other FNCs became more anti-correlated with increased 'time awake'. The sensorimotor networks were the only ones who showed a within network change of FNC, namely decreased connectivity as function of 'time awake'. These specific changes of FNC could reflect both compensatory mechanisms aiming to fight sleep as well as a first reduction of consciousness while becoming drowsy. We think that the specific changes observed in functional network connectivity could imply an impairment of information transfer between the affected RSNs.

Developmental Changes in Sleep Oscillations during Early Childhood.

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.

Development of nap neurophysiology: preliminary insights into sleep regulation in early childhood.

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.

Vigilance and wake EEG architecture in simulated hyperammonaemia: a pilot study on the effects of L-Ornithine-L-Aspartate (LOLA) and caffeine.

UNLABELLED: Hyperammonaemia/mild hepatic encephalopathy (HE) can be simulated by the oral administration of a so-called amino acid challenge (AAC). This study sought to assess the effects of the AAC alone and in combination with either ammonia-lowering [L-ornithine-L-aspartate (LOLA)] or vigilance-enhancing medication (caffeine). Six patients with cirrhosis (5 males; 61.3 ± 9.2 years; 5 Child A, 1 Child B) and six healthy volunteers (5 males; 49.8 ± 10.6 years) were studied between 08:00 and 19:00 on Monday of three consecutive weeks. The following indices were obtained: hourly capillary ammonia, hourly subjective sleepiness, paper & pencil/computerized psychometry and wake electroencephalography (EEG) at 12:00, i.e. at the time of the maximum expected effect of the AAC. RESULTS: On average, patients had worse neuropsychological performance and slower EEG than healthy volunteers in all conditions but differences did not reach significance. In healthy volunteers, the post-AAC increase in capillary ammonia levels was contained by both the administration of LOLA and of caffeine (significant differences between 10:00 and 14:00 h). The administration of caffeine also resulted in a reduction in subjective sleepiness and in the amplitude of the EEG on several frontal/temporal-occipital sites (p < 0.05; paired t-test). Changes in ammonia levels, subjective sleepiness and the EEG in the three conditions were less obvious in patients. In conclusion, both LOLA and caffeine contained the AAC-induced increase in capillary ammonia, especially in healthy volunteers. Caffeine also counteracted the AAC effects on sleepiness/EEG amplitude. The association of ammonia-lowering and vigilance-enhancing medication in the management of HE is worthy of further study.

Developmental Changes in Sleep Spindle Characteristics and Sigma Power across Early Childhood.

Sleep spindles, a prominent feature of the non-rapid eye movement (NREM) sleep electroencephalogram (EEG), are linked to cognitive abilities. Early childhood is a time of rapid cognitive and neurophysiological maturation; however, little is known about developmental changes in sleep spindles. In this study, we longitudinally examined trajectories of multiple sleep spindle characteristics (i.e., spindle duration, frequency, integrated spindle amplitude, and density) and power in the sigma frequency range (10-16 Hz) across ages 2, 3, and 5 years (n = 8; 3 males). At each time point, nocturnal sleep EEG was recorded in-home after 13-h of prior wakefulness. Spindle duration, integrated spindle amplitude, and sigma power increased with age across all EEG derivations (C3A2, C4A1, O2A1, and O1A2; all ps < 0.05). We also found a developmental decrease in mean spindle frequency (p < 0.05) but no change in spindle density with increasing age. Thus, sleep spindles increased in duration and amplitude but decreased in frequency across early childhood. Our data characterize early developmental changes in sleep spindles, which may advance understanding of thalamocortical brain connectivity and associated lifelong disease processes. These findings also provide unique insights into spindle ontogenesis in early childhood and may help identify electrophysiological features related to healthy and aberrant brain maturation.

Dopaminergic role in regulating neurophysiological markers of sleep homeostasis in humans.

While dopamine affects fundamental brain processes such as movement control, emotional responses, addiction, and pain, the roles for this neurotransmitter in regulating wakefulness and sleep are incompletely understood. Genetically modified animal models with reduced dopamine clearance exhibit hypersensitivity to caffeine, reduced-responsiveness to modafinil, and increased homeostatic response to prolonged wakefulness when compared with wild-type animals. Here we studied sleep-wake regulation in humans and combined pharmacogenetic and neurophysiologic methods to analyze the effects of the 3'-UTR variable-number-tandem-repeat polymorphism of the gene (DAT1, SLC6A3) encoding dopamine transporter (DAT). Previous research demonstrated that healthy homozygous 10-repeat (10R/10R) allele carriers of this genetic variant have reduced striatal DAT protein expression when compared with 9-repeat (9R) allele carriers. Objective and subjective estimates of caffeine sensitivity were higher in 10R allele homozygotes than in carriers of the 9R allele. Moreover, caffeine and modafinil affected wakefulness-induced changes in functional bands (delta, sigma, beta) of rhythmic brain activity in wakefulness and sleep in a DAT1 genotype-dependent manner. Finally, the sleep deprivation-induced increase in well established neurophysiologic markers of sleep homeostasis, including slow-wave sleep, electroencephalographic slow-wave activity (0.5-4.5 Hz), and number of low-frequency (0.5-2.0 Hz) oscillations in non-rapid-eye-movement sleep, was significantly larger in the 10R/10R genotype than in the 9R allele carriers of DAT1. Together, the data suggest that the dopamine transporter contributes to homeostatic sleep-wake regulation in humans.

The spectrum of the non-rapid eye movement sleep electroencephalogram following total sleep deprivation is trait-like.

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.

Inter-individual and intra-individual variation of the effects of pulsed RF EMF exposure on the human sleep EEG.

Pulse-modulated radiofrequency electromagnetic fields (RF EMF) can alter brain activity during sleep; increases of electroencephalographic (EEG) power in the sleep spindle (13.75-15.25 Hz) and delta-theta (1.25-9 Hz) frequency range have been reported. These field effects show striking inter-individual differences. However, it is still unknown whether individual subjects react in a similar way when repeatedly exposed. Thus, our study aimed to investigate inter-individual variation and intra-individual stability of field effects. To do so, we exposed 20 young male subjects twice for 30 min prior to sleep to the same amplitude modulated 900 MHz (2 Hz pulse, 20 Hz Gaussian low-pass filter and a ratio of peak-to-average of 4) RF EMF (spatial peak absorption of 2 W/kg averaged over 10 g) 2 weeks apart. The topographical analysis of EEG power during all-night non-rapid eye movement sleep revealed: (1) exposure-related increases in delta-theta frequency range in several fronto-central electrodes; and (2) no differences in spindle frequency range. We did not observe reproducible within-subject RF EMF effects on sleep spindle and delta-theta activity in the sleep EEG and it remains unclear whether a biological trait of how the subjects' brains react to RF EMF exists.

Fading signatures of critical brain dynamics during sustained wakefulness in humans.

Sleep encompasses approximately a third of our lifetime, yet its purpose and biological function are not well understood. Without sleep optimal brain functioning such as responsiveness to stimuli, information processing, or learning may be impaired. Such observations suggest that sleep plays a crucial role in organizing or reorganizing neuronal networks of the brain toward states where information processing is optimized. Increasing evidence suggests that cortical neuronal networks operate near a critical state characterized by balanced activity patterns, which supports optimal information processing. However, it remains unknown whether critical dynamics is affected in the course of wake and sleep, which would also impact information processing. Here, we show that signatures of criticality are progressively disturbed during wake and restored by sleep. We demonstrate that the precise power-laws governing the cascading activity of neuronal avalanches and the distribution of phase-lock intervals in human electroencephalographic recordings are increasingly disarranged during sustained wakefulness. These changes are accompanied by a decrease in variability of synchronization. Interpreted in the context of a critical branching process, these seemingly different findings indicate a decline of balanced activity and progressive distance from criticality toward states characterized by an imbalance toward excitation where larger events prevail dynamics. Conversely, sleep restores the critical state resulting in recovered power-law characteristics in activity and variability of synchronization. These findings support the intriguing hypothesis that sleep may be important to reorganize cortical network dynamics to a critical state thereby assuring optimal computational capabilities for the following time awake.