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

Disruption of functional network development in children with prenatal Zika virus exposure revealed by resting-state EEG

Children born to mothers infected by Zika virus (ZIKV) during pregnancy are at increased risk of adverse neurodevelopmental outcomes including microcephaly, epilepsy, and neurocognitive deficits, collectively known as Congenital Zika Virus Syndrome. To study the impact of ZIKV on infant brain development, we collected resting-state electroencephalography (EEG) recordings from 28 normocephalic ZIKV-exposed children and 16 socio-demographically similar but unexposed children at 23-27 months of age. We assessed group differences in frequency band power and brain synchrony, as well as the relationship between these metrics and age. A significant difference (p < 0.05, Bonferroni corrected) in Inter-Site Phase Coherence was observed: median Pearson correlation coefficients were 0.15 in unexposed children and 0.07 in ZIKV-exposed children. Results showed that functional brain networks in the unexposed group were developing rapidly, in part by strengthening distal high-frequency and weakening proximal lower frequency connectivity, presumably reflecting normal synaptic growth, myelination and pruning. These maturation patterns were attenuated in the ZIKV-exposed group, suggesting that ZIKV exposure may contribute to neurodevelopmental vulnerabilities that can be detected and quantified by resting-state 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.

The association between infant sleep, cognitive, and psychomotor development: a systematic review

STUDY OBJECTIVES

To synthesize findings of original articles examining the association between sleep-wake patterns of typically developing infants aged 0 to 18 months and cognitive and psychomotor development.

METHODS

A systematic search strategy was used to identify articles assessing the association between infant sleep (0 to 18 months) and cognitive/psychomotor development (Medline, PsycINFO, and SCOPUS). Of 7136 articles screened, 22 articles met inclusion criteria, and the results were subsequently synthesized. A quality assessment was conducted, and studies were categorized as "poor," "fair," or "good."

RESULTS

Out of 22 studies, 2 found exclusively significant associations (SAs) between infant sleep and cognitive/psychomotor development, 2 found no SAs and 17 found mixed results (MRs). Studies with exclusively significant results used a single sleep variable and single timepoint designs. Studies finding MRs or no SAs used multiple sleep, developmental variables, or multi-timepoint designs. Eight out of 10 studies and 7 out of 8 studies investigating nocturnal and total sleep duration, respectively, found no SA with developmental outcomes. While 63% of studies were rated as having good methodological quality, all studies but one had an estimated power of less than 0.80.

CONCLUSIONS

Findings of this review do not support conclusive associations between sleep-wake patterns in infancy and cognitive/psychomotor development. This conclusion contrasts with the literature in older populations, questioning if the association between sleep and development is of a different nature in infancy, potentially because of brain maturation. More studies including larger samples will be needed to clarify the presence or absence of such an association.

Sleep-slow oscillation-spindle coupling precedes spindle-ripple coupling during development

STUDY OBJECTIVES

Sleep supports systems memory consolidation through the precise temporal coordination of specific oscillatory events during slow-wave sleep, i.e. the neocortical slow oscillations (SOs), thalamic spindles, and hippocampal ripples. Beneficial effects of sleep on memory are also observed in infants, although the contributing regions, especially hippocampus and frontal cortex, are immature. Here, we examined in rats the development of these oscillatory events and their coupling during early life.

METHODS

EEG and hippocampal local field potentials were recorded during sleep in male rats at postnatal days (PD)26 and 32, roughly corresponding to early (1-2 years) and late (9-10 years) human childhood, and in a group of adult rats (14-18 weeks, corresponding to ~22-29 years in humans).

RESULTS

SO and spindle amplitudes generally increased from PD26 to PD32. In parallel, frontocortical EEG spindles increased in density and frequency, while changes in hippocampal ripples remained nonsignificant. The proportion of SOs co-occurring with spindles also increased from PD26 to PD32. Whereas parietal cortical spindles were phase-locked to the depolarizing SO-upstate already at PD26, over frontal cortex SO-spindle phase-locking emerged not until PD32. Co-occurrence of hippocampal ripples with spindles was higher during childhood than in adult rats, but significant phase-locking of ripples to the excitable spindle troughs was observed only in adult rats.

CONCLUSIONS

Results indicate a protracted development of synchronized thalamocortical processing specifically in frontocortical networks (i.e. frontal SO-spindle coupling). However, synchronization within thalamocortical networks generally precedes synchronization of thalamocortical with hippocampal processing as reflected by the delayed occurrence of spindle-ripple phase-coupling.

Interhemispheric coherence of EEG rhythms in children: Maturation and differentiation in corpus callosum dysgenesis

OBJECTIVES

To evaluate the evolution of interhemispheric coherences (ICo) in background and spindle frequency bands during childhood and use it to identify individuals with corpus callosum dysgenesis (CCd).

METHODS

A monocentric cohort of children aged from 0.25 to 15 years old, consisting of 13 children with CCd and 164 without, was analyzed. The ICo of background activity (ICOBckgrdA), sleep spindles (ICOspindles), and their sum (sICO) were calculated. The impact of age, gender, and CC status on the ICo was evaluated, and the sICO was used to discriminate children with or without CCd.

RESULTS

ICOBckgrdA, ICOspindles and sICO increased significantly with age without any effect of gender (p < 10-4), in both groups. The regression equations of the different ICo were stronger, with adjusted R2 values of 0.54, 0.35, and 0.57, respectively. The ICo was lower in children with CCd compared to those without CCd (p < 10-4 for all comparisons). The area under the precision recall curves for predicting CCd using sICO was 0.992 with 98.9 % sensitivity and 87.5 % specificity.

DISCUSSION

ICo of spindles and background activity evolve in parallel to brain maturation and depends on the integrity of the corpus callosum. sICO could be an effective diagnostic biomarker for screening children with interhemispheric dysfunction.

Nocturnal sleep duration trajectories in early childhood and school performance at age 10 years

Sleep plays a fundamental role in brain development and resultant functions. The aim was to verify whether nocturnal sleep duration during early childhood has long-term associations with academic achievement at age 10 years. The present study is part of the Quebec Longitudinal Study of Child Development, a representative cohort of infants born in 1997-1998 in the province of Quebec, Canada. Children with known neurological conditions were excluded from this cohort. Four trajectories of parent-reported nocturnal sleep duration at ages 2.5, 3, 4, 5 and 6 years were determined using a SAS procedure named PROC TRAJ. Sleep duration at age 10 years was also reported. Teachers provided data on academic performance when the children were age 10 years. These data were available for 910 children (430 boys, 480 girls; 96.6% Caucasians). Univariate and multivariable logistic regressions were performed using SPSS. Children who slept less than 8 hr per night at 2.5 years but normalized later on (Traj1) had three-five times the odds of having grades below the class average in reading, writing, mathematics and science compared with children who slept sufficiently (Traj3-4: 10-11 hr per night). Children who slept about 9 hr per night throughout childhood (Traj2) had two-three times the odds of being below the class average in mathematics and science. Sleep duration at age 10 years was not correlated with the academic performance. These results point to the presence of a very important early period during which sufficient sleep is needed to fine-tune the functions necessary for academic achievement later on.

Pediatric sleep: current knowledge, gaps, and opportunities for the future

This White Paper addresses the current gaps in knowledge, as well as opportunities for future studies in pediatric sleep. The Sleep Research Society's Pipeline Development Committee assembled a panel of experts tasked to provide information to those interested in learning more about the field of pediatric sleep, including trainees. We cover the scope of pediatric sleep, including epidemiological studies and the development of sleep and circadian rhythms in early childhood and adolescence. Additionally, we discuss current knowledge of insufficient sleep and circadian disruption, addressing the neuropsychological impact (affective functioning) and cardiometabolic consequences. A significant portion of this White Paper explores pediatric sleep disorders (including circadian rhythm disorders, insomnia, restless leg and periodic limb movement disorder, narcolepsy, and sleep apnea), as well as sleep and neurodevelopment disorders (e.g. autism and attention deficit hyperactivity disorder). Finally, we end with a discussion on sleep and public health policy. Although we have made strides in our knowledge of pediatric sleep, it is imperative that we address the gaps to the best of our knowledge and the pitfalls of our methodologies. For example, more work needs to be done to assess pediatric sleep using objective methodologies (i.e. actigraphy and polysomnography), to explore sleep disparities, to improve accessibility to evidence-based treatments, and to identify potential risks and protective markers of disorders in children. Expanding trainee exposure to pediatric sleep and elucidating future directions for study will significantly improve the future of the field.

Origin, synchronization, and propagation of sleep slow waves in children

STUDY OBJECTIVES

Sleep slow wave activity, as measured using EEG delta power (<4 Hz), undergoes significant changes throughout development, mirroring changes in brain function and anatomy. Yet, age-dependent variations in the characteristics of individual slow waves have not been thoroughly investigated. Here we aimed at characterizing individual slow wave properties such as origin, synchronization, and cortical propagation at the transition between childhood and adulthood.

METHODS

We analyzed overnight high-density (256 electrodes) EEG recordings of healthy typically developing children (N=21, 10.3±1.5 years old) and young healthy adults (N=18, 31.1±4.4 years old). All recordings were preprocessed to reduce artifacts, and NREM slow waves were detected and characterized using validated algorithms. The threshold for statistical significance was set at p=0.05.

RESULTS

The slow waves of children were larger and steeper, but less widespread than those of adults. Moreover, they tended to mainly originate from and spread over more posterior brain areas. Relative to those of adults, the slow waves of children also displayed a tendency to more strongly involve and originate from the right than the left hemisphere. The separate analysis of slow waves characterized by high and low synchronization efficiency showed that these waves undergo partially distinct maturation patterns, consistent with their possible dependence on different generation and synchronization mechanisms.

CONCLUSIONS

Changes in slow wave origin, synchronization, and propagation at the transition between childhood and adulthood are consistent with known modifications in cortico-cortical and subcortico-cortical brain connectivity. In this light, changes in slow-wave properties may provide a valuable yardstick to assess, track, and interpret physiological and pathological development.

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.

The Associations between 24-Hour Movement Behaviours and Quality of Life in Preschoolers: A Compositional Analysis of Cross-Sectional Data from 2018-2021

Studies show that the quality of life (QoL) of preschoolers is closely related to physical activity (PA), sedentary behaviour (SB), and sleep (SL). Yet many researchers looked at these 24-h movement behaviours as behaviours that are independent of one another when examining the association of QoL with these behaviours. The main purpose of the present study was to describe the temporal trends in PA, SB, and SL in preschoolers and the concomitant association with QoL of children. Annual cross-sectional data on QoL and 24-h movement behaviours of 8045 Singaporean preschoolers were collected from 2018 to 2021. Compositional analysis, linear regression, and isotemporal replacement approaches were used to examine changes in PA, SB, and SL from 2018-2021 and how these changes were associated with QoL. Temporal trends in movement behaviours showed that PA and SL decreased after 2020. During 2018-2021, the association of PA and QoL in preschoolers was characterised by a 'U' curve (βPA-2018 = 3.06, p < 0.001; βPA-2019 = 1.43, p < 0.05; βPA-2020 = -0.43, p > 0.05; βPA-2021 = 2.82, p < 0.001), while SL and QoL were characterised by an inverted 'U' curve (βSL-2018 = -2.39, p < 0.001; βSL-2019 = -0.27, p > 0.05; βSL-2020 = 2.00, p < 0.01; βSL-2021 = -0.21, p > 0.05). SB was significantly and negatively associated with QoL after 2020, with 2020 identified as the inflection point for the change in SB (βSB-2018 = 0.67, p > 0.05; βSB-2019 = -1.16, p > 0.05; βSB-2020 = -1.56, p < 0.01; βSB-2021 = -2.61, p < 0.01). Using a time re-allocation technique to treat the 2021 data, reallocating time from SB to PA or to SL predicted improvements in QoL of preschoolers (Pall < 0.05). The study provided useful information on the temporal trends in PA, SB, SL, and QoL of preschoolers over four years. Additionally, these data provided insights into how changes in QoL are predicted by changes in duration in the 24-h movement behaviours.

How Are the Sleep Problems of Children in the US Foster Care System Addressed?

OBJECTIVE

Evidence of poor sleep health among children in foster care continues to mount, but information about whether and how sleep problems are addressed is unavailable. The goal of this study was to begin to fill these significant knowledge gaps.

METHODS

Four hundred eighty-five foster caregivers from across the United States completed a survey focused on the sleep health of one child, 4 to 11 years ( M = 6.4; SD = 2.2) currently in their care. Caregivers provided quantitative and qualitative responses to questions regarding training, information, and services received in relation to their child's sleep. Caregivers also reported on the factors and strategies they perceived as most important for helping children in their care sleep well.

RESULTS

Only 13% of caregivers reported receiving any information/education about sleep from agencies or case workers, whereas 55% had sought help from a health provider related to their child's sleep. Nearly half of all caregivers (46%) reported giving their child melatonin. Caregivers reported that a bedtime routine/consistency, reassurance of safety/love, and a calming environment were most important for helping their child sleep well. A recurrent theme in qualitative responses was a need to mitigate child fear/anxiety at night.

CONCLUSION

Children in foster care face a range of risk factors that increase the likelihood of poor/insufficient sleep, but these findings suggest this critical aspect of health requires greater clinical and research attention. As these data were collected during the initial months of the COVID-19 pandemic, replication studies are necessary.

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.

Associations Between Preschool Sleep Problems and Observed Dimensions of Elementary Classroom Engagement

Sleep has clear importance for academic success. However, most research in this area has focused on older children and adolescents and has used narrow measures of academic achievement, overlooking the importance of early sleep problems in shaping children's classroom behaviors that support academic success. Using a community sample (N = 276, 50% female), the current study examined associations between parent-reported preschool sleep problems (M _age = 3.84, SD = 0.83) and three dimensions of classroom engagement coded during live classroom observations in the first grade (M _age = 6.72, SD = 0.34). The moderating role of family socioeconomic status (SES) was also considered. A multivariate multilevel model found that more preschool sleep problems were associated with less focused engagement (defined as involvement in academic tasks, such as writing or asking questions), but more competing responses (defined as inappropriate or distracting behaviors). Preschool sleep problems were not associated with task management (defined as preparation for academic tasks, such as locating classroom materials). Although family SES did not moderate any of these associations, higher income-to-needs ratios in preschool were associated with more focused engagement and fewer competing responses. Findings highlight the role of early sleep problems in classroom behaviors that facilitate academic success. Targeting sleep problems prior to the school transition may serve as a useful approach to optimizing learning conditions during this key developmental period.

Bedsharing in Early Childhood: Frequency, Partner Characteristics, and Relations to Sleep

Bedsharing (sharing a bed with others during sleep) in early childhood (3-5 years old) is common across Western and non-Western societies alike. Though prior work indicates that bedsharing may relate to impairments in child sleep quantity or quality, the majority of studies conducted in young children are limited to parent-child bedsharing and rely almost exclusively on caregiver reports to measure child sleep. Here, the authors endeavored to gain further insights into the diversity of bedsharing practices among children in the United States, including how different bedsharing partners (caregivers, siblings) might impact actigraphy-derived measures of children's sleep. Using a sample of 631 children ages 2:9 to 5:11 years, we found that over 36% of children bedshared in some form overnight, with approximately 22% bedsharing habitually. In a subset of children for whom actigraphy measures were collected (n = 337), children who bedshared habitually (n = 80) had significantly shorter overnight sleep, later sleep and wake times, and longer naps than solitary sleepers (n = 257), even when controlling for socioeconomic status. Despite supplementing their shorter overnight sleep with longer naps, habitually bedsharing children had significantly shorter 24-hr sleep time than did solitary sleepers, though differences in sleep efficiency were nonsignificant for all sleep periods. Additionally, sleep efficiency, onset latency, and duration did not differ between children who habitually bedshared with siblings versus those who habitually bedshared with parents. The present results add to prior work examining family contextual correlates of sleep differences in early childhood and provide a more objective account of relations between bedsharing and child sleep.

Sleep and human cognitive development

Emerging studies across learning domains have shed light on mechanisms underlying sleep's benefits during numerous developmental periods. In this conceptual review, we survey recent studies of sleep and cognition across infancy, childhood, and adolescence. By summarizing recent findings and integrating across studies with disparate approaches, we provide a novel understanding of sleep's role in human cognitive function. Collectively, these studies point to an interrelation between brain development, sleep, and cognition. Moreover, we point to gaps in our understanding, which inform the agenda for future research in developmental and sleep science.

Critical aspects of neurodevelopment

Organisms have the unique ability to adapt to their environment by making use of external inputs. In the process, the brain is shaped by experiences that go hand-in-hand with optimisation of neural circuits. As such, there exists a time window for the development of different brain regions, each unique for a particular sensory modality, wherein the propensity of forming strong, irreversible connections are high, referred to as a critical period of development. Over the years, this domain of neurodevelopmental research has garnered considerable attention from many scientists, primarily because of the intensive activity-dependent nature of development. This review discusses the cellular, molecular, and neurophysiological bases of critical periods of different sensory modalities, and the disorders associated in cases the regulators of development are dysfunctional. Eventually, the neurobiological bases of the behavioural abnormalities related to developmental pathologies are discussed. A more in-depth insight into the development of the brain during the critical period of plasticity will eventually aid in developing potential therapeutics for several neurodevelopmental disorders that are categorised under critical period disorders.

Mismatched response predicts behavioral speech discrimination outcomes in infants with hearing loss and normal hearing

Children with hearing loss (HL) remain at risk for poorer language abilities than normal hearing (NH) children despite targeted interventions; reasons for these differences remain unclear. In NH children, research suggests speech discrimination is related to language outcomes, yet we know little about it in children with HL under the age of 2 years. We utilized a vowel contrast, /a-i/, and a consonant-vowel contrast, /ba-da/, to examine speech discrimination in 47 NH infants and 40 infants with HL. At Mean age =3 months, EEG recorded from 11 scalp electrodes was used to compute the time-frequency mismatched response (TF-MMR_SE ) to the contrasts; at Mean age =9 months, behavioral discrimination was assessed using a head turn task. A machine learning (ML) classifier was used to predict behavioral discrimination when given an arbitrary TF-MMR_SE as input, achieving accuracies of 73% for exact classification and 92% for classification within a distance of one class. Linear fits revealed a robust relationship regardless of hearing status or speech contrast. TF-MMR_SE responses in the delta (1-3.5 Hz), theta (3.5-8 Hz), and alpha (8-12 Hz) bands explained the most variance in behavioral task performance. Our findings demonstrate the feasibility of using TF-MMR_SE to predict later behavioral speech discrimination.

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.

The Maximum Eigenvalue of the Brain Functional Network Adjacency Matrix: Meaning and Application in Mental Fatigue Evaluation

The maximum eigenvalue of the adjacency matrix (AM) has been supposed to contain rich information about the corresponding network. An experimental study focused on revealing the meaning and application of the maximum eigenvalue is missing. To this end, AM was constructed using mutual information (MI) to determine the functional connectivity with electroencephalogram (EEG) data recorded with a mental fatigue model, and then was converted into both binary and weighted brain functional network (BFN) and corresponding random networks (RNs). Both maximum eigenvalue and corresponding network characters in BFNs and RNs were considered to explore the changes during the formation of mental fatigue. The results indicated that large maximum eigenvalue means more edges in the corresponding network, along with a high degree and a short characteristic path length both in weighted and binary BFNs. Interestingly, the maximum eigenvalue of AM was always a little larger than that of the corresponding random matrix (RM), and had an obvious linearity with the sum of the AM elements, indicating that the maximum eigenvalue can be able to distinguish the network structures which have the same mean degree. What is more, the maximum eigenvalue, which increased with the deepening of mental fatigue, can become a good indicator for mental fatigue estimation.

Sex Difference in EEG Functional Connectivity during Sleep Stages and Resting Wake State Based on Weighted Phase Lag Index

Men and women were reported to be different in brain structure and sleep patterns. Here we analyzed the region, sleep stage and frequency band-specific EEG synchronization intensity of whole night sleep recording of 14 male and 14 age-matched female subjects by calculating weighted phase lag indexes. Moreover, resting wakeful stage EEG was also analyzed and compared. The synchronization intensities showed significant gender differences in all stages and bands: higher in women in non-rapid eye movement (NREM) sleep, and higher in men in α and β bands in wakeful stage and rapid eye movement (REM) sleep. However, Except for α band, the similar changing trends in characteristics of EEG synchronization during different stages were found in both male and female subjects. These results suggest that there may be some differences in the mechanisms of sleep regulation between men and women. Moreover, the synchronous intensity of different sleep stages in different frequency bands of male and female groups was not consistent with the influence of age, which may be related to the gender differences in aging patterns.

Sleep-behaviour relationship in children with autism spectrum disorder: methodological pitfalls and insights from cognition and sensory processing

Sleep disturbances are frequent and varied in autism spectrum disorder (ASD). Growing evidence suggests that sleep problems in children with ASD are driven by their clinical characteristics and psychiatric comorbidities. Therefore, the wide range of reported sleep disturbances reflects the marked heterogeneity of clinical pictures in ASD. Whether sleep disturbances and their various forms may, in turn, account for at least part of the phenotypical variability of ASD is a crucial question discussed in this review. We first outline studies both validating and challenging a bidirectional theoretical framework for sleep disorders in children with ASD. We then propose to extend this model by including cognition and sensory processing as key factors in the vicious circle linking sleep disorders and autistic symptoms. WHAT THIS PAPER ADDS: There is a bidirectional interplay between autism symptoms and sleep disturbances. Sleep influence on daytime cognitive and sensory skills should be further investigated.

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.

A Mixed Lipid Emulsion Containing Fish Oil and Its Effect on Electrophysiological Brain Maturation in Infants of Extremely Low Birth Weight: A Secondary Analysis of a Randomized Clinical Trial

OBJECTIVE

To assess whether parenteral nutrition for infants of extremely low birth weight using a mixed lipid emulsion that contains fish oil influences electrophysiological brain maturation.

STUDY DESIGN

The study is a prespecified secondary outcome analysis of a randomized controlled trial of 230 infants of extremely low birth weight receiving a mixed (soybean oil, medium-chain triglycerides, olive oil, and fish oil; intervention) or a soybean oil-based lipid emulsion (control). The study was conducted at a single-level IV neonatal care unit (Medical University Vienna; June 2012 to October 2015). Electrophysiological brain maturation (background activity, sleep-wake cycling, and brain maturational scores) was assessed biweekly by amplitude-integrated electroencephalography (birth to discharge).

RESULTS

A total of 317 amplitude-integrated electroencephalography measurements (intervention: n = 165; control: n = 152) from 121 (intervention: n = 63; control: n = 58) of 230 infants of the core study were available for analysis. Demographic characteristics were not significantly different. By 28 weeks of postmenstrual age, infants receiving the intervention displayed significantly greater percentages of continuous background activity. Total maturational scores and individual scores for continuity, cycling, and bandwidth were significantly greater. Maximum maturational scores were reached 2 weeks earlier in the intervention group (36.4 weeks, 35.4-37.5) compared with the control group (38.4 weeks, 37.1-42.4) (median, IQR; P < .001).

CONCLUSIONS

Using a mixed parenteral lipid emulsion that contains fish oil, we found that electrophysiological brain maturation was accelerated in infants who were preterm.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT01585935.

Functional brain connectivity in a rodent seizure model of autistic-like behavior

OBJECTIVE

There is increasing evidence that Autism Spectrum Disorder (ASD) is a disorder of functional connectivity with both human and rodent studies demonstrating alterations in connectivity. Here, we hypothesized that early-life seizures (ELS) in rats would interrupt normal brain connectivity and result in autistic-like behavior (ALB).

METHODS

Following 50 seizures, adult rats were tested in the social interaction and social novelty tests and then underwent qualitative and quantitative intracranial electroencephalography (EEG) monitoring in the medial prefrontal cortex (PFC) and the hippocampal subfields, CA3 and CA1.

RESULTS

Rats with ELS showed deficits in social interaction and novelty, and compared with control, rats had marked increases in coherence within the hippocampus (CA3-CA1) and between the hippocampus and PFC during the awake and sleep states indicating hyperconnectivity. In addition, sleep spindle density was significantly reduced in rats with ELS. There were no differences in voltage correlations and power spectral densities between the ELS and control rats in any bandwidths.

CONCLUSION

Taken together, these findings indicate that ELS can result in ALB and alter functional connectivity as measured by coherence and sleep spindle density. These findings implicate altered connectivity as a robust neural signature for ALB following ELS.

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.

Early Life Sleep Deprivation: Role of Oxido-Inflammatory Processes

The adverse consequences of early-life sleep deprivation on mental health are well recognized, yet many aspects remain unknown, therefore, animal studies can offer useful insights. Male Sprague-Dawley rats at postnatal day (PND) 19 were subjected to sleep deprivation (SD) for 14 days (6-8 hours/day). Control (CON) rats were gently handled. Behavior tests were done on PND33, PND60 and PND90. SD rats exhibited anxiety-like behavior at PND33 and PND60, when compared to CON rats. Depression-like behavior was observed at PND90. Evaluation of oxidative stress and inflammatory markers revealed interesting results. Plasma 8-isoprostane and antioxidant defense enzymes; hemeoxygenase-1, superoxide dismutase, glutathione peroxidase in the prefrontal cortex (PFC), were upregulated in SD rats at PND33 but not at PND90. PFC interleukin-6 protein expression was elevated at PND33 and PND90. PFC mitogen activated protein kinase phosphatase-1 (MKP-1) and p-38 protein expression were upregulated at PND90. PFC expression of glutamate receptor subunits, post synaptic density protein (PSD-95), calcium/calmodulin-dependent protein kinase (CaMKII), and extracellular signal-regulated kinase (ERK_1/2), were significantly reduced in SD rats at PND33 and PND90. PFC brain derived neurotrophic factor (BDNF) and cAMP response element binding protein (CREB) were reduced in SD rats at PND90. Our postulation is that SD by increasing PFC oxido-inflammation, negatively affects glutamate receptor subunits and PSD95 expression, which disrupts synapse formation and maturation, potentially causing anxiety-like behavior at PND33. Oxido-inflammation further results in MKP-1 and CaMKII-mediated blockade of ERK_1/2 activation, which inhibits CREB dependent BDNF expression. This most likely disrupts neuronal circuit development, leading to depression-like behavior at PND90.

REM sleep in naps differentially relates to memory consolidation in typical preschoolers and children with Down syndrome

Sleep is recognized as a physiological state associated with learning, with studies showing that knowledge acquisition improves with naps. Little work has examined sleep-dependent learning in people with developmental disorders, for whom sleep quality is often impaired. We examined the effect of natural, in-home naps on word learning in typical young children and children with Down syndrome (DS). Despite similar immediate memory retention, naps benefitted memory performance in typical children but hindered performance in children with DS, who retained less when tested after a nap, but were more accurate after a wake interval. These effects of napping persisted 24 h later in both groups, even after an intervening overnight period of sleep. During naps in typical children, memory retention for object-label associations correlated positively with percent of time in rapid eye movement (REM) sleep. However, in children with DS, a population with reduced REM, learning was impaired, but only after the nap. This finding shows that a nap can increase memory loss in a subpopulation, highlighting that naps are not universally beneficial. Further, in healthy preschooler's naps, processes in REM sleep may benefit learning.

Sleep spindles are altered in early- but not late-onset nightmare recallers

Nightmares are a common sleep disorder, defined as highly disturbing mentation which usually awakens the individual from rapid eye movement (REM) sleep. While nightmares are mainly a REM sleep phenomenon, Picard-Deland et al., (2017) recently showed an association between nightmare recall and sleep spindles, which are a non-rapid eye movement (NREM) oscillatory feature. Their results pointed to fewer slow spindles and a higher oscillatory frequency for fast spindles among frequent nightmare recallers compared with controls. To test the suggestion that nightmares stem from changes to emotional neural circuits arising in early childhood (Nielsen, 2017), including early changes in sleep spindles (Scholle et al., 2007), we investigated if the spindle features of early-onset nightmare recallers (ie, recalling nightmares since childhood) (N = 22), differed from those of late-onset nightmare recallers (ie, since adolescence or adulthood) (N = 11), or from those of controls (N = 23). A retrospective analysis of the sleep spindles of 56 participants who had undergone a polysomnographically-recorded morning nap revealed that Early starters uniquely exhibited lower slow spindle densities in five of six derivations (all p < 0.045) and higher fast spindle frequencies in all six derivations (all p < 0.015). These results add precision to previously reported findings for Nightmare recallers: spindle differences are shown to hold only for Early starters. The lifelong occurrence of nightmares may be closely tied to disruptions in the normal development of spindle generation processes occurring early in development.

Evaluation of an automated pipeline for large-scale EEG spectral analysis: the National Sleep Research Resource

STUDY OBJECTIVES

We present an automated sleep electroencephalogram (EEG) spectral analysis pipeline that includes an automated artifact detection step, and we test the hypothesis that spectral power density estimates computed with this pipeline are comparable to those computed with a commercial method preceded by visual artifact detection by a sleep expert (standard approach).

METHODS

EEG data were analyzed from the C3-A2 lead in a sample of polysomnograms from 161 older women participants in a community-based cohort study. We calculated the sensitivity, specificity, accuracy, and Cohen's kappa measures from epoch-by-epoch comparisons of automated to visual-based artifact detection results; then we computed the average EEG spectral power densities in six commonly used EEG frequency bands and compared results from the two methods using correlation analysis and Bland-Altman plots.

RESULTS

Assessment of automated artifact detection showed high specificity [96.8%-99.4% in non-rapid eye movement (NREM), 96.9%-99.1% in rapid eye movement (REM) sleep] but low sensitivity (26.7%-38.1% in NREM, 9.1-27.4% in REM sleep). However, large artifacts (total power > 99th percentile) were removed with sensitivity up to 87.7% in NREM and 90.9% in REM, with specificities of 96.9% and 96.6%, respectively. Mean power densities computed with the two approaches for all EEG frequency bands showed very high correlation (≥0.99). The automated pipeline allowed for a 100-fold reduction in analysis time with regard to the standard approach.

CONCLUSION

Despite low sensitivity for artifact rejection, the automated pipeline generated results comparable to those obtained with a standard method that included manual artifact detection. Automated pipelines can enable practical analyses of recordings from thousands of individuals, allowing for use in genetics and epidemiological research requiring large samples.

Feature Extraction with GMDH-Type Neural Networks for EEG-Based Person Identification

The brain activity observed on EEG electrodes is influenced by volume conduction and functional connectivity of a person performing a task. When the task is a biometric test the EEG signals represent the unique “brain print”, which is defined by the functional connectivity that is represented by the interactions between electrodes, whilst the conduction components cause trivial correlations. Orthogonalization using autoregressive modeling minimizes the conduction components, and then the residuals are related to features correlated with the functional connectivity. However, the orthogonalization can be unreliable for high-dimensional EEG data. We have found that the dimensionality can be significantly reduced if the baselines required for estimating the residuals can be modeled by using relevant electrodes. In our approach, the required models are learnt by a Group Method of Data Handling (GMDH) algorithm which we have made capable of discovering reliable models from multidimensional EEG data. In our experiments on the EEG-MMI benchmark data which include 109 participants, the proposed method has correctly identified all the subjects and provided a statistically significant ([Formula: see text]) improvement of the identification accuracy. The experiments have shown that the proposed GMDH method can learn new features from multi-electrode EEG data, which are capable to improve the accuracy of biometric identification.

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.

The relationship between mismatch response and the acoustic change complex in normal hearing infants

OBJECTIVE

To examine the utility of the mismatch response (MMR) and acoustic change complex (ACC) for assessing speech discrimination in infants.

METHODS

Continuous EEG was recorded during sleep from 48 (24 male, 20 female) normally hearing aged 1.77 to -4.57 months in response to two auditory discrimination tasks. ACC was recorded in response to a three-vowel sequence (/i/-/a/-/i/). MMR was recorded in response to a standard vowel, /a/, (probability 85%), and to a deviant vowel, /i/, (probability of 15%). A priori comparisons included: age, sex, and sleep state. These were conducted separately for each of the three bandpass filter settings were compared (1-18, 1-30, and 1-40 Hz).

RESULTS

A priori tests revealed no differences in MMR or ACC for age, sex, or sleep state for any of the three filter settings. ACC and MMR responses were prominently observed in all 44 sleeping infants (data from four infants were excluded). Significant differences observed for ACC were to the onset and offset of stimuli. However, neither group nor individual differences were observed to changes in speech stimuli in the ACC. MMR revealed two prominent peaks occurring at the stimulus onset and at the stimulus offset. Permutation t-tests revealed significant differences between the standard and deviant stimuli for both the onset and offset MMR peaks (p < 0.01). The 1-18 Hz filter setting revealed significant differences for all participants in the MMR paradigm.

CONCLUSION

Both ACC and MMR responses were observed to auditory stimulation suggesting that infants perceive and process speech information even during sleep. Significant differences between the standard and deviant responses were observed in the MMR, but not ACC paradigm. These findings suggest that the MMR is sensitive to detecting auditory/speech discrimination processing.

SIGNIFICANCE

This paper identified that MMR can be used to identify discrimination in normal hearing infants. This suggests that MMR has potential for use in infants with hearing loss to validate hearing aid fittings.

Historical neighborhood poverty trajectories and child sleep

OBJECTIVES

To determine whether historical neighborhood poverty measures are associated with mothers' reports of their children's sleep duration and to compare results from historical neighborhood poverty measures to contemporaneous measures of neighborhood poverty.

DESIGN

The Geographic Research on Wellbeing (GROW) study is a follow-up survey of mothers who gave birth between 2003 and 2007. GROW mothers assessed their own and their children's health and health behaviors 5-10 years later (2012-2013).

SETTING

Urban Californian counties.

PARTICIPANTS

GROW respondents.

MEASUREMENTS

We categorized children's sleep as adequate or inadequate using clinical age-specific guidelines and based on mothers' reports of their child's sleep duration. We conducted a latent class analysis to identify historical poverty classes for all California census tracts using data from 1970 to 2005-2009, and we categorized current neighborhood poverty based on data from 2005 to 2009 only. We then assigned children to different neighborhood exposure classes based on their neighborhood of residence at birth and follow-up.

RESULTS

Logistic models indicated that net of controls for demographics, child behavior and health characteristics, mother characteristics, and household socioeconomic status, children who grew up in historically low (OR: 0.64, 95% confidence interval=0.45-0.92) or historically moderate poverty classes (OR: 0.68, 95% confidence interval=0.48-0.98) had lower odds of inadequate sleep duration compared with children who grew up in historically high poverty. We show that the historical specification of neighborhood poverty remained significant despite controls, whereas contemporaneous measures of neighborhood poverty did not.

CONCLUSIONS

Our findings indicate strong associations between historical neighborhood poverty and child sleep duration.

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.

Extrapolating evidence of antiepileptic drug efficacy in adults to children ≥2 years of age with focal seizures: The case for disease similarity

Expediting pediatric access to new antiseizure drugs is particularly compelling, because epileptic seizures are the most common serious neurological symptom in children. Analysis of antiepileptic drug (AED) efficacy outcomes of randomized controlled trials, conducted during the past 20 years in different populations and a broad range of study sites and countries, has shown considerable consistency for each drug between adult and pediatric populations. Historically, the majority of regulatory approvals for AEDs have been for seizure types and not for specific epilepsy syndromes. Available data, both anatomical and neurophysiological, support a similar pathophysiology of focal seizures in adults and young children, and suggest that by age 2 years the structural and physiological milieu upon which seizures develop is similar. Although the distribution of specific etiologies and epilepsy syndromes is different in children from in adults, this should not impact approvals of efficacy based on seizure type, because the pathophysiology of focal seizures and the drug responsiveness of these seizure types are quite similar. Safety and pharmacokinetics cannot be extrapolated from adults to children. The scientific rationale, clinical consensus, and published data support a future approach accepting efficacy data from adult trials and focusing exclusively on prospective pharmacokinetic, tolerability, and safety studies and long-term follow-up in children. Whereas tolerability studies can be compared easily in children and adults, safety studies require large numbers of patients followed for many years.

Increased overall cortical connectivity with syndrome specific local decreases suggested by atypical sleep-EEG synchronization in Williams syndrome

Williams syndrome (7q11.23 microdeletion) is characterized by specific alterations in neurocognitive architecture and functioning, as well as disordered sleep. Here we analyze the region, sleep state and frequency-specific EEG synchronization of whole night sleep recordings of 21 Williams syndrome and 21 typically developing age- and gender-matched subjects by calculating weighted phase lag indexes. We found broadband increases in inter- and intrahemispheric neural connectivity for both NREM and REM sleep EEG of Williams syndrome subjects. These effects consisted of increased theta, high sigma, and beta/low gamma synchronization, whereas alpha synchronization was characterized by a peculiar Williams syndrome-specific decrease during NREM states (intra- and interhemispheric centro-temporal) and REM phases of sleep (occipital intra-area synchronization). We also found a decrease in short range, occipital connectivity of NREM sleep EEG theta activity. The striking increased overall synchronization of sleep EEG in Williams syndrome subjects is consistent with the recently reported increase in synaptic and dendritic density in stem-cell based Williams syndrome models, whereas decreased alpha and occipital connectivity might reflect and underpin the altered microarchitecture of primary visual cortex and disordered visuospatial functioning of Williams syndrome subjects.

Spectral-temporal EEG dynamics of speech discrimination processing in infants during sleep

Background

Oddball paradigms are frequently used to study auditory discrimination by comparing event-related potential (ERP) responses from a standard, high probability sound and to a deviant, low probability sound. Previous research has established that such paradigms, such as the mismatch response or mismatch negativity, are useful for examining auditory processes in young children and infants across various sleep and attention states. The extent to which oddball ERP responses may reflect subtle discrimination effects, such as speech discrimination, is largely unknown, especially in infants that have not yet acquired speech and language.

Results

Mismatch responses for three contrasts (non-speech, vowel, and consonant) were computed as a spectral-temporal probability function in 24 infants, and analyzed at the group level by a modified multidimensional scaling. Immediately following an onset gamma response (30–50 Hz), the emergence of a beta oscillation (12–30 Hz) was temporally coupled with a lower frequency theta oscillation (2–8 Hz). The spectral-temporal probability of this coupling effect relative to a subsequent theta modulation corresponds with discrimination difficulty for non-speech, vowel, and consonant contrast features.

Discussion

The theta modulation effect suggests that unexpected sounds are encoded as a probabilistic measure of surprise. These results support the notion that auditory discrimination is driven by the development of brain networks for predictive processing, and can be measured in infants during sleep. The results presented here have implications for the interpretation of discrimination as a probabilistic process, and may provide a basis for the development of single-subject and single-trial classification in a clinically useful context.

Conclusion

An infant’s brain is processing information about the environment and performing computations, even during sleep. These computations reflect subtle differences in acoustic feature processing that are necessary for language-learning. Results from this study suggest that brain responses to deviant sounds in an oddball paradigm follow a cascade of oscillatory modulations. This cascade begins with a gamma response that later emerges as a beta synchronization, which is temporally coupled with a theta modulation, and followed by a second, subsequent theta modulation. The difference in frequency and timing of the theta modulations appears to reflect a measure of surprise. These insights into the neurophysiological mechanisms of auditory discrimination provide a basis for exploring the clinically utility of the MMR_TF and other auditory oddball responses.

Developmental Changes in Ultradian Sleep Cycles across Early Childhood

Nocturnal human sleep is composed of cycles between rapid eye movement (REM) sleep and non-REM (NREM) sleep. In adults, the structure of ultradian cycles between NREM and REM sleep is well characterized; however, less is known about the developmental trajectories of ultradian sleep cycles across early childhood. Cross-sectional studies indicate that the rapid ultradian cycling of active-quiet sleep in infancy shifts to a more adult-like pattern of NREM-REM sleep cycling by the school-age years, yet longitudinal studies elucidating the details of this transition are scarce. To address this gap, we examined ultradian cycling during nocturnal sleep following 13 h of prior wakefulness in 8 healthy children at 3 longitudinal points: 2Y (2.5-3.0 years of age), 3Y (3.5-4.0 years of age), and 5Y (5.5-6.0 years of age). We found that the length of ultradian cycles increased with age as a result of increased NREM sleep episode duration. In addition, we observed a significant decrease in the number of NREM sleep episodes as well as a nonsignificant trend for a decrease in the number of cycles with increasing age. Together, these findings suggest a concurrent change in which cycle duration increases and the number of cycles decreases across development. We also found that, consistent with data from adolescents and adults, the duration of NREM sleep episodes decreased with time since lights-off whereas the duration of REM sleep episodes increased over this time period. These results indicate the presence of circadian modulation of nocturnal sleep in preschool children. In addition to characterizing changes in ultradian cycling in healthy children ages 2 to 5 years, this work describes a developmental model that may provide insights into the emergence of normal adult REM sleep regulatory circuitry as well as potential trajectories of dysregulated ultradian cycles such as those associated with affective disorders.

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.

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.

Increased Sleep Depth in Developing Neural Networks: New Insights from Sleep Restriction in Children

Brain networks respond to sleep deprivation or restriction with increased sleep depth, which is quantified as slow-wave activity (SWA) in the sleep electroencephalogram (EEG). When adults are sleep deprived, this homeostatic response is most pronounced over prefrontal brain regions. However, it is unknown how children’s developing brain networks respond to acute sleep restriction, and whether this response is linked to myelination, an ongoing process in childhood that is critical for brain development and cortical integration. We implemented a bedtime delay protocol in 5- to 12-year-old children to obtain partial sleep restriction (1-night; 50% of their habitual sleep). High-density sleep EEG was assessed during habitual and restricted sleep and brain myelin content was obtained using mcDESPOT magnetic resonance imaging. The effect of sleep restriction was analyzed using statistical non-parametric mapping with supra-threshold cluster analysis. We observed a localized homeostatic SWA response following sleep restriction in a specific parieto-occipital region. The restricted/habitual SWA ratio was negatively associated with myelin water fraction in the optic radiation, a developing fiber bundle. This relationship occurred bilaterally over parieto-temporal areas and was adjacent to, but did not overlap with the parieto-occipital region showing the most pronounced homeostatic SWA response. These results provide evidence for increased sleep need in posterior neural networks in children. Sleep need in parieto-temporal areas is related to myelin content, yet it remains speculative whether age-related myelin growth drives the fading of the posterior homeostatic SWA response during the transition to adulthood. Whether chronic insufficient sleep in the sensitive period of early life alters the anatomical generators of deep sleep slow-waves is an important unanswered question.

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.

State-Dependent Differences in Functional Connectivity in Young Children With Autism Spectrum Disorder

Background

While there is increasing evidence of altered brain connectivity in autism, the degree and direction of these alterations in connectivity and their uniqueness to autism has not been established. The aim of the present study was to compare connectivity in children with autism to that of typically developing controls and children with developmental delay without autism.

Methods

We assessed EEG spectral power, coherence, phase lag, Pearson and partial correlations, and epileptiform activity during the awake, slow wave sleep, and REM sleep states in 137 children aged 2 to 6 years with autism (n = 87), developmental delay without autism (n = 21), or typical development (n = 29).

Findings

We found that brain connectivity, as measured by coherence, phase lag, and Pearson and partial correlations distinguished children with autism from both neurotypical and developmentally delayed children. In general, children with autism had increased coherence which was most prominent during slow wave sleep.

Interpretation

Functional connectivity is distinctly different in children with autism compared to samples with typical development and developmental delay without autism. Differences in connectivity in autism are state and region related. In this study, children with autism were characterized by a dynamically evolving pattern of altered connectivity.

•

We used EEG to examine the connectivity in young children in awake, rapid eye movement, and slow wave sleep (SWS) states.

•

Differences in coherence between the autism group and the other groups were maximal during SWS.

•

Sleep may be the most sensitive time to measure differences in neuro-development before they are observable in behavior.

Shared mechanisms underlie normal healthy sleep and normal brain development. Therefore, we suspect that differences in the way that the brain is behaving during sleep have the potential to tell us about what might be developing incorrectly in people with neurodevelopmental disorders. In addition, sleep evaluations of children allow us to filter out waking distractions, so that we are truly measuring the brain working offline. For instance, the differences in the way the brain was connected that we observed between our three study groups were by far the most notable during slow wave sleep. This finding highlights the importance of taking the state of the brain into account when commenting on the ‘connectedness’ of the brain as a potential biomarker for neurodevelopmental disorders. Future attempts to classify developmental disorders by using differences in connectivity must take into account brain state, whether awake or asleep as well as developmental stage.