Developmental changes in brain connectivity assessed using the sleep EEG

Infant sleep EEG features at 4 months as biomarkers of neurodevelopment at 18 months

BACKGROUND

Sleep parameters evolve in parallel with neurodevelopment. Sleep participates in synaptic homeostasis and memory consolidation and infant sleep parameters correlate with later aspects of early childhood cognition.

METHODS

Typically developing, term-born infants had a diurnal sleep-EEG at 4 months and Griffiths III developmental assessment at 18 months. EEG analysis included sleep macrostructure (i.e. durations of total sleep and sleep stages, and latencies to sleep and REM), sleep spindle features, and quantitative EEG features (qEEG): interhemispheric connectivity and spectral power. We assessed the correlations between these EEG features and Griffiths III quotients.

RESULTS

Sleep recordings from 92 infants were analyzed. Sleep latency was positively associated with the Griffiths III Foundations of Learning subscale and N3 sleep duration was positively correlated with the Personal-Social-Emotional subscale. Sleep spindle synchrony was negatively associated with Eye and Hand Coordination, Personal-Social-Emotional, Gross Motor, and General Development quotients. Sleep spindle duration was negatively associated with the Personal-Social-Emotional and Gross Motor subscales. In some sleep states, delta 1 and 2 EEG spectral power and interhemispheric coherence measures were correlated with subscale quotients.

CONCLUSION

Certain sleep features in the EEG of 4-month-old infants are associated with neurodevelopment at 18 months and may be useful early biomarkers of neurodevelopment.

IMPACT

This study shows that the EEG during infant sleep may provide insights into later neurodevelopmental outcomes. We have examined novel EEG sleep spindle features and shown that spindle duration and synchrony may help predict neurodevelopmental outcomes. Sleep macrostructure elements such as latency to sleep, N3 duration, and qEEG features such as interhemispheric coherence and spectral power measures at 4 months may be useful for the assessment of future neurodevelopmental outcomes. Due to exceptional neuroplasticity in infancy, EEG biomarkers of neurodevelopment may support early and targeted intervention to optimize outcomes.

Sleep Fragmentation Modulates the Neurophysiological Correlates of Cognitive Fatigue

Cognitive fatigue (CF) is a critical factor affecting performance and well-being. It can be altered in suboptimal sleep quality conditions, e.g., in patients suffering from obstructive sleep apnea who experience both intermittent hypoxia and sleep fragmentation (SF). Understanding the neurophysiological basis of SF in healthy individuals can provide insights to improve cognitive functioning in disrupted sleep conditions. In this electroencephalographical (EEG) study, we investigated in 16 healthy young participants the impact of experimentally induced SF on the neurophysiological correlates of CF measured before, during, and after practice on the TloadDback, a working memory task tailored to each individual's maximal cognitive resources. The participants spent three consecutive nights in the laboratory two times, once in an undisrupted sleep (UdS) condition and once in an SF condition induced by non-awakening auditory stimulations, counterbalanced and performed the TloadDback task both in a high (HCL) and a low (LCL) cognitive load condition. EEG activity was recorded during wakefulness in the 5 min resting state immediately before and after, as well as during the 16 min of the TloadDback task practice. In the high cognitive load under a sleep-fragmentation (HCL/SF) condition, high beta power increased during the TloadDback, indicating heightened cognitive effort, and the beta and alpha power increased in the post- vs. pre-task resting state, suggesting a relaxation rebound. In the low cognitive load/undisturbed sleep (LCL/UdS) condition, low beta activity increased, suggesting a relaxed focus, as well as mid beta activity associated with active thinking. These findings highlight the dynamic impact of SF on the neurophysiological correlates of CF and underscore the importance of sleep quality and continuity to maintain optimal cognitive functioning.

Inter-hemispheric somatosensory coherence and parental stress in hypersensitivity at 8 months old: An electroencephalography study

OBJECTIVE

Infant hypersensitivity affects daily challenges and parental stress. Although the crucial role of tactile sensation in infants' brain function has been highlighted, hypersensitive infants and their families lack support. Electroencephalography may be useful for understanding hypersensitivity traits. We investigated the relationship between infant perceptual hypersensitivity and parental stress, somatosensory-evoked potential (SEP), and magnitude-squared coherence (MSC) in the general population.

METHODS

Infants aged 8 months (n = 63) were evaluated for hypersensitivity and parental stress using a questionnaire and for cortical activity using electroencephalography. Vibration stimuli were applied to the infant's left foot. SEP components that peaked around 150 ms (N2) and at 200 ms (P2) after stimulus onset were evaluated by amplitude and latency at the midline electrode (Cz) and MSC between the midline electrodes (C3-C4).

RESULTS

Parental stress was associated with infant hypersensitivity. The latency of Cz was delayed, and C3-C4 delta MSC was high in infants with hypersensitivity.

CONCLUSIONS

Increasing inter-hemispheric MSC synchrony in the stimulated condition in infants with hypersensitivity suggested atypical somatosensory cortical function.

SIGNIFICANCE

These findings contribute to identifying, understanding the mechanisms of, and developing effective coping strategies for early-stage hypersensitivity.

High stability of EEG spectral power across polysomnography and multiple sleep latency tests in good sleepers and chronic insomniacs

To assess the stability of electroencephalographic (EEG) spectral features across overnight polysomnography (PSG) and daytime multiple sleep latency tests (MSLTs) in chronic insomniacs (CIs) and normal controls (NCs). A total of 20 NCs and 22 CIs underwent standard PSG and MSLTs. Spectral analyses were performed on EEG data from PSG and MSLTs and absolute and relative power in central, frontal and occipital channels were obtained for wake (W) and non-rapid eye movement sleep stage 1 and 2 (N1, N2). Intraclass correlation coefficients (ICCs) were used to assess the stability of EEG spectral power across PSG and MSLTs for W, N1 and N2. The absolute power of all frequency bands except delta exhibited high stability across PSG and MSLTs in both NCs and CIs (ICCs ranged from 0.430 to 0.978). Although delta absolute power was stable in NCs during N1 and N2 stages (ICCs ranged from 0.571 to 0.835), it tended to be less stable in CIs during W and sleep stages (ICCs ranged from 0.042 to 0.807). We also observed lower stability of relative power compared to absolute power though the majority of relative power outcomes maintained high stability in both groups (ICCs in relative power ranged from 0.044 to 0.962). Most EEG spectral bandwidths across PSG and MSLT in W, N1 and N2 show high stability in good sleepers and chronic insomniacs. EEG signals from either an overnight PSG or a daytime MSLT may be useful for reliably exploring EEG spectral features during wakefulness or sleep.

Bedtime to the brain: how infants' sleep behaviours intertwine with non-rapid eye movement sleep electroencephalography features

Adequate sleep is critical for development and facilitates the maturation of the neurophysiological circuitries at the basis of cognitive and behavioural function. Observational research has associated early life sleep problems with worse later cognitive, psychosocial, and somatic health outcomes. Yet, the extent to which day-to-day sleep behaviours (e.g., duration, regularity) in early life relate to non-rapid eye movement (NREM) neurophysiology-acutely and the long-term-remains to be studied. We measured sleep behaviours in 32 healthy 6-month-olds assessed with actimetry and neurophysiology with high-density electroencephalography (EEG) to investigate the association between NREM sleep and habitual sleep behaviours. Our study revealed four findings: first, daytime sleep behaviours are related to EEG slow-wave activity (SWA). Second, night-time movement and awakenings from sleep are connected with spindle density. Third, habitual sleep timing is linked to neurophysiological connectivity quantified as delta coherence. And lastly, delta coherence at 6 months predicts night-time sleep duration at 12 months. These novel findings widen our understanding that infants' sleep behaviours are closely intertwined with three particular levels of neurophysiology: sleep pressure (determined by SWA), the maturation of the thalamocortical system (spindles), and the maturation of cortical connectivity (coherence). The crucial next step is to extend this concept to clinical groups to objectively characterise infants' sleep behaviours 'at risk' that foster later neurodevelopmental problems.

Sleep restriction effects on sleep spindles in adolescents and relation of these effects to subsequent daytime sleepiness and cognition

STUDY OBJECTIVES

Limiting spindle activity via sleep restriction could explain some of the negative cognitive effects of sleep loss in adolescents. The current study evaluates how sleep restriction affects sleep spindle number, incidence, amplitude, duration, and wave frequency and tests whether sleep restriction effects on spindles change across the years of adolescence. The study determines whether sleep restriction effects on daytime sleepiness, vigilance, and cognition are related to changes in sleep spindles.

METHODS

In each year of this 3-year longitudinal study, 77 participants, ranging in age from 10 to 16 years, each completed three different time in bed (TIB) schedules: 7, 8.5, or 10 hours in bed for 4 consecutive nights. A computer algorithm detected and analyzed sleep spindles in night four central and frontal electroencephalogram. Objective and self-reported daytime sleepiness and cognition were evaluated on the day following the 4th night.

RESULTS

For 7 versus 10 hours TIB average all-night frontal and central spindle counts were reduced by 35% and 32%, respectively. Reducing TIB also significantly decreased spindle incidence in the first 5 hours of non-rapid eye movement sleep, produced small but significant reductions in spindle amplitude, and had little to no effect on spindle duration and spindle wave frequency. Sleep restriction effects did not change with age. The reductions in spindle count and incidence were related to daytime sleepiness on the following day but were not related to working memory.

CONCLUSIONS

The sleep loss effects on daytime functioning in adolescents are partially mediated by reduced sleep spindles impacting daytime sleepiness.

The sleeping brain's connectivity and family environment: characterizing sleep EEG coherence in an infant cohort

Brain connectivity closely reflects brain function and behavior. Sleep EEG coherence, a measure of brain's connectivity during sleep, undergoes pronounced changes across development under the influence of environmental factors. Yet, the determinants of the developing brain's sleep EEG coherence from the child's family environment remain unknown. After characterizing high-density sleep EEG coherence in 31 healthy 6-month-old infants by detecting strongly synchronized clusters through a data-driven approach, we examined the association of sleep EEG coherence from these clusters with factors from the infant's family environment. Clusters with greatest coherence were observed over the frontal lobe. Higher delta coherence over the left frontal cortex was found in infants sleeping in their parents' room, while infants sleeping in a room shared with their sibling(s) showed greater delta coherence over the central parts of the frontal cortex, suggesting a link between local brain connectivity and co-sleeping. Finally, lower occipital delta coherence was associated with maternal anxiety regarding their infant's sleep. These interesting links between sleep EEG coherence and family factors have the potential to serve in early health interventions as a new set of targets from the child's immediate environment.

Adolescent sleep and the foundations of prefrontal cortical development and dysfunction

Modern life poses many threats to good-quality sleep, challenging brain health across the lifespan. Curtailed or fragmented sleep may be particularly damaging during adolescence, when sleep disruption by delayed chronotypes and societal pressures coincides with our brains preparing for adult life via intense refinement of neural connectivity. These vulnerabilities converge on the prefrontal cortex, one of the last brain regions to mature and a central hub of the limbic-cortical circuits underpinning decision-making, reward processing, social interactions and emotion. Even subtle disruption of prefrontal cortical development during adolescence may therefore have enduring impact. In this review, we integrate synaptic and circuit mechanisms, glial biology, sleep neurophysiology and epidemiology, to frame a hypothesis highlighting the implications of adolescent sleep disruption for the neural circuitry of the prefrontal cortex. Convergent evidence underscores the importance of acknowledging, quantifying and optimizing adolescent sleep's contributions to normative brain development and to lifelong mental health.

Relations between sleep patterns early in life and brain development: A review

Sleep supports healthy cognitive functioning in adults. Over the past decade, research has emerged advancing our understanding of sleep's role in cognition during development. Infancy and early childhood are marked by unique changes in sleep physiology and sleep patterns as children transition from biphasic to monophasic sleep. Growing evidence suggests that, during development, there are parallel changes in sleep and the brain and that sleep may modulate brain structure and activity and vice versa. In this review, we survey studies of sleep and brain development across childhood. By summarizing these findings, we provide a unique understanding of the importance of healthy sleep for healthy brain and cognitive development. Moreover, we discuss gaps in our understanding, which will inform future research.

Early Life Sleep Deprivation and Brain Development: Insights From Human and Animal Studies

Adequate sleep especially during developmental stages of life, is considered essential for normal brain development and believed to play an important role in promoting healthy cognitive and psychosocial development, while persistent sleep disturbances and/or sleep deprivation during early life are believed to trigger many mental ailments such as anxiety disorders, depression, and cognitive impairment. Initially it was suggested that adverse mental health conditions adversely affect sleep, however, it is now accepted that this association is bidirectional. In fact, sleep disturbances are listed as a symptom of many mental health disorders. Of special interest is the association between early life sleep deprivation and its negative mental health outcomes. Studies have linked persistent early life sleep deprivation with later life behavioral and cognitive disturbances. Neurobiological underpinnings responsible for the negative outcomes of early life sleep deprivation are not understood. This is a significant barrier for early therapeutic and/or behavioral intervention, which can be feasible only if biological underpinnings are well-understood. Animal studies have provided useful insights in this area. This article focusses on the knowledge gained from the research conducted in the area of early life sleep deprivation, brain development, and behavioral function studies.

Brain functional and effective connectivity based on electroencephalography recordings: A review

Functional connectivity and effective connectivity of the human brain, representing statistical dependence and directed information flow between cortical regions, significantly contribute to the study of the intrinsic brain network and its functional mechanism. Many recent studies on electroencephalography (EEG) have been focusing on modeling and estimating brain connectivity due to increasing evidence that it can help better understand various brain neurological conditions. However, there is a lack of a comprehensive updated review on studies of EEG-based brain connectivity, particularly on visualization options and associated machine learning applications, aiming to translate those techniques into useful clinical tools. This article reviews EEG-based functional and effective connectivity studies undertaken over the last few years, in terms of estimation, visualization, and applications associated with machine learning classifiers. Methods are explored and discussed from various dimensions, such as either linear or nonlinear, parametric or nonparametric, time-based, and frequency-based or time-frequency-based. Then it is followed by a novel review of brain connectivity visualization methods, grouped by Heat Map, data statistics, and Head Map, aiming to explore the variation of connectivity across different brain regions. Finally, the current challenges of related research and a roadmap for future related research are presented.

Heritability of Sleep and Its Disorders in Childhood and Adolescence

PURPOSE OF REVIEW

This review summarizes recent literature on the heritability of sleep and sleep disorders in childhood and adolescence. We also identify gaps in the literature and priorities for future research.

RECENT FINDINGS

Findings indicate that age, measurement method, reporter, and timing of sleep measurements can influence heritability estimates. Recent genome-wide association studies (GWAS) have identified differences in the heritability of sleep problems when ancestral differences are considered, but sample sizes are small compared to adult GWAS. Most studies focus on sleep variables in the full range rather than on disorder. Studies using objective measures of sleep typically comprised small samples.

SUMMARY

Current evidence demonstrates a wide range of heritability estimates across sleep phenotypes in childhood and adolescence, but research in larger samples, particularly using objective sleep measures and GWAS, is needed. Further understanding of environmental mechanisms and the interaction between genes and environment is key for future research.

Interhemispheric asymmetry during NREM sleep in the dog

Functional hemispheric asymmetry was evidenced in many species during sleep. Dogs seem to show hemispheric asymmetry during wakefulness; however, their asymmetric neural activity during sleep was not yet explored. The present study investigated interhemispheric asymmetry in family dogs using non-invasive polysomnography. EEG recordings during 3-h-long afternoon naps were carried out (N = 19) on two occasions at the same location. Hemispheric asymmetry was assessed during NREM sleep, using bilateral EEG channels. To include periods with high homeostatic sleep pressure and to reduce the variance of the time spent in NREM sleep between dogs, the first two sleep cycles were analysed. Left hemispheric predominance of slow frequency range was detected in the first sleep cycle of sleep recording 1, compared to the baseline level of zero asymmetry as well as to the first sleep cycle of sleep recording 2. Regarding the strength of hemispheric asymmetry, we found greater absolute hemispheric asymmetry in the second sleep cycle of sleep recording 1 and 2 in the frequency ranges of alpha, sigma and beta, compared to the first sleep cycle. Differences between sleep recordings and consecutive sleep cycles might be indicative of adaptation-like processes, but do not closely resemble the results described in humans.

REM Sleep Microstates in the Human Anterior Thalamus

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

Gender differences in adolescent sleep neurophysiology: a high-density sleep EEG study

During adolescence, differences between males and females in physiology, behavior and risk for psychopathology are accentuated. The goal of the current study was to examine gender differences in sleep neurophysiology using high-density sleep EEG in early adolescence. We examined gender differences in sleep EEG power and coherence across frequency bands for both NREM and REM sleep in a sample of 61 adolescents (31 girls and 30 boys; mean age = 12.48; SD = 1.34). In addition, sleep spindles were individually detected and characterized. Compared to boys, girls had significantly greater spindle activity, as reflected in higher NREM sigma power, spindle amplitude, spindle frequency and spindle density over widespread regions. Furthermore, power in higher frequency bands (16.2–44 Hz) was larger in girls than boys in a state independent manner. Oscillatory activity across frequency bands and sleep states was generally more coherent in females as compared to males, suggesting greater connectivity in females. An exception to this finding was the alpha band during NREM and REM sleep, where coherence was higher (NREM) or not different (REM) in boys compared to girls. Sleep spindles are generated through thalamocortical circuits, and thus, the greater spindle activity across regions in females may represent a stronger thalamocortical circuit in adolescent females as compared to males. Moreover, greater global connectivity in females may reflect functional brain differences with implications for cognition and mental health. Given the pronounced gender differences, our study highlights the importance of taking gender into account when designing and interpreting studies of sleep neurophysiology.

Slow-wave activity and sigma activities are associated with psychomotor development at 8 months of age

STUDY OBJECTIVES

The electrophysiological properties of non-rapid eye movement sleep (NREM) EEG are homeostatically modulated on global and local use-dependent levels. Furthermore, the local NREM quality reflects age-dependent brain maturation and individual, age-independent, and psychomotor potential. Cortical maturation and its electrophysiological marker, Slow-wave activity (SWA), as well as sleep spindles are known to change in topography and quality during the early years of life, but their associations with psychomotor development in infants are unknown. Therefore, we aimed to evaluate the local properties of SWA and spindles (sigma power) and ascertain whether they correlate with psychomotor development in 8-month-old infants.

METHODS

Ambulatory polysomnographies were recorded in 56 infants at 8 months of age to calculate the local SWA and sigma powers. The associations between the SWA and sigma powers and psychomotor development (Bayley-III) were examined in 36 of these infants.

RESULTS

In both hemispheres, the highest SWA and sigma powers were found occipitally and centrally, respectively, with higher powers in the right hemisphere than in the left. The Bayley-III correlated with local SWA and sigma powers: the occipital SWA and centro-occipital sigma correlated with cognitive scales, and the frontal and occipital SWA and centro-occipital sigma correlated with language and fine motor scales. Most of the correlations were unilateral.

CONCLUSIONS

In 8-month-old infants, the NREM sleep quality shows local differences that are mostly attributable to the topical phase of brain maturation. The local NREM parameters correlate with psychomotor development.

Environmental Factors Shape Sleep EEG Connectivity During Early Adolescence

Quantifying the degree to which genetic and environmental factors shape brain network connectivity is critical to furthering our understanding of the developing human brain. Sleep, a state of sensory disengagement, provides a unique opportunity to study brain network activity noninvasively by means of sleep electroencephalography (EEG) coherence. We conducted a high-density sleep EEG study in monozygotic (MZ; n = 38; mean age = 12.46; 20 females) and dizygotic (DZ; n = 24; mean age = 12.50; 12 females) twins to assess the heritability of sleep EEG coherence in early adolescence—a period of significant brain rewiring. Structural equation modeling was used to estimate three latent factors: genes, environmental factors shared between twins and environmental factors unique to each twin. We found a strong contribution of unique environmental factors (66% of the variance) and moderate genetic influence (19% of the variance) on sleep EEG coherence across frequencies and sleep states. An exception to this was sleep spindle activity, an index of the thalamocortical network, which showed on average a genetic contribution of 48% across connections. Furthermore, we observed high intraindividual stability of coherence across two consecutive nights suggesting that despite only a modest genetic contribution, sleep EEG coherence is like a trait. Our findings in adolescent humans are in line with earlier findings in animals that show the primordial cerebral map and its connections are plastic and it is through interaction with the environment that the pattern of brain network connectivity is shaped. Therefore, even in twins living together, small differences in the environment may cascade into meaningful differences in brain connectivity.

Association Between Prenatal Exposure to Alcohol and Tobacco and Neonatal Brain Activity: Results From the Safe Passage Study

IMPORTANCE

Research to date has not determined a safe level of alcohol or tobacco use during pregnancy. Electroencephalography (EEG) is a noninvasive measure of cortical function that has previously been used to examine effects of in utero exposures and associations with neurodevelopment.

OBJECTIVE

To examine the association of prenatal exposure to alcohol (PAE) and tobacco smoking (PTE) with brain activity in newborns.

DESIGN, SETTING, AND PARTICIPANTS

This prospective cohort study enrolled mother-newborn dyads from December 2011 through August 2015, with data analyzed from June 2018 through June 2019. Pregnant women were recruited from clinical sites in Cape Town, South Africa, and the Northern Plains region of the US. Participants were a subset of newborns enrolled in the Safe Passage Study. Exclusions included birth at less than 37 or more than 41 weeks' gestation, multiple birth, or maternal use of psychiatric medication during pregnancy.

EXPOSURES

PAE and PTE groups were determined by cluster analysis.

MAIN OUTCOMES AND MEASURES

Analyses of covariance were run on EEG spectral power at 12 scalp locations across the frequency spectrum from 1 to 45 Hz in 3-Hz bins by sleep state.

RESULTS

The final sample consisted of 1739 newborns (median [interquartile range] gestational age at birth, 39.29 [1.57] weeks; 886 [50.9%] were female; median [interquartile range] newborn age at assessment, 48.53 [44.96] hours). Newborns whose mothers were in the low continuous (95% CI, -0.379 to -0.031; P < .05; 95% CI, -0.379 to -0.045; P < .05), quit (95% CI, -0.419 to -0.127; P < .001; 95% CI, -0.398 to -0.106; P < .005), and moderate or high continuous (95% CI, -0.430 to -0.124; P < .001; 95% CI, -0.420 to -0.119; P < .005) PAE clusters had increased 4- to 6-Hz and 7- to 9-Hz left-temporal EEG power. Newborns with moderate or high continuous PTE had decreased 19- to 21-Hz (95% CI, 0.034 to 0.327; P < .05) and 22- to 24-Hz (95% CI, 0.022 to 0.316; P < .05) right-central EEG compared with newborns with no PTE. Newborns with moderate or high continuous PTE had significantly decreased 22- to 36-Hz right-central EEG power compared with the quit smoking group (22-24 Hz, 95% CI, 0.001 to 0.579; P < .05; 25-27 Hz, 95% CI, 0.008 to 0.586; P < .05; 28-30 Hz, 95% CI, 0.028 to 0.607; P < .05; 31-33 Hz, 95% CI, 0.038 to 0.617; P < .05; 34-36 Hz, 95% CI, 0.057 to 0.636; P < .05).

CONCLUSIONS AND RELEVANCE

These findings suggest that even low levels of PAE or PTE are associated with changes in offspring brain development.

Later School Start Time: The Impact of Sleep on Academic Performance and Health in the Adolescent Population

The crucial role of sleep in physical and mental health is well known, especially during the developmental period. In recent years, there has been a growing interest in examining the relationship between sleep patterns and school performance in adolescents. At this stage of life, several environmental and biological factors may affect both circadian and homeostatic regulation of sleep. A large part of this population does not experience adequate sleep, leading to chronic sleep restriction and/or disrupted sleep-wake cycles. Studies investigating the effects of different sleep-wake schedules on academic achievement showed that impaired sleep quality and quantity are associated with decreased learning ability and compromised daytime functioning. This review focuses on the most recent studies that evaluated the effects of modified school start time on sleep patterns and related outcomes. Moreover, based on the available empirical evidence, we intend to propose a direction for future studies targeted to implement prevention or treatment programs by modifying sleep timing.

A simple sleep EEG marker in childhood predicts brain myelin 3.5 years later

Epidemiological research reveals that insufficient sleep in children has negative cognitive and emotional consequences; however, the physiological underpinnings of these observations remain understudied. We tested the hypothesis that the topographical distribution of deep sleep slow wave activity during the childhood predicts brain white matter microstructure (myelin) 3.5 y later. Healthy children underwent sleep high-density EEG at baseline (n = 13; ages 2.4-8.0 y) and follow-up (n = 14; ages 5.5-12.2 y). At follow-up, myelin (myelin water fraction) and cortical morphology were also quantified. Our investigation revealed 3 main findings. (1) The Frontal/Occipital (F/O)-ratio at baseline strongly predicted whole brain myelin at follow-up. (2) At follow-up, the F/O-ratio was only minimally (negatively) linked to brain myelin. (3) Cortical morphology was not related to the F/O-ratio, neither at baseline nor at follow-up. Our results support the hypothesis that during child development EEG markers during sleep longitudinally predict brain myelin content. Data extend previous findings reporting a link between EEG markers of sleep need and cortical morphology, by supporting the hypothesis that sleep is a necessary component to underlying processes of brain, and specifically myelin, maturation. In line with the overarching theory that sleep contributes to neurodevelopmental processes, it remains to be investigated whether chronic sleep loss negatively affects white matter myelin microstructure growth during sensitive periods of development.

Mental Sleep Activity and Disturbing Dreams in the Lifespan

Sleep significantly changes across the lifespan, and several studies underline its crucial role in cognitive functioning. Similarly, mental activity during sleep tends to covary with age. This review aims to analyze the characteristics of dreaming and disturbing dreams at different age brackets. On the one hand, dreams may be considered an expression of brain maturation and cognitive development, showing relations with memory and visuo-spatial abilities. Some investigations reveal that specific electrophysiological patterns, such as frontal theta oscillations, underlie dreams during sleep, as well as episodic memories in the waking state, both in young and older adults. On the other hand, considering the role of dreaming in emotional processing and regulation, the available literature suggests that mental sleep activity could have a beneficial role when stressful events occur at different age ranges. We highlight that nightmares and bad dreams might represent an attempt to cope the adverse events, and the degrees of cognitive-brain maturation could impact on these mechanisms across the lifespan. Future investigations are necessary to clarify these relations. Clinical protocols could be designed to improve cognitive functioning and emotional regulation by modifying the dream contents or the ability to recall/non-recall them.

Across-night dynamics in traveling sleep slow waves throughout childhood

Study Objectives

Sleep slow waves behave like traveling waves and are thus a marker for brain connectivity. Across a night of sleep in adults, wave propagation is scaled down, becoming more local. Yet, it is unknown whether slow wave propagation undergoes similar across-night dynamics in childhood-a period of extensive cortical rewiring.

Methods

High-density electroencephalography (EEG; 128 channels) was recorded during sleep in three groups of healthy children: 2.0-4.9 years (n = 11), 5.0-8.9 years (n = 9) and 9.0-16.9 years (n = 9). Slow wave propagation speed, distance, and cortical involvement were quantified. To characterize across-night dynamics, the 20% most pronounced (highest amplitude) slow waves were subdivided into five time-based quintiles.

Results

We found indications that slow wave propagation distance decreased across a night of sleep. We observed an interesting interaction of across-night slow wave propagation dynamics with age (p < 0.05). When comparing the first and last quintiles, there was a trend level difference between age groups: 2- to 4.9-year-old children showed an 11.9% across-night decrease in slow wave propagation distance, which was not observed in the older two age groups. Regardless of age, cortical involvement decreased by 10.4%-23.7% across a night of sleep. No across-night changes were observed in slow wave speed.

Conclusions

Findings provide evidence that signatures of brain connectivity undergo across-night dynamics specific to maturational periods. These results suggest that across-night dynamics in slow wave propagation distance reflect heightened plasticity in underlying cerebral networks specific to developmental periods.

Maturation changes the excitability and effective connectivity of the frontal lobe: A developmental TMS-EEG study

The combination of transcranial magnetic stimulation with simultaneous electroencephalography (TMS-EEG) offers direct neurophysiological insight into excitability and connectivity within neural circuits. However, there have been few developmental TMS-EEG studies to date, and they all have focused on primary motor cortex stimulation. In the present study, we used navigated high-density TMS-EEG to investigate the maturation of the superior frontal cortex (dorsal premotor cortex [PMd]), which is involved in a broad range of motor and cognitive functions known to develop with age. We demonstrated that reactivity to frontal cortex TMS decreases with development. We also showed that although frontal cortex TMS elicits an equally complex TEP waveform in all age groups, the statistically significant between-group differences in the topography of the TMS-evoked peaks and differences in current density maps suggest changes in effective connectivity of the right PMd with maturation. More generally, our results indicate that direct study of the brain's excitability and effective connectivity via TMS-EEG co-registration can also be applied to pediatric populations outside the primary motor cortex, and may provide useful information for developmental studies and studies on developmental neuropsychiatric disorders.

Sleep deprivation, oxidative stress and inflammation

Adequate sleep is essential for normal brain function, especially during early life developmental stages as postnatal brain maturation occurs during the critical period of childhood and adolescence. Therefore, sleep disturbance and/or deficit during this period can have detrimental consequences. Many epidemiological and clinical studies have linked early life sleep disturbance with occurrence of later life behavioral and cognitive impairments. Role of oxidative stress and inflammation has been implicated in sleep deprivation-related impairments. This review article presents a detailed description of the current state of the literature on the subject.

Traveling Slow Oscillations During Sleep: A Marker of Brain Connectivity in Childhood

Slow oscillations, a defining characteristic of the nonrapid eye movement sleep electroencephalogram (EEG), proliferate across the scalp in highly reproducible patterns. In adults, the propagation of slow oscillations is a recognized fingerprint of brain connectivity and excitability. In this study, we (1) describe for the first time maturational features of sleep slow oscillation propagation in children (n = 23; 2-13 years) using high-density (hd) EEG and (2) examine associations between sleep slow oscillatory propagation characteristics (ie, distance, traveling speed, cortical involvement) and white matter myelin microstructure as measured with multicomponent Driven Equilibrium Single Pulse Observation of T1 and T2-magnetic resonance imaging (mcDESPOT-MRI). Results showed that with increasing age, slow oscillations propagated across longer distances (average growth of 0.2 cm per year; R(21) = 0.50, p < .05), while traveling speed and cortical involvement (ie, slow oscillation expanse) remained unchanged across childhood. Cortical involvement (R(20) = 0.44) and slow oscillation speed (R(20) = -0.47; both p < .05, corrected for age) were associated with myelin content in the superior longitudinal fascicle, the largest anterior-posterior, intrahemispheric white matter connectivity tract. Furthermore, slow oscillation distance was moderately associated with whole-brain (R(21) = 0.46, p < .05) and interhemispheric myelin content, the latter represented by callosal myelin water fraction (R(21) = 0.54, p < .01, uncorrected). Thus, we demonstrate age-related changes in slow oscillation propagation distance, as well as regional associations between brain activity during sleep and the anatomical connectivity of white matter microstructure. Our findings make an important contribution to knowledge of the brain connectome using a noninvasive and novel analytic approach. These data also have implications for understanding the emergence of neurodevelopmental disorders and the role of sleep in brain maturation trajectories.

Developmental trends of theta-beta interelectrode power correlation during resting state in normal children

The possibility that power-to-power (theta-beta) frequency coupling increases during development was analyzed. Three minutes of spontaneous EEG in an open eyes condition were recorded in a sample of 160 subjects ranging from 6 to 26 years old. Theta (4-7 Hz) and beta band (15-20 Hz) power was calculated in a trial-by-trial basis. Inter-electrode power correlations (IPC) were computed in each subject as the correlation between the power of two frequency bands recorded in two electrodes. An increase in theta-beta IPC with age was obtained. IPCs were higher when theta was seeded in posterior regions than in anterior or central regions. Moreover, the significant correlations between each individual IPC and age were calculated, making it possible to draw IPC versus age correlation maps in order to capture the IPC development topography. An increase was found in significant correlations in the left hemisphere compared to the right hemisphere. There were no differences in the inter-hemispheric versus intra-hemispheric IPC maturation spatial patterns. An increase in power-to-power-frequency coupling in theta-beta occurs during development, suggesting an increase in functional connectivity with age. Frequency coupling between theta and beta rhythms would be one of the mechanisms facilitating integration of long distance functional networks during development.

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.

Large-scale network organization of EEG functional connectivity in newborn infants

The organization of functional brain networks changes across human lifespan. The present study analyzed functional brain networks in healthy full-term infants (N = 139) within 1-6 days from birth by measuring neural synchrony in EEG recordings during quiet sleep. Large-scale phase synchronization was measured in six frequency bands with the Phase Lag Index. Macroscopic network organization characteristics were quantified by constructing unweighted minimum spanning tree graphs. The cortical networks in early infancy were found to be significantly more hierarchical and had a more cost-efficient organization compared with MST of random control networks, more so in the theta and alpha than in other frequency bands. Frontal and parietal sites acted as the main hubs of these networks, the topological characteristics of which were associated with gestation age (GA). This suggests that individual differences in network topology are related to cortical maturation during the prenatal period, when functional networks shift from strictly centralized toward segregated configurations. Hum Brain Mapp 38:4019-4033, 2017. © 2017 Wiley Periodicals, Inc.

Electroencephalogram Coherence Patterns in Autism: An Updated Review

Electrophysiologic studies suggest that autism spectrum disorder is characterized by aberrant anatomic and functional neural circuitry. During normal brain development, pruning and synaptogenesis facilitate ongoing changes in both short- and long-range neural wiring. In developmental disorders such as autism, this process may be perturbed and lead to abnormal neural connectivity. Careful analysis of electrophysiologic connectivity patterns using EEG coherence may provide a way to probe the resulting differences in neurological function between people with and without autism. There is general consensus that electroencephalogram coherence patterns differ between individuals with and without autism spectrum disorders; however, the exact nature of the differences and their clinical significance remain unclear. Here we review recent literature comparing electroencephalogram coherence patterns between patients with autism spectrum disorders or at high risk for autism and their nonautistic or low-risk for autism peers.

Adolescent Alcohol Exposure Persistently Impacts Adult Neurobiology and Behavior

Adolescence is a developmental period when physical and cognitive abilities are optimized, when social skills are consolidated, and when sexuality, adolescent behaviors, and frontal cortical functions mature to adult levels. Adolescents also have unique responses to alcohol compared with adults, being less sensitive to ethanol sedative-motor responses that most likely contribute to binge drinking and blackouts. Population studies find that an early age of drinking onset correlates with increased lifetime risks for the development of alcohol dependence, violence, and injuries. Brain synapses, myelination, and neural circuits mature in adolescence to adult levels in parallel with increased reflection on the consequence of actions and reduced impulsivity and thrill seeking. Alcohol binge drinking could alter human development, but variations in genetics, peer groups, family structure, early life experiences, and the emergence of psychopathology in humans confound studies. As adolescence is common to mammalian species, preclinical models of binge drinking provide insight into the direct impact of alcohol on adolescent development. This review relates human findings to basic science studies, particularly the preclinical studies of the Neurobiology of Adolescent Drinking in Adulthood (NADIA) Consortium. These studies focus on persistent adult changes in neurobiology and behavior following adolescent intermittent ethanol (AIE), a model of underage drinking. NADIA studies and others find that AIE results in the following: increases in adult alcohol drinking, disinhibition, and social anxiety; altered adult synapses, cognition, and sleep; reduced adult neurogenesis, cholinergic, and serotonergic neurons; and increased neuroimmune gene expression and epigenetic modifiers of gene expression. Many of these effects are specific to adolescents and not found in parallel adult studies. AIE can cause a persistence of adolescent-like synaptic physiology, behavior, and sensitivity to alcohol into adulthood. Together, these findings support the hypothesis that adolescent binge drinking leads to long-lasting changes in the adult brain that increase risks of adult psychopathology, particularly for alcohol dependence.

Annual Research Review: Sleep problems in childhood psychiatric disorders--a review of the latest science

BACKGROUND

Hippocrates flagged the value of sleep for good health. Nonetheless, historically, researchers with an interest in developmental psychopathology have largely ignored a possible role for atypical sleep. Recently, however, there has been a surge of interest in this area, perhaps reflecting increased evidence that disturbed or insufficient sleep can result in poor functioning in numerous domains. This review outlines what is known about sleep in the psychiatric diagnoses most relevant to children and for which associations with sleep are beginning to be understood. While based on a comprehensive survey of the literature, the focus of the current review is on the latest science (largely from 2010). There is a description of both concurrent and longitudinal links as well as possible mechanisms underlying associations. Preliminary treatment research is also considered which suggests that treating sleep difficulties may result in improvements in behavioural areas beyond sleep quality.

FINDINGS

To maximise progress in this field, there now needs to be: (a) greater attention to the assessment of sleep in children; (b) sleep research on a wider range of psychiatric disorders; (c) a greater focus on and examination of mechanisms underlying associations; (d) a clearer consideration of developmental questions and (e) large-scale well-designed treatment studies.

CONCLUSIONS

While sleep problems may sometimes be missed by parents and healthcare providers; hence constituting a hidden risk for other psychopathologies - knowing about these difficulties creates unique opportunities. The current excitement in this field from experts in diverse areas including developmental psychology, clinical psychology, genetics and neuropsychology should make these opportunities a reality.

Sleep and Early Cortical Development

Sleep is increasingly recognized as a key process in neurodevelopment. Animal data show that sleep is essential for the maturation of fundamental brain functions, and growing epidemiological findings indicate that children with early sleep disturbance suffer from later cognitive, attentional, and psychosocial problems. Still, major gaps exist in understanding processes underlying links between sleep and neurodevelopment. One challenge is to translate findings from animal research to humans. In this review, we describe parallels and differences in sleep and development of the cortex in humans and animals and discuss emerging questions.

Early adolescent cognitive gains are marked by increased sleep EEG coherence

Although the increases in cognitive capacities of adolescent humans are concurrent with significant cortical restructuring, functional associations between these phenomena are unclear. We examined the association between cortical development, as measured by the sleep EEG, and cognitive performance in a sample of 9/10 year olds followed up 1 to 3 years later. Our cognitive measures included a response inhibition task (Stroop), an executive control task (Trail Making), and a verbal fluency task (FAS). We correlated sleep EEG measures of power and intra-hemispheric coherence at the initial assessment with performance at that assessment. In addition we correlated the rate of change across assessments in sleep EEG measures with the rate of change in performance. We found no correlation between sleep EEG power and performance on cognitive tasks for the initial assessment. In contrast, we found a significant correlation of the rate of change in intra-hemispheric coherence for the sigma band (11 to 16 Hz) with rate of change in performance on the Stroop (r = 0.61; p<0.02) and Trail Making (r =  -0.51; p<0.02) but no association for the FAS. Thus, plastic changes in connectivity (i.e., sleep EEG coherence) were associated with improvement in complex cognitive function.

The maturation of cortical sleep rhythms and networks over early development

OBJECTIVE

Although neuronal activity drives all aspects of cortical development, how human brain rhythms spontaneously mature remains an active area of research. We sought to systematically evaluate the emergence of human brain rhythms and functional cortical networks over early development.

METHODS

We examined cortical rhythms and coupling patterns from birth through adolescence in a large cohort of healthy children (n=384) using scalp electroencephalogram (EEG) in the sleep state.

RESULTS

We found that the emergence of brain rhythms follows a stereotyped sequence over early development. In general, higher frequencies increase in prominence with striking regional specificity throughout development. The coordination of these rhythmic activities across brain regions follows a general pattern of maturation in which broadly distributed networks of low-frequency oscillations increase in density while networks of high frequency oscillations become sparser and more highly clustered.

CONCLUSION

Our results indicate that a predictable program directs the development of key rhythmic components and physiological brain networks over early development.

SIGNIFICANCE

This work expands our knowledge of normal cortical development. The stereotyped neurophysiological processes observed at the level of rhythms and networks may provide a scaffolding to support critical periods of cognitive growth. Furthermore, these conserved patterns could provide a sensitive biomarker for cortical health across development.

Development of Brain EEG Connectivity across Early Childhood: Does Sleep Play a Role?

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.

Brain functional networks in syndromic and non-syndromic autism: a graph theoretical study of EEG connectivity

BACKGROUND

Graph theory has been recently introduced to characterize complex brain networks, making it highly suitable to investigate altered connectivity in neurologic disorders. A current model proposes autism spectrum disorder (ASD) as a developmental disconnection syndrome, supported by converging evidence in both non-syndromic and syndromic ASD. However, the effects of abnormal connectivity on network properties have not been well studied, particularly in syndromic ASD. To close this gap, brain functional networks of electroencephalographic (EEG) connectivity were studied through graph measures in patients with Tuberous Sclerosis Complex (TSC), a disorder with a high prevalence of ASD, as well as in patients with non-syndromic ASD.

METHODS

EEG data were collected from TSC patients with ASD (n = 14) and without ASD (n = 29), from patients with non-syndromic ASD (n = 16), and from controls (n = 46). First, EEG connectivity was characterized by the mean coherence, the ratio of inter- over intra-hemispheric coherence and the ratio of long- over short-range coherence. Next, graph measures of the functional networks were computed and a resilience analysis was conducted. To distinguish effects related to ASD from those related to TSC, a two-way analysis of covariance (ANCOVA) was applied, using age as a covariate.

RESULTS

Analysis of network properties revealed differences specific to TSC and ASD, and these differences were very consistent across subgroups. In TSC, both with and without a concurrent diagnosis of ASD, mean coherence, global efficiency, and clustering coefficient were decreased and the average path length was increased. These findings indicate an altered network topology. In ASD, both with and without a concurrent diagnosis of TSC, decreased long- over short-range coherence and markedly increased network resilience were found.

CONCLUSIONS

The altered network topology in TSC represents a functional correlate of structural abnormalities and may play a role in the pathogenesis of neurological deficits. The increased resilience in ASD may reflect an excessively degenerate network with local overconnection and decreased functional specialization. This joint study of TSC and ASD networks provides a unique window to common neurobiological mechanisms in autism.

Modulation of γ and spindle-range power by slow oscillations in scalp sleep EEG of children

Deep sleep is characterized by slow waves of electrical activity in the cerebral cortex. They represent alternating down states and up states of, respectively, hyperpolarization with accompanying neuronal silence and depolarization during which neuronal firing resumes. The up states give rise to faster oscillations, notably spindles and gamma activity which appear to be of major importance to the role of sleep in brain function and cognition. Unfortunately, while spindles are easily detectable, gamma oscillations are of very small amplitude. No previous sleep study has succeeded in demonstrating modulations of gamma power along the time course of slow waves in human scalp EEG. As a consequence, progress in our understanding of the functional role of gamma modulation during sleep has been limited to animal studies and exceptional human studies, notably those of intracranial recordings in epileptic patients. Because high synaptic density, which peaks some time before puberty depending on the brain region (Huttenlocher and Dabholkar, 1997), generates oscillations of larger amplitude, we considered that the best chance to demonstrate a modulation of gamma power by slow wave phase in regular scalp sleep EEG would be in school-aged children. Sleep EEG was recorded in 30 healthy children (aged 10.7 ± 0.8 years; mean ± s.d.). Time-frequency analysis was applied to evaluate the time course of spectral power along the development of a slow wave. Moreover, we attempted to modify sleep architecture and sleep characteristics through automated acoustic stimulation coupled to the occurrence of slow waves in one subset of the children. Gamma power increased on the rising slope and positive peak of the slow wave. Gamma and spindle activity is strongly suppressed during the negative peak. There were no differences between the groups who received and did not receive acoustic stimulation in the sleep parameters and slow wave-locked time-frequency analysis. Our findings show, for the first time in scalp EEG in humans, that gamma activity is associated with the up-going slope and peak of the slow wave. We propose that studies in children provide a uniquely feasible opportunity to conduct investigations into the role of gamma during sleep.

Mapping the electrophysiological marker of sleep depth reveals skill maturation in children and adolescents

Electroencephalographically (EEG) recorded slow wave activity (SWA, 1-4.5Hz), reflecting the depth of sleep, is suggested to play a crucial role in synaptic plasticity. Mapping of SWA by means of high-density EEG reveals that cortical regions showing signs of maturational changes (structural and behavioral) during childhood and adolescence exhibit more SWA. Moreover, the maturation of specific skills is predicted by the topographical distribution of SWA. Thus, SWA topography may serve as a promising neuroimaging tool with prognostic potential. Finally, our data suggest that deep sleep SWA in humans is involved in cortical development that optimizes performance.

Dissipation of sleep pressure is stable across adolescence

The sleep electroencephalogram (EEG) undergoes many changes during adolescence. We assessed whether sleep homeostasis is altered across adolescent development using two measures: the dissipation of slow-wave activity (SWA, 0.6-4.6Hz) across the night and the rate of build-up of SWA in the first non-rapid eye movement (NREM) sleep episode. Furthermore, we examined the association between homeostatic and circadian measures, by correlating the build-up of SWA in the first non-rapid eye movement (NREM) sleep episode with circadian phase. Finally, we compared the dissipation of SWA in individuals with (PH+) and without (PH-) a parental history of alcohol abuse/dependence. Twenty children (8 PH+) and 25 teens (10 PH+) underwent two consecutive polysomnographic recordings at ages 9/10 and 15/16 years and again 1.5-3 years later. Thirteen young adults (ages 20-23 years; no PH+) were assessed one time. The decay of Process S was modeled for each individual at each assessment using data from both recordings. Four parameters of Process S were derived for EEG derivation C3/A2: time constant of the decay, lower asymptote (LA), the level of S at sleep onset (S(SO)), and S(SO) minus LA. We found no change in these parameters between assessments for the children and teen cohorts. Between-subject analysis of the follow-up assessment for children (ages 11-13 years) and the initial assessment for teens (ages 15/16 years) showed no difference in these parameters, nor did follow-up assessment of teens (ages 17-19 years) compared to the single assessment of young adults (ages 20-23 years). Similarly, we observed no developmental changes in the rate of the build-up of SWA in the first NREM sleep episode for our within- and between-subject analyses, or a correlation between this measure and circadian phase for either cohort. With regard to parental alcohol history, we found no difference in the dissipation of sleep pressure between PH+ and PH- children and teens. These results indicate that the dissipation of sleep pressure does not change across adolescent development, is not correlated with circadian phase, and does not differ between PH+ and PH- children and teens.

Adolescence and parental history of alcoholism: insights from the sleep EEG

BACKGROUND

Disrupted sleep is a common complaint of individuals with alcohol use disorder and in abstinent alcoholics. Furthermore, among recovering alcoholics, poor sleep predicts relapse to drinking. Whether disrupted sleep in these populations results from prolonged alcohol use or precedes the onset of drinking is not known. The aim of this study was to examine the sleep electroencephalogram (EEG) in alcohol-naïve, parental history positive (PH+), and negative (PH-) boys and girls.

METHODS

All-night sleep EEG recordings in 2 longitudinal cohorts (child and teen) followed at 1.5 to 3 year intervals were analyzed. The child and teen participants were 9/10 and 15/16 years old at the initial assessment, respectively. Parental history status was classified by Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria applied to structured interviews (DIS-IV) resulting in 14 PH- and 10 PH+ children and 14 PH- and 10 PH+ teens. Sleep data were visually scored in 30-second epochs using standard criteria. Power spectra were calculated for EEG derivations C3/A2, C4/A1, O2/A1, O1/A2 for nonrapid eye movement (NREM) and rapid eye movement (REM) sleep.

RESULTS

We found no difference between PH+ and PH- individuals in either cohort for any visually scored sleep stage variable. Spectral power declined in both cohorts across assessments for NREM and REM sleep in all derivations and across frequencies independent of parental history status. With regard to parental history, NREM sleep EEG power was lower for the delta band in PH+ teens at both assessments for the central derivations. Furthermore, power in the sigma band for the right occipital derivation in both NREM and REM sleep was lower in PH+ children only at the initial assessment.

CONCLUSIONS

We found no gross signs of sleep disruption as a function of parental history. Modest differences in spectral EEG power between PH+ and PH- children and teens indicate that a marker of parental alcohol history may be detectable in teens at risk for problem drinking.