NREM sleep EEG slow waves in autistic and typically developing children: Morphological characteristics and scalp distribution

A Closer Look at Paediatric Sleep: Sleep Health and Sleep Behavioural Disorders in Children and Adolescents

Adequate sleep is crucial for healthy development, contributing significantly to physical and mental well-being. While research on paediatric sleep is expanding, there remain several open questions. This narrative review provides an overview of our current knowledge on paediatric sleep health and identifies literature gaps, considering factors such as age, gender, cultural differences, and the interplay between sleep, physical activity, nutrition, and mental health. It also considers sleep health in the more specific group of children with neurodevelopmental disorders. By viewing paediatric sleep health as a multidimensional construct, this review discusses age-specific issues, including the different factors affecting satisfaction, daytime alertness, sleep timing, efficiency and duration, and sleep-related behaviours. While gender differences in sleep health become apparent after puberty, few studies have addressed sex differences in children or different parental attitudes toward sleep in boys and girls. Cultural differences in sleep duration, timing, and setting are reported from infancy through adolescence; however, the cultural influence on sleep health, particularly during adolescence, remains unclear. This is crucial when considering the effects of screen time, smartphone use, and social media exposure on sleep. Further research is required to understand how sleep, nutrition, and physical health interact throughout the developmental span. Additionally, this review underscores the protective nature of sleep for adolescent mental health and for the management of emotional and behavioural problems in children with neurodevelopmental disorders. The review identifies critical areas for future research to enhance our understanding of paediatric sleep health and develop more effective and tailored interventions and preventive programmes.

Electroencephalography in Autism Spectrum Disorder

Background/Objectives: Electroencephalography (EEG) has been widely used to differentiate individuals with autism spectrum disorder (ASD) and co-occurring conditions, particularly epilepsy. However, the relationship between EEG abnormalities and core features of ASD remains unclear. This study reviews the potential impact of EEG findings on the development, behavior, sleep, and seizure occurrence in ASD patients. Additionally, it evaluates whether routine EEG testing is warranted for all ASD patients, particularly in the absence of clinical seizures. Methods: A systematic review was conducted that covered literature published between 2014 and 2024. The review focused on EEG abnormalities, both epileptiform and non-epileptiform, in individuals with ASD. Studies were selected based on predefined inclusion criteria, emphasizing the prevalence, type, and clinical relevance of EEG findings. The analysis also included a critical assessment of whether EEG abnormalities correlate with specific ASD symptoms, such as cognitive impairment, speech delay, or behavioral issues. Results: EEG abnormalities were reported in 23-80% of ASD patients, indicating a broad range of findings. Despite their frequent occurrence, the evidence linking these abnormalities to specific clinical symptoms remains inconclusive. Some studies suggest an association between epileptiform patterns and more severe ASD traits, while others do not confirm this. Furthermore, the effectiveness of anticonvulsant treatment in children with EEG abnormalities and no seizures remains uncertain, with limited supporting data. Conclusions: Given the uncertain relationship between EEG findings and ASD symptoms, routine EEG testing for all children with ASD appears unnecessary. EEG should be considered primarily when epilepsy is clinically suspected.

Recent Evidence of Non-Rapid Eye Movement Sleep Oscillation Abnormalities in Psychiatric Disorders

PURPOSE OF REVIEW

We review recent studies published from 2019 to 2024 examining slow waves and sleep spindles abnormalities across neurodevelopmental, mood, trauma-related, and psychotic disorders using polysomnography and Electroencephalogram (EEG).

RECENT FINDINGS

Individuals with attention-deficit/hyperactivity disorder (ADHD) showed higher slow-spindle activity, while findings on slow-wave activity were mixed. Individuals with autism spectrum disorder (ASD) showed inconsistent results with some evidence of lower spindle chirp and slow-wave amplitude. Individuals with depression displayed lower slow-wave and spindle parameters mostly in medicated patients. Individuals with post-traumatic stress disorder (PTSD) showed higher spindle frequency and activity, which were associated with their clinical symptoms. Psychotic disorders demonstrated the most consistent alterations, with lower spindle density, amplitude, and duration across illness stages that correlated with patients' symptom severity and cognitive deficits, whereas lower slow-wave measures were present in the early phases of the disorders. Sleep spindle and slow-wave abnormalities are present across psychiatric populations, with the most consistent alterations observed in psychotic disorders. Larger studies with standardized methodologies and longitudinal assessments are needed to establish the potential of these oscillations as neurophysiological biomarkers and/or treatment targets.

Hypnotic treatment improves sleep architecture and EEG disruptions and rescues memory deficits in a mouse model of fragile X syndrome

Fragile X syndrome (FXS) is associated with disrupted cognition and sleep abnormalities. Sleep loss negatively impacts cognitive function, and one untested possibility is that disrupted cognition in FXS is exacerbated by abnormal sleep. We tested whether ML297, a hypnotic acting on G-protein-activated inward-rectifying potassium (GIRK) channels, could reverse sleep phenotypes and disrupted memory in Fmr1-/y mice. Fmr1-/y mice exhibit reduced non-rapid eye movement (NREM) sleep and fragmented NREM architecture, altered sleep electroencephalogram (EEG) oscillations, and reduced EEG coherence between cortical areas; these are partially reversed following ML297 administration. Treatment following contextual fear or spatial learning restores disrupted memory consolidation in Fmr1-/y mice. During memory recall, Fmr1-/y mice show an altered balance of activity among hippocampal principal neurons vs. parvalbumin-expressing interneurons; this is partially reversed by ML297. Because sleep disruption could impact neurophysiological phenotypes in FXS, augmenting sleep may improve disrupted cognition in this disorder.

Neuroligin-2 shapes individual slow waves during slow-wave sleep and the response to sleep deprivation in mice

BACKGROUND

Sleep disturbances are a common comorbidity to most neurodevelopmental disorders and tend to worsen disease symptomatology. It is thus crucial to understand mechanisms underlying sleep disturbances to improve patients' quality of life. Neuroligin-2 (NLGN2) is a synaptic adhesion protein regulating GABAergic transmission. It has been linked to autism spectrum disorders and schizophrenia in humans, and deregulations of its expression were shown to cause epileptic-like hypersynchronized cerebral activity in rodents. Importantly, the absence of Nlgn2 (knockout: KO) was previously shown to alter sleep-wake duration and quality in mice, notably increasing slow-wave sleep (SWS) delta activity (1-4 Hz) and altering its 24-h dynamics. This type of brain oscillation is involved in memory consolidation, and is also a marker of homeostatic sleep pressure. Sleep deprivation (SD) is notably known to impair cognition and the physiological response to sleep loss involves GABAergic transmission.

METHODS

Using electrocorticographic (ECoG) recordings, we here first aimed to verify how individual slow wave (SW; 0.5-4 Hz) density and properties (e.g., amplitude, slope, frequency) contribute to the higher SWS delta activity and altered 24-h dynamics observed in Nlgn2 KO mice. We further investigated the response of these animals to SD. Finally, we tested whether sleep loss affects the gene expression of Nlgn2 and related GABAergic transcripts in the cerebral cortex of wild-type mice using RNA sequencing.

RESULTS

Our results show that Nlgn2 KO mice have both greater SW amplitude and density, and that SW density is the main property contributing to the altered 24-h dynamics. We also found the absence of Nlgn2 to accelerate paradoxical sleep recovery following SD, together with profound alterations in ECoG activity across vigilance states. Sleep loss, however, did not modify the 24-h distribution of the hypersynchronized ECoG events observed in these mice. Finally, RNA sequencing confirmed an overall decrease in cortical expression of Nlgn2 and related GABAergic transcripts following SD in wild-type mice.

CONCLUSIONS

This work brings further insight into potential mechanisms of sleep duration and quality deregulation in neurodevelopmental disorders, notably involving NLGN2 and GABAergic neurotransmission.

Sleep in 22q11.2 Deletion Syndrome: Current Findings, Challenges, and Future Directions

PURPOSE OF REVIEW

To summarize current literature available on sleep in 22q11.2 Deletion Syndrome (22q11.2DS; Velocardiofacial or DiGeorge Syndrome), a neurogenetic disorder caused by a hemizygous deletion in a genomic region critical for neurodevelopment. Due to the greatly increased risk of developmental psychiatric disorders (e.g., autism and schizophrenia) in 22q11.2DS, this review focuses on clinical correlates of sleep disturbances and potential neurobiological underpinnings of these relationships.

RECENT FINDINGS

Sleep disturbances are widely prevalent in 22q11.2DS and are associated with worse behavioral, psychiatric, and physical health outcomes. There are reports of sleep architecture and sleep neurophysiology differences, but the literature is limited by logistical challenges posed by objective sleep measures, resulting in small study samples to date. Sleep disturbances in 22q11.2DS are prevalent and have a substantial impact on well-being. Further investigation of sleep in 22q11.2DS utilizing multimodal sleep assessments has the potential to provide new insight into neurobiological mechanisms and a potential trans-diagnostic treatment target in 22q11.2DS.

Hypnotic treatment reverses NREM sleep disruption and EEG desynchronization in a mouse model of Fragile X syndrome to rescue memory consolidation deficits

Fragile X syndrome (FXS) is a highly-prevalent genetic cause of intellectual disability, associated with disrupted cognition and sleep abnormalities. Sleep loss itself negatively impacts cognitive function, yet the contribution of sleep loss to impaired cognition in FXS is vastly understudied. One untested possibility is that disrupted cognition in FXS is exacerbated by abnormal sleep. We hypothesized that restoration of sleep-dependent mechanisms could improve functions such as memory consolidation in FXS. We examined whether administration of ML297, a hypnotic drug acting on G-protein-activated inward-rectifying potassium channels, could restore sleep phenotypes and improve disrupted memory consolidation in Fmr1 -/y mice. Using 24-h polysomnographic recordings, we found that Fmr1 -/y mice exhibit reduced non-rapid eye movement (NREM) sleep and fragmented NREM sleep architecture, alterations in NREM EEG spectral power (including reductions in sleep spindles), and reduced EEG coherence between cortical areas. These alterations were reversed in the hours following ML297 administration. Hypnotic treatment following contextual fear or spatial learning also ameliorated disrupted memory consolidation in Fmr1 -/y mice. Hippocampal activation patterns during memory recall was altered in Fmr1 -/y mice, reflecting an altered balance of activity among principal neurons vs. parvalbumin-expressing (PV+) interneurons. This phenotype was partially reversed by post-learning ML297 administration. These studies suggest that sleep disruption could have a major impact on neurophysiological and behavioral phenotypes in FXS, and that hypnotic therapy may significantly improve disrupted cognition in this disorder.

Identification of atypical sleep microarchitecture biomarkers in children with autism spectrum disorder

Importance

Sleep disorders are one of the most frequent comorbidities in children with autism spectrum disorder (ASD). However, the link between neurodevelopmental effects in ASD children with their underlying sleep microarchitecture is not well understood. An improved understanding of etiology of sleep difficulties and identification of sleep-associated biomarkers for children with ASD can improve the accuracy of clinical diagnosis.

Objectives

To investigate whether machine learning models can identify biomarkers for children with ASD based on sleep EEG recordings.

Design setting and participants

Sleep polysomnogram data were obtained from the Nationwide Children' Health (NCH) Sleep DataBank. Children (ages: 8-16 yrs) with 149 autism and 197 age-matched controls without neurodevelopmental diagnosis were selected for analysis. An additional independent age-matched control group (n = 79) selected from the Childhood Adenotonsillectomy Trial (CHAT) was also used to validate the models. Furthermore, an independent smaller NCH cohort of younger infants and toddlers (age: 0.5-3 yr.; 38 autism and 75 controls) was used for additional validation.

Main outcomes and measures

We computed periodic and non-periodic characteristics from sleep EEG recordings: sleep stages, spectral power, sleep spindle characteristics, and aperiodic signals. Machine learning models including the Logistic Regression (LR) classifier, Support Vector Machine (SVM), and Random Forest (RF) model were trained using these features. We determined the autism class based on the prediction score of the classifier. The area under the receiver operating characteristics curve (AUC), accuracy, sensitivity, and specificity were used to evaluate the model performance.

Results

In the NCH study, RF outperformed two other models with a 10-fold cross-validated median AUC of 0.95 (interquartile range [IQR], [0.93, 0.98]). The LR and SVM models performed comparably across multiple metrics, with median AUC 0.80 [0.78, 0.85] and 0.83 [0.79, 0.87], respectively. In the CHAT study, three tested models have comparable AUC results: LR: 0.83 [0.76, 0.92], SVM: 0.87 [0.75, 1.00], and RF: 0.85 [0.75, 1.00]. Sleep spindle density, amplitude, spindle-slow oscillation (SSO) coupling, aperiodic signal's spectral slope and intercept, as well as the percentage of REM sleep were found to be key discriminative features in the predictive models.

Conclusion and relevance

Our results suggest that integration of EEG feature engineering and machine learning can identify sleep-based biomarkers for ASD children and produce good generalization in independent validation datasets. Microstructural EEG alterations may help reveal underlying pathophysiological mechanisms of autism that alter sleep quality and behaviors. Machine learning analysis may reveal new insight into the etiology and treatment of sleep difficulties in autism.

Sleep EEG in young people with 22q11.2 deletion syndrome: A cross-sectional study of slow-waves, spindles and correlations with memory and neurodevelopmental symptoms

Background

Young people living with 22q11.2 Deletion Syndrome (22q11.2DS) are at increased risk of schizophrenia, intellectual disability, attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). In common with these conditions, 22q11.2DS is also associated with sleep problems. We investigated whether abnormal sleep or sleep-dependent network activity in 22q11.2DS reflects convergent, early signatures of neural circuit disruption also evident in associated neurodevelopmental conditions.

Methods

In a cross-sectional design, we recorded high-density sleep EEG in young people (6-20 years) with 22q11.2DS (n=28) and their unaffected siblings (n=17), quantifying associations between sleep architecture, EEG oscillations (spindles and slow waves) and psychiatric symptoms. We also measured performance on a memory task before and after sleep.

Results

22q11.2DS was associated with significant alterations in sleep architecture, including a greater proportion of N3 sleep and lower proportions of N1 and REM sleep than in siblings. During sleep, deletion carriers showed broadband increases in EEG power with increased slow-wave and spindle amplitudes, increased spindle frequency and density, and stronger coupling between spindles and slow-waves. Spindle and slow-wave amplitudes correlated positively with overnight memory in controls, but negatively in 22q11.2DS. Mediation analyses indicated that genotype effects on anxiety, ADHD and ASD were partially mediated by sleep EEG measures.

Conclusions

This study provides a detailed description of sleep neurophysiology in 22q11.2DS, highlighting alterations in EEG signatures of sleep which have been previously linked to neurodevelopment, some of which were associated with psychiatric symptoms. Sleep EEG features may therefore reflect delayed or compromised neurodevelopmental processes in 22q11.2DS, which could inform our understanding of the neurobiology of this condition and be biomarkers for neuropsychiatric disorders.

Funding

This research was funded by a Lilly Innovation Fellowship Award (UB), the National Institute of Mental Health (NIMH 5UO1MH101724; MvdB), a Wellcome Trust Institutional Strategic Support Fund (ISSF) award (MvdB), the Waterloo Foundation (918-1234; MvdB), the Baily Thomas Charitable Fund (2315/1; MvdB), MRC grant Intellectual Disability and Mental Health: Assessing Genomic Impact on Neurodevelopment (IMAGINE) (MR/L011166/1; JH, MvdB and MO), MRC grant Intellectual Disability and Mental Health: Assessing Genomic Impact on Neurodevelopment 2 (IMAGINE-2) (MR/T033045/1; MvdB, JH and MO); Wellcome Trust Strategic Award 'Defining Endophenotypes From Integrated Neurosciences' Wellcome Trust (100202/Z/12/Z MO, JH). NAD was supported by a National Institute for Health Research Academic Clinical Fellowship in Mental Health and MWJ by a Wellcome Trust Senior Research Fellowship in Basic Biomedical Science (202810/Z/16/Z). CE and HAM were supported by Medical Research Council Doctoral Training Grants (C.B.E. 1644194, H.A.M MR/K501347/1). HMM and UB were employed by Eli Lilly & Co during the study; HMM is currently an employee of Boehringer Ingelheim Pharma GmbH & Co KG. The views and opinions expressed are those of the author(s), and not necessarily those of the NHS, the NIHR or the Department of Health funders.

Neurobehavioral Associations with NREM and REM Sleep Architecture in Children with Autism Spectrum Disorder

Objective: Insomnia and daytime behavioral problems are common issues in pediatric autism spectrum disorder (ASD), yet specific underlying relationships with NonRapid Eye Movement sleep (NREM) and Rapid Eye Movement (REM) sleep architecture are understudied. We hypothesize that REM sleep alterations (REM%, REM EEG power) are associated with more internalizing behaviors and NREM sleep deficits (N3%; slow wave activity (SWA) 0.5–3 Hz EEG power) are associated with increased externalizing behaviors in children with ASD vs. typical developing controls (TD). Methods: In an age- and gender-matched pediatric cohort of n = 23 ASD and n = 20 TD participants, we collected macro/micro sleep architecture with overnight home polysomnogram and daytime behavior scores with Child Behavior Checklist (CBCL) scores. Results: Controlling for non-verbal IQ and medication use, ASD and TD children have similar REM and NREM sleep architecture. Only ASD children show positive relationships between REM%, REM theta power and REM beta power with internalizing scores. Only TD participants showed an inverse relationship between NREM SWA and externalizing scores. Conclusion: REM sleep measures reflect concerning internalizing behaviours in ASD and could serve as a biomarker for mood disorders in this population. While improving deep sleep may help externalizing behaviours in TD, we do not find evidence of this relationship in ASD.

Neural responses to affective speech, including motherese, map onto clinical and social eye tracking profiles in toddlers with ASD

Affective speech, including motherese, captures an infant's attention and enhances social, language and emotional development. Decreased behavioural response to affective speech and reduced caregiver-child interactions are early signs of autism in infants. To understand this, we measured neural responses to mild affect speech, moderate affect speech and motherese using natural sleep functional magnetic resonance imaging and behavioural preference for motherese using eye tracking in typically developing toddlers and those with autism. By combining diverse neural-clinical data using similarity network fusion, we discovered four distinct clusters of toddlers. The autism cluster with the weakest superior temporal responses to affective speech and very poor social and language abilities had reduced behavioural preference for motherese, while the typically developing cluster with the strongest superior temporal response to affective speech showed the opposite effect. We conclude that significantly reduced behavioural preference for motherese in autism is related to impaired development of temporal cortical systems that normally respond to parental affective speech.

Evidence of a maturational disruption in non-rapid eye movement sleep slow wave activity in youth with attention-deficit/hyperactivity, learning and internalizing disorders

BACKGROUND

Sleep slow wave activity (SWA) peaks during childhood and declines in the transition to adolescence during typical development (TD). It remains unknown whether this trajectory differs in youth with neuropsychiatric disorders.

METHODS

We analyzed sleep EEGs of 664 subjects 6 to 21 y (449 TD, 123 unmedicated, 92 medicated) and 114 subjects 7-12 y (median 10.5 y) followed-up at 18-22 y (median 19 y). SWA (0.4-4 Hz) power was calculated during non-rapid eye movement sleep.

RESULTS

TD and unmedicated youth showed cubic central and frontal SWA trajectories from 6 to 21 y (p-cubic<0.05), with TD youth showing peaks in central SWA at 6.8 y and frontal at 8.2 y. Unmedicated attention-deficit/hyperactivity (ADHD) and/or learning disorders (LD) showed peak central SWA 2 y later (at 9.6 y, coinciding with peak frontal SWA) than TD, followed by a 67% steeper slope by 19 y. Frontal SWA peak and slope in unmedicated ADHD/LD, and that of central and frontal in internalizing disorders (ID), were similar to TD. Unmedicated ADHD/LD did not differ in the longitudinal SWA percent change by 18-22 y; unmedicated ID showed a lower longitudinal change in frontal SWA than TD. Medicated youth showed a linear decline in central and frontal SWA from 6 to 21 y (p-linear<0.05).

CONCLUSIONS

ADHD/LD youth show a maturational delay and potential topographical disruption in SWA during childhood and steeper decline throughout adolescence, suggesting faster synaptic pruning. Youth with ID experience less changes in frontal SWA by late adolescence. Psychotropic medications may impact the maturational trajectory of SWA, but not the magnitude of developmental decline by late adolescence.

Nonrapid eye movement sleep characteristics and relations with motor, memory, and cognitive ability from infancy to preadolescence

Sleep plays a critical role in neural neurodevelopment. Hallmarks of sleep reflected in the electroencephalogram during nonrapid eye movement (NREM) sleep are associated with learning processes, cognitive ability, memory, and motor functioning. Research in adults is well-established; however, the role of NREM sleep in childhood is less clear. Growing evidence suggests the importance of two NREM sleep features: slow-wave activity and sleep spindles. These features may be critical for understanding maturational change and the functional role of sleep during development. Here, we review the literature on NREM sleep from infancy to preadolescence to provide insight into the network dynamics of the developing brain. The reviewed findings show distinct relations between topographical and maturational aspects of slow waves and sleep spindles; however, the direction and consistency of these relationships vary, and associations with cognitive ability remain unclear. Future research investigating the role of NREM sleep and development would benefit from longitudinal approaches, increased control for circadian and homeostatic influences, and in early childhood, studies recording daytime naps and overnight sleep to yield increased precision for detecting age-related change. Such evidence could help explicate the role of NREM sleep and provide putative physiological markers of neurodevelopment.

Subjective and Electroencephalographic Sleep Parameters in Children and Adolescents with Autism Spectrum Disorder: A Systematic Review

Background: Sleep problems have commonly manifested in children and adolescents with autism spectrum disorder (ASD) with a complex and multifactorial interaction between clinical and etiological components. These disorders are associated with functional impairment, and provoke significant physical and mental affliction. The purpose of this study is to update the existing literature about objective and subjective sleep parameters in children and adolescents with ASD, extrapolating information from polysomnography or sleep electroencephalography, and sleep related questionnaires. Methods: We have conducted a systematic review of case-control studies on this topic, performing a web-based search on PubMed, Scopus and the Web of Science databases according to the Preferred Reporting items for Systematic Review and Meta-analyses (PRISMA) guidelines. Results: Data collected from 20 survey result reports showed that children and adolescents with ASD experienced a higher rate of sleep abnormalities than in typically developing children. The macrostructural sleep parameters that were consistent with subjective parent reported measures unveil a greater percentage of nighttime signs of insomnia. Sleep microstructure patterns, in addition, pointed towards the bidirectional relationship between brain dysfunctions and sleep problems in children with ASD. Conclusions: Today’s literature acknowledges that objective and subjective sleep difficulties are more often recognized in individuals with ASD, so clinicians should assess sleep quality in the ASD clinical population, taking into consideration the potential implications on treatment strategies. It would be worthwhile in future studies to examine how factors, such as age, cognitive level or ASD severity could be related to ASD sleep abnormalities. Future research should directly assess whether sleep alterations could represent a specific marker for atypical brain development in ASD.

How do children with autism spectrum disorder form gist memory during sleep? A study of slow oscillation-spindle coupling

Sleep is assumed to support memory through an active systems consolidation process that does not only strengthen newly encoded representations but also facilitates the formation of more abstract gist memories. Studies in humans and rodents indicate a key role of the precise temporal coupling of sleep slow oscillations (SO) and spindles in this process. The present study aimed at bolstering these findings in typically developing (TD) children, and at dissecting particularities in SO-spindle coupling underlying signs of enhanced gist memory formation during sleep found in a foregoing study in children with autism spectrum disorder (ASD) without intellectual impairment. Sleep data from 19 boys with ASD and 20 TD boys (9-12 years) were analyzed. Children performed a picture-recognition task and the Deese-Roediger-McDermott (DRM) task before nocturnal sleep (encoding) and in the next morning (retrieval). Sleep-dependent benefits for visual-recognition memory were comparable between groups but were greater for gist abstraction (recall of DRM critical lure words) in ASD than TD children. Both groups showed a closely comparable SO-spindle coupling, with fast spindle activity nesting in SO-upstates, suggesting that a key mechanism of memory processing during sleep is fully functioning already at childhood. Picture-recognition at retrieval after sleep was positively correlated to frontocortical SO-fast-spindle coupling in TD children, and less in ASD children. Critical lure recall did not correlate with SO-spindle coupling in TD children but showed a negative correlation (r = -.64, p = .003) with parietal SO-fast-spindle coupling in ASD children, suggesting other mechanisms specifically conveying gist abstraction, that may even compete with SO-spindle coupling.

REM Sleep EEG Activity and Clinical Correlates in Adults With Autism

We tested the hypothesis of an atypical scalp distribution of electroencephalography (EEG) activity during Rapid Eye Movement (REM) sleep in young autistic adults. EEG spectral activity and ratios along the anteroposterior axis and across hemispheres were compared in 16 neurotypical (NT) young adults and 17 individuals with autism spectrum disorder (ASD). EEG spectral power was lower in the ASD group over the bilateral central and right parietal (beta activity) as well as bilateral occipital (beta, theta, and total activity) recording sites. The NT group displayed a significant posterior polarity of intra-hemispheric EEG activity while EEG activity was more evenly or anteriorly distributed in ASD participants. No significant inter-hemispheric EEG lateralization was found. Correlations between EEG distribution and ASD symptoms using the Autism Diagnostic Interview-Revised (ADI-R) showed that a higher posterior ratio was associated with a better ADI-R score on communication skills, whereas a higher anterior ratio was related to more restricted interests and repetitive behaviors. EEG activity thus appears to be atypically distributed over the scalp surface in young adults with autism during REM sleep within cerebral hemispheres, and this correlates with some ASD symptoms. These suggests the existence in autism of a common substrate between some of the symptoms of ASD and an atypical organization and/or functioning of the thalamo-cortical loop during REM sleep.

Sleep electroencephalography and brain maturation: developmental trajectories and the relation with cognitive functioning

Sleep has a crucial role in brain functioning and cognition, and several sleep electroencephalography (EEG) hallmarks are associated with intellectual abilities, neural plasticity, and learning processes. Starting from this evidence, a growing interest has been raised regarding the involvement of the sleep EEG in brain maturation and cognitive functioning during typical development (TD). The aim of this review is to provide a general framework about the maturational changes and the functional role of the human sleep EEG during TD from birth to late adolescence (≤22 years). The reviewed findings show large developmental modifications in several sleep EEG hallmarks (slow wave activity, sleep spindles, theta activity, and cyclic alternating pattern) during TD, and many studies support the notion of an active role of sleep slow wave activity in supporting brain maturation. Moreover, we focus on the possible relation between sleep microstructure, intelligence, and several memory domains (declarative, emotional, procedural), showing that sleep EEG oscillations seem involved in intellectual abilities and learning processes during TD, although results are often conflicting and divergent from findings in adults. Starting from the present literature, we propose that larger methodological uniformity, greater attention to the topographical and maturational aspects of the sleep EEG oscillations and their mutual interactions, and a higher number of longitudinal studies will be essential to clarify the role of the sleep EEG in cognitive functioning during TD.

Reduced sleep pressure in young children with autism

Study Objectives

Sleep disturbances and insomnia are highly prevalent in children with Autism Spectrum Disorder (ASD). Sleep homeostasis, a fundamental mechanism of sleep regulation that generates pressure to sleep as a function of wakefulness, has not been studied in children with ASD so far, and its potential contribution to their sleep disturbances remains unknown. Here, we examined whether slow-wave activity (SWA), a measure that is indicative of sleep pressure, differs in children with ASD.

Methods

In this case-control study, we compared overnight electroencephalogram (EEG) recordings that were performed during Polysomnography (PSG) evaluations of 29 children with ASD and 23 typically developing children.

Results

Children with ASD exhibited significantly weaker SWA power, shallower SWA slopes, and a decreased proportion of slow-wave sleep in comparison to controls. This difference was largest during the first 2 hours following sleep onset and decreased gradually thereafter. Furthermore, SWA power of children with ASD was significantly negatively correlated with the time of their sleep onset in the lab and at home, as reported by parents.

Conclusions

These results suggest that children with ASD may have a dysregulation of sleep homeostasis that is manifested in reduced sleep pressure. The extent of this dysregulation in individual children was apparent in the amplitude of their SWA power, which was indicative of the severity of their individual sleep disturbances. We, therefore, suggest that disrupted homeostatic sleep regulation may contribute to sleep disturbances in children with ASD.