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

Spatiotemporal EEG dynamics of the sleep onset process in preadolescence

BACKGROUND

During preadolescence the sleep electroencephalography undergoes massive qualitative and quantitative modifications. Despite these relevant age-related peculiarities, the specific EEG pattern of the wake-sleep transition in preadolescence has not been exhaustively described.

METHODS

The aim of the present study is to characterize regional and temporal electrophysiological features of the sleep onset (SO) process in a group of 23 preadolescents (9-14 years) and to compare the topographical pattern of slow wave activity and delta/beta ratio of preadolescents with the EEG pattern of young adults.

RESULTS

Results showed in preadolescence the same dynamics known for adults, but with peculiarities in the delta and beta activity, likely associated with developmental cerebral modifications: the delta power showed a widespread increase during the SO with central maxima, and the lower bins of the beta activity showed a power increase after SO. Compared to adults, preadolescents during the SO exhibited higher delta power only in the slowest bins of the band: before SO slow delta activity was higher in prefrontal, frontal and occipital areas in preadolescents, and, after SO the younger group had higher slow delta activity in occipital areas. In preadolescents delta/beta ratio was higher in more posterior areas both before and after the wake-sleep transition and, after SO, preadolescents showed also a lower delta/beta ratio in frontal areas, compared to adults.

CONCLUSION

Results point to a general higher homeostatic drive for the developing areas, consistently with plastic-related maturational modifications, that physiologically occur during preadolescence.

Electroencephalographic slowing during REM sleep in older adults with subjective cognitive impairment and mild cognitive impairment

STUDY OBJECTIVES

In older adults with Alzheimer's disease, slowing of electroencephalographic (EEG) activity during REM sleep has been observed. Few studies have examined EEG slowing during REM in those with mild cognitive impairment (MCI) and none have examined its relationship with cognition in this at-risk population.

METHODS

Two hundred and ten older adults (mean age = 67.0, SD = 8.2 years) underwent comprehensive neuropsychological, medical, and psychiatric assessment and overnight polysomnography. Participants were classified as subjective cognitive impairment (SCI; n = 75), non-amnestic MCI (naMCI, n = 85), and amnestic MCI (aMCI, n = 50). REM EEG slowing was defined as (δ + θ)/(α + σ + β) power and calculated for frontal, central, parietal, and occipital regions. Analysis of variance compared REM EEG slowing between groups. Correlations between REM EEG slowing and cognition, including learning and memory, visuospatial and executive functions, were examined within each subgroup.

RESULTS

The aMCI group had significantly greater REM EEG slowing in the parietal and occipital regions compared to the naMCI and SCI groups (partial η2 = 0.06, p < 0.05 and 0.06, p < 0.05, respectively), and greater EEG slowing in the central region compared to SCI group (partial η2 = 0.03, p < 0.05). Greater REM EEG slowing in parietal (r = -0.49) and occipital regions (r = -0.38 [O1/M2] and -0.33 [O2/M1]) were associated with poorer visuospatial performance in naMCI.

CONCLUSIONS

REM EEG slowing may differentiate older adults with memory impairment from those without. Longitudinal studies are now warranted to examine the prognostic utility of REM EEG slowing for cognitive and dementia trajectories.

Sleep duration trajectories and cognition in early childhood: A systematic review

Sleep is dynamic in childhood and studies have shown the relationship between sleep and cognition in children. As the human brain is the most plastic during childhood, the study of longitudinal sleep patterns and neurocognition is an important research area. We aimed to systematically review studies that investigated sleep duration trajectories and cognition in typically-developing children. We searched four databases for articles published between 2003 to October 2023. We included observation studies of children with sleep duration trajectories as a predictor and outcomes related to cognition, memory, language, developmental milestones, intelligence or executive function. We excluded studies where children had atypical development or completed the sleep and neurocognitive assessments after six and 12 years of age respectively. Out of 752 articles identified, 511 were screened and 23 full texts were assessed. The selected studies included three single trajectory and four multiple group trajectories studies. We found associations between both types of trajectories and cognitive development. Overall, children with longer sleep trajectories or more mature sleep pattern with rapid decrease in sleep duration, had better performance scores in developmental assessment tools, and intelligence tests. Findings for language and executive functioning were mixed, whereby some studies found associations and others did not.

Characteristics of ADHD Symptoms and EEG Theta/Beta Ratio in Children With Sleep Disordered Breathing

Objectives. This study aimed to explore parent-reported symptoms of attention deficit-hyperactivity disorder (ADHD) and sleep electroencephalogram (EEG) theta/beta ratio (TBR) characteristics in children with sleep disordered breathing (SDB). Methods. The parents of children (aged 6-11 years) with SDB (n = 103) and healthy controls (n = 28) completed the SNAP-IV questionnaire, and children underwent overnight polysomnography. Children with SDB were grouped according to obstructive apnea/hypopnea index: primary snoring, mild, and moderate-severe obstructive sleep apnea (OSA) groups. The TBR in non-rapid eye movement (NREM) periods in three sleep cycles was analyzed. Results. Children with SDB showed worse ADHD symptoms compared with the healthy control. There was no intergroup difference in TBR. The time-related decline in TBR observed in the control, primary snoring and mild OSA groups, which was not observed in the moderate-severe OSA group. Overnight transcutaneous oxygen saturation was negatively associated with the hyperactivity/impulsivity score of ADHD symptom. The global TBR during the NREM period in the first sleep cycle was positively correlated with inattention score. Conclusion. Children with SDB showed more ADHD inattention symptoms than the healthy control. Although we found no difference in TBR among groups, we found significant main effect for NREM period. There existed a relationship between hypoxia, TBR, and scores of ADHD symptoms. Hence, it was speculated that TBR can reflect the nocturnal electrophysiological manifestations in children with SDB, which may be related to daytime ADHD symptoms.

Does the absence or presence of sleep spindles on EEG have prognostic value for cognitive outcome in children with infantile epileptic spasms syndrome? A systematic literature review

Infantile Epileptic Spasms Syndrome (IESS) is an epileptic encephalopathy in childhood that affects infants under the age of two years. When spasm series occur, prognosis for cognitive outcome is poor in the majority of cases. The encephalopathy in IESS includes delayed maturation of normal sleep phenomena in the EEG, such as sleep spindles. Children with intellectual disabilities often have abnormal sleep, and children with sleep problems have difficulties learning at school. We examined whether there is evidence of prognostic value of detection of sleep spindles in the EEG of children with IESS on their future cognitive development. A systematic literature search yielded five studies touching this question. They were evaluated by two scorers independently. The lack of normal sleep patterns including lack of sleep spindles was used as a biomarker of poor cognitive outcome. Positive (PPV) and Negative (NPV) prognostic values were calculated. A summary of all five studies indicates a PPV of 82% and an NPV of 45%. Given the small amount of data, the retrospective quality of most studies, and the differences in the outcome parameters reported, it is prudent to say that currently available data do not allow us to conclude whether spindles have a specific and independent role in the cognitive prognosis of affected children. Since sleep spindles are needed for memory consolidation and demonstrate the active role of sleep for learning and memory, the hypothesis remains that their absence in the EEG may indicate an increased risk of cognitive delay, but more supporting data are needed to reach such a firm conclusion.

Does the brain sleep differently depending on intellectual abilities?

AIMS

To compare the children's sleep electroencephalogram according to their intellectual profile.

METHODS

Children were grouped according to their Wechsler Intelligence Scale for Children (WISC) scores (17 with normal intelligence quotient [IQ, NIQ] and 24 with high IQ [HIQ]). Comparisons of spectral power between groups and its relationship with WISC scores were assessed using analyses of variance and linear regression models, adjusted for age and sex.

RESULTS

Children with HIQ had more rapid eye movement (REM) sleep, especially late at night, and more power in slow-frequency bands during REM sleep than those with NIQ. There were also positive associations between the processing speed index and the spectral power in β bands in NREM sleep, and with the spectral power in α, σ, β, and γ bands in REM sleep, with different associations between groups.

CONCLUSION

The enhanced power in slow bands during REM sleep in children with HIQ overlaps with that of typical REM sleep oscillations thought to be involved in emotional memory consolidation. The dissimilar relationships between spectral power and WISC scores in NIQ and HIQ groups may underlie functional differences in brain activity related to cognitive efficiency, questioning the direction of the relationship between sleep and cognitive functioning.

Maturational trend of daytime sleep propensity in adolescents

STUDY OBJECTIVES

The teenage increase in sleepiness is not simply a response to decreasing nighttime sleep duration. Daytime sleepiness increases across adolescence even when prior sleep duration is held constant. Here we determine the maturational trend in daytime sleep propensity assessed with the multiple sleep latency test (MSLT) and assess the trend's relation to pubertal maturation and changes in the sleep electroencephalogram. We also evaluate whether the relation of daytime sleep propensity to prior sleep duration changes between ages 10 and 23 years.

METHODS

Participants (n = 159) entered the study between ages 9.8 and 22.8 years and were studied annually for up to 3 years. Annually, participants kept each of three sleep schedules in their homes: 7, 8.5, and 10 hours in bed for 4 consecutive nights with polysomnography on nights 2 and 4. MSLT-measured daytime sleep propensity was assessed in the laboratory on the day following the fourth night.

RESULTS

A two-part linear spline model described the maturation of daytime sleep propensity. MSLT sleep likelihood increased steeply until age 14.3 years, after which it did not change significantly. The maturational trend was strongly associated with the adolescent decline in slow-wave (delta, 1-4 Hz) EEG power during NREM sleep and with pubertal maturation assessed with Tanner stage measurement of breast/genital development. The effect of prior sleep duration on sleep likelihood decreased with age.

CONCLUSIONS

Adolescent brain changes related to pubertal maturation and those reflected in the delta decline contribute to the adolescent increase in daytime sleep propensity.

Maturation-dependent changes in cortical and thalamic activity during sleep slow waves: Insights from a combined EEG-fMRI study

INTRODUCTION

Studies using scalp EEG have shown that slow waves (0.5-4 Hz), the most prominent hallmark of NREM sleep, undergo relevant changes from childhood to adulthood, mirroring brain structural modifications and the acquisition of cognitive skills. Here we used simultaneous EEG-fMRI to investigate the cortical and subcortical correlates of slow waves in school-age children and determine their relative developmental changes.

METHODS

We analyzed data from 14 school-age children with self-limited focal epilepsy of childhood who fell asleep during EEG-fMRI recordings. Brain regions associated with slow-wave occurrence were identified using a voxel-wise regression that also modelled interictal epileptic discharges and sleep spindles. At the group level, a mixed-effects linear model was used. The results were qualitatively compared with those obtained from 2 adolescents with epilepsy and 17 healthy adults.

RESULTS

Slow waves were associated with hemodynamic-signal decreases in bilateral somatomotor areas. Such changes extended more posteriorly relative to those in adults. Moreover, the involvement of areas belonging to the default mode network changes as a function of age. No significant hemodynamic responses were observed in subcortical structures. However, we identified a significant correlation between age and thalamic hemodynamic changes.

CONCLUSIONS

Present findings indicate that the somatomotor cortex may have a key role in slow-wave expression throughout the lifespan. At the same time, they are consistent with a posterior-to-anterior shift in slow-wave distribution mirroring brain maturational changes. Finally, our results suggest that slow-wave changes may not reflect only neocortical modifications but also the maturation of subcortical structures, including the thalamus.

Sleep Stage Transitions and Sleep-Dependent Memory Consolidation in Children with Narcolepsy-Cataplexy

Electroencephalographic sleep stage transitions and altered first REM sleep period transitions have been identified as biomarkers of type 1 narcolepsy in adults, but not in children. Studies on memory complaints in narcolepsy have not yet investigated sleep-dependent memory consolidation. We aimed to explore stage transitions; more specifically altered REM sleep transition and its relationship with sleep-dependent memory consolidation in children with narcolepsy. Twenty-one children with narcolepsy-cataplexy and twenty-three healthy control children completed overnight polysomnography and sleep-dependent memory consolidation tests. Overnight transition rates (number of transitions per hour), global relative transition frequencies (number of transitions between a stage and all other stages/total number of transitions × 100), overnight transitions to REM sleep (transition from a given stage to REM/total REM transitions × 100), and altered first REM sleep period transitions (transitions from wake or N1 to the first REM period) were computed. Narcoleptic children had a significantly higher overnight transition rate with a higher global relative transition frequencies to wake. A lower sleep-dependent memory consolidation score found in children with narcolepsy was associated with a higher overnight transition frequency. As observed in narcoleptic adults, 90.48% of narcoleptic children exhibited an altered first REM sleep transition. As in adults, the altered sleep stage transition is also present in children with narcolepsy-cataplexy, and a higher transition rate could have an impact on sleep-dependent memory consolidation. These potential biomarkers could help diagnose type 1 narcolepsy in children more quickly; however, further studies with larger cohorts, including of those with type 2 narcolepsy and hypersomnia, are needed.

Characteristics of the Attentional Network in Children with Sleep-Disordered Breathing

Purpose

To explore the characteristics of the attentional network and related factors in children with sleep-disordered breathing (SDB).

Patients and Methods

A total 228 children (200 children aged 6-10 years with snoring or mouth breathing, admitted to our hospital from May 2020 to July 2022, and 28 healthy children recruited from the community as the control group) were enrolled. All participants underwent polysomnography (PSG) and completed the ADHD rating scale and child version of the Attention Network Test. According to their SDB history and obstructive apnea hypopnea index (OAHI), the participants were divided into control (n = 28), primary snoring (PS; n = 67) and obstructive sleep apnea (OSA; n = 133) groups.

Results

The OSA and PS groups were younger than controls (P < 0.05). The proportion of boys was higher in the OSA than control group (P < 0.05). Body mass index was higher in the OSA than control and PS groups (P < 0.01). Attention deficit and hyperactive impulsivity scores were independently associated with the OAHI (P < 0.001). The efficiency of the alerting network was higher in the OSA than in controls (P = 0.020), but was not correlated with OAHI after adjusting for age, sex and SDB history duration (P > 0.05).

Conclusion

Children with OSA have impaired attention, characterized by excessive alerting network activation. However, alerting network efficiency did not change linearly with disease severity. More research is needed to elucidate the neural mechanisms underlying attention deficits in pediatric OSA.

Relationship between self-reported sleep and cognitive function: a specification curve analysis

The relationship between self-reported sleep and cognitive function is complex; it is unclear whether self-reported sleep is a robust correlate of people's cognitive function. We address this gap by using a comprehensive large-scale dataset (N = 1054) coupled with a novel modeling approach, specification curve analysis (SCA), to test the association between self-reported sleep and cognitive function. The results of the SCA showed robust correlations between self-reported sleep and cognitive function, with poorer sleep associated with worse cognitive function. Furthermore, the correlations between sleep components and cognitive function were heterogeneous, with differences emerging across cognitive measures and domains. Specifically, daytime dysfunction was associated with the strongest effect on subjective cognitive function, whereas sleep duration and sleep efficiency had the strongest effect on objective cognitive function. Therefore, the relationship between self-reported sleep and cognition depends largely on what and how cognitive function is measured. Our findings guide measurement and domain selection for future research on the role of sleep in cognitive function.

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.

'High-Density-SleepCleaner': An open-source, semi-automatic artifact removal routine tailored to high-density sleep EEG

BACKGROUND

With up to 256 channels, high-density electroencephalography (hd-EEG) has become essential to the sleep research field. The vast amount of data resulting from this magnitude of channels in overnight EEG recordings complicates the removal of artifacts.

NEW METHOD

We present a new, semi-automatic artifact removal routine specifically designed for sleep hd-EEG recordings. By employing a graphical user interface (GUI), the user assesses epochs in regard to four sleep quality markers (SQMs). Based on their topography and underlying EEG signal, the user eventually removes artifactual values. To identify artifacts, the user is required to have basic knowledge of the typical (patho-)physiological EEG they are interested in, as well as artifactual EEG. The final output consists of a binary matrix (channels x epochs). Channels affected by artifacts can be restored in afflicted epochs using epoch-wise interpolation, a function included in the online repository.

RESULTS

The routine was applied in 54 overnight sleep hd-EEG recordings. The proportion of bad epochs highly depends on the number of channels required to be artifact-free. Between 95% and 100% of bad epochs could be restored using epoch-wise interpolation. We furthermore present a detailed examination of two extreme cases (with few and many artifacts). For both nights, the topography and cyclic pattern of delta power look as expected after artifact removal.

COMPARISON WITH EXISTING METHODS

Numerous artifact removal methods exist, yet their scope of application usually targets short wake EEG recordings. The proposed routine provides a transparent, practical, and efficient approach to identify artifacts in overnight sleep hd-EEG recordings.

CONCLUSION

This method reliably identifies artifacts simultaneously in all channels and epochs.

Season is related to the slow wave and sigma activity of infants and toddlers

OBJECTIVE/BACKGROUND

Slow wave activity (SWA) and sigma frequency activity (SFA) are hallmarks of NREM sleep EEG and important indicators of neural plasticity, development of the central nervous system, and cognition. However, little is known about the factors that modulate these sleep EEG activities, especially in small children.

PATIENTS/METHODS

We analyzed the power spectral densities of SWA (1-4 Hz) and SFA range (10-15 Hz) from six EEG derivations of 56 infants (8 months) and 60 toddlers (24 months) during their all-night sleep and during the first and the last half of night sleep. The spectral values were compared between the four seasons.

RESULTS

In the spring group of infants, compared with the darker seasons, SFA was lower in the centro-occipital EEG derivations during both halves of the night. The SWA findings of the infants were restricted to the last half of the night (SWA2) and frontally, where SWA2 was higher during winter than spring. The toddlers presented less frontal SWA2 during winter compared with autumn. Both age groups showed a reduction in both SWA and SFA towards the last half of the night.

CONCLUSIONS

The sleep EEG spectral power densities are more often associated with seasons in infants' SFA range. The results might stem from seasonally changing light exposure, but the exact mechanism warrants further study. Moreover, contrary to the adult-like increment of SFA, the SFA at both ages was lower at the last part of the night sleep. This suggests different regulation of spindle activity in infants and toddlers.

Habitual night waking associates with dynamics of waking cortical theta power in infancy

The implications of the substantial individual differences in infant sleep for early brain development remain unclear. Here, we examined whether night sleep quality relates to daytime brain activity, operationalized through measures of EEG theta power and its dynamic modulation, which have been previously linked to later cognitive development. For this longitudinal study, 76 typically developing infants were studied (age: 4-14 months, 166 individual study visits) over the course of 6 months with one, two, three, or four lab visits. Habitual sleep was measured with a 7-day sleep diary and actigraphy, and the Brief Infant Sleep Questionnaire. Twenty-channel EEG was recorded while infants watched multiple rounds of videos of women singing nursery rhymes; oscillatory power in the theta band was extracted. Key metrics were average theta across stimuli and the slope of change in theta within the first novel movie. Both objective and subjective sleep assessment methods showed a relationship between more night waking and higher overall theta power and reduced dynamic modulation of theta over the course of the novel video stimuli. These results may indicate altered learning and consolidation in infants with more disrupted night sleep, which may have implications for cognitive development.

Deep-spindle: An automated sleep spindle detection system for analysis of infant sleep spindles

BACKGROUND

Sleep spindles are an indicator of the development and integrity of the central nervous system in infants. Identifying sleep spindles manually in EEG is time-consuming and typically requires experienced experts. Automated detection of sleep spindles would greatly facilitate this analysis. Deep learning methods have been widely used recently in EEG analysis.

METHOD

We have developed a deep learning-based automated sleep spindle detection system, Deep-spindle, which employs a convolutional neural network (CNN) combined with a bidirectional Long Short-Term Memory (LSTM) network, which could assist in the analysis of infant sleep spindles. Deep-spindle was trained on the EEGs of ex-term infants to estimate the number and duration of sleep spindles. The ex-term EEG on channel F4-C4 was split into training (N=81) and validation (N=30) sets. An additional 30 ex-term EEG and 54 ex-preterm infant EEGs (channel F4-C4 and F3-C3) were used as an independent test set.

RESULT

Deep-spindle detected the number of sleep spindles with 91.9% to 96.5% sensitivity and 95.3% to 96.7% specificity, and estimated sleep spindle duration with a percent error of 13.1% to 19.1% in the independent test set. For each detected spindle event, the user is presented with amplitude, power spectral density and the spectrogram of the corresponding spindle EEG, and the probability of the event being a sleep spindle event, providing the user with insight into why the event is predicted as a sleep spindle to provide confidence in the predictions.

CONCLUSION

The Deep-spindle system can reduce physicians' workload, demonstrating the potential to assist physicians in the automated analysis of sleep spindles in infants.

Sleep Fosters Odor Recognition in Children with Attention Deficit Hyperactivity Disorder but Not in Typically Developing Children

Prior experience represents a prerequisite for memory consolidation across various memory systems. In the context of olfaction, sleep was found to enhance the consolidation of odors in adults but not in typically developing children (TDC), likely due to differences in pre-experience. Interestingly, unmedicated children with attention deficit hyperactivity disorder (ADHD), a neurodevelopmental condition related to dopamine dysfunction, showed lower perceptive thresholds for odors, potentially allowing for more odor experience compared to TDC. We investigated sleep-associated odor memory consolidation in ADHD. Twenty-eight children with ADHD and thirty age-matched TDC participated in an incidental odor recognition task. For the sleep groups (ADHD: n = 14, TDC: n = 15), the encoding of 10 target odorants took place in the evening, and the retention of odorants was tested with 10 target odorants and 10 distractor odorants the next morning. In the wake groups (ADHD: n = 14, TDC: n = 15), the time schedule was reversed. Odor memory consolidation was superior in the ADHD sleep group compared to the TDC sleep and the ADHD wake groups. Intensity and familiarity ratings during encoding were substantially higher in ADHD compared to TDC. Sleep-associated odor memory consolidation in ADHD is superior to TDC. Abundant pre-experience due to lower perceptive thresholds is suggested as a possible explanation. Olfaction might serve as a biomarker in ADHD.

Sleep EEG-Based Approach to Detect Mild Cognitive Impairment

Mild Cognitive Impairment (MCI) is an early stage of dementia, which may lead to Alzheimer's disease (AD) in older adults. Therefore, early detection of MCI and implementation of treatment and intervention can effectively slow down or even inhibit the progression of the disease, thus minimizing the risk of AD. Currently, we know that published work relies on an analysis of awake EEG recordings. However, recent studies have suggested that changes in the structure of sleep may lead to cognitive decline. In this work, we propose a sleep EEG-based method for MCI detection, extracting specific features of sleep to characterize neuroregulatory deficit emergent with MCI. This study analyzed the EEGs of 40 subjects (20 MCI, 20 HC) with the developed algorithm. We extracted sleep slow waves and spindles features, combined with spectral and complexity features from sleep EEG, and used the SVM classifier and GRU network to identify MCI. In addition, the classification results of different feature sets (including with sleep features from sleep EEG and without sleep features from awake EEG) and different classification methods were evaluated. Finally, the MCI classification accuracy of the GRU network based on features extracted from sleep EEG was the highest, reaching 93.46%. Experimental results show that compared with the awake EEG, sleep EEG can provide more useful information to distinguish between MCI and HC. This method can not only improve the classification performance but also facilitate the early intervention of AD.

Sleep Loss, Daytime Sleepiness, and Neurobehavioral Performance among Adolescents: A Field Study

The current study investigates the impact of sleep loss on neurobehavioral functioning and sleepiness in a natural setting among healthy adolescents. Fifty-nine adolescents (32 females) from grades 7 to 12 (mean age of 16.29 ± 1.86 years) participated in the study. All participants wore the actigraph for a continuous five to seven days, including school and nonschool days. Subjective sleepiness and neurobehavioral performance (using the psychomotor vigilance test and the digit symbol substitution test) were measured three times a day on two school days and one nonschool day. The results presented that sleep loss influenced subjective sleepiness reports, showing higher sleepiness scores following sleep loss than following sufficient night sleep. Neurobehavioral functioning across all measurements was also significantly worse following sleep loss. Furthermore, participants performed worse on weekday morning assessments than on assessments at other times of the day following sleep loss. These findings suggest that sleep loss in natural settings has a significant impact on neurobehavioral performance and subjective sleepiness. Our findings have essential implications for public policy on school schedules.

Sleep Power Topography in Children with Attention Deficit Hyperactivity Disorder (ADHD)

OBJECTIVE

Recent years saw an increasing interest towards sleep microstructure abnormalities in attention-deficit/hyperactivity disorder (ADHD). However, the existing literature on sleep electroencephalographic (EEG) power in ADHD is still controversial, often based on single electrode recordings, and mainly focused on slow wave activity (SWA) during NREM sleep. This study aimed to systematically investigate sleep power topography in all traditional frequency bands, in all sleep stages and across sleep cycles using high-density EEG (HD-EEG).

METHOD

Thirty drug-naïve children with ADHD (10.5 ± 2.1 years, 21 male) and 23 typically developing (TD) control participants (mean age: 10.2 ± 1.6 years, 13 male) were included in the current analysis. Signal power topography was computed in classical frequency bands during sleep, contrasted between groups and sleep cycles, and correlated with measures of ADHD severity, cognitive functioning and estimated total sleep time.

RESULTS

Compared to TD subjects, patients with ADHD consistently displayed a widespread increase in low-frequency activity (between 3 and 10 Hz) during NREM sleep, but not during REM sleep and wake before sleep onset. Such a difference involved a wide centro-posterior cluster of channels in the upper SWA range, in Theta, and low-Alpha. Between-group difference was maximal in sleep stage N3 in the first sleep cycle, and positively correlated with average total sleep time.

CONCLUSIONS

These results support the concept that children with ADHD, compared to TD peers, have a higher sleep pressure and altered sleep homeostasis, which possibly interfere with (and delay) cortical maturation.

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.

Sleep architecture and emotional inhibition processing in adolescents hospitalized during a suicidal crisis

BACKGROUND

Suicide is the second leading cause of death in adolescents. Sleep disturbances could alter inhibitory processes and contribute to dangerous behaviors in this critical developmental period. Adolescents in suicidal crisis have been shown to have lighter sleep compared to healthy controls. Additionally, suicidal adolescents have lower neural resources mobilized by emotionally charged inhibition processing. The present exploratory study aimed to determine how sleep architecture in suicidal adolescents may relate to inhibition processing in response to emotional stimuli.

METHODS

Ten adolescents between 12 and 17 years of age with a diagnosis of major depressive disorder and who attempted suicide were recruited while hospitalized for a suicidal crisis in a psychiatric inpatient unit. Event-related potentials (ERPs) were recorded prior to bedtime during a Go/NoGo task involving pictures of sad, happy, and neutral faces. Polysomnography was then recorded throughout the night. Pearson correlations were conducted to investigate how inhibition performance and ERP parameters reflecting inhibition processing (i.e., P3d and N2d derived from difference waveform calculated as NoGo minus Go trials) relate to sleep architecture.

RESULTS

Poorer inhibition accuracy in response to emotional stimuli was significantly correlated with shorter REM sleep latency, higher REM sleep, and more frequent nocturnal awakenings. The P3d in response to sad faces was negatively correlated with NREM2 sleep and positively correlated with NREM3 sleep. No such association with the P3d was found for happy or neutral stimuli. There were no significant correlations for the N2d.

CONCLUSION

Altered sleep in adolescents with depression who are in a suicidal crisisis associated with behavioral inhibition difficulties and fewer neural resources mobilized by inhibitory processes in emotionally charged contexts. This highlights the importance of addressing sleep disturbances while managing suicidal crises in adolescents.

Preschool sleep and depression interact to predict gray matter volume trajectories across late childhood to adolescence

There is a close relationship between sleep and depression, and certain maladaptive outcomes of sleep problems may only be apparent in individuals with heightened levels of depression. In a sample enriched for preschool depression, we examined how sleep and depression in early childhood interact to predict later trajectories of gray matter volume. Participants (N = 161) were recruited and assessed during preschool (ages 3–6 years) and were later assessed with five waves of structural brain imaging, spanning from late childhood to adolescence. Sleep and depression were assessed using a semi-structured parent interview when the children were preschool-aged, and total gray matter volume was calculated at each scan wave. Although sleep disturbances alone did not predict gray matter volume/trajectories, preschool sleep and depression symptoms interacted to predict later total gray matter volume and the trajectory of decline in total gray matter volume. Sleep disturbances in the form of longer sleep onset latencies, increased irregularity in the child’s sleep schedule, and higher levels of daytime sleepiness in early childhood were all found to interact with early childhood depression severity to predict later trajectories of cortical gray matter volume. Findings provide evidence of the interactive effects of preschool sleep and depression symptoms on later neurodevelopment.

Concordance between subjective and objective measures of infant sleep varies by age and maternal mood: Implications for studies of sleep and cognitive development

Infant habitual sleep has been proposed as an important moderator of development in domains such as attention, memory or temperament. To test such hypotheses, we need to know how to accurately and consistently assess habitual sleep in infancy. Common assessment methods include easy to deploy but subjective parent-report measures (diary/sleep questionnaire); or more labour-intensive but objective motor movement measures (actigraphy). Understanding the degree to which these methods provide converging insights is important, but cross-method agreement has yet to be investigated longitudinally. Moreover, it is unclear whether concordance systematically varies with infant or maternal characteristics that could represent confounders in observational studies. This longitudinal study (up to 4 study visits/participant) investigated cross-method concordance on one objective (7-day actigraphy) and three commonly used subjective (7-day sleep diary, Brief Infant Sleep Questionnaire, Sleep & Settle Questionnaire) sleep measures in 76 typically developing infants (age: 4–14 months) and assessed the impact of maternal characteristics (stress, age, education) and infant characteristics (age) on cross-method concordance. In addition, associations between objective and subjective sleep measures and a measure of general developmental status (Ages & Stages Questionnaire) were investigated. A range of equivalence analyses (tests of equivalence, correlational analyses, Bland-Altman plots) showed mixed agreement between sleep measures. Most importantly, cross-method agreement was associated with maternal stress levels and infant age. Specifically, agreement between different measures of night waking was better for mothers experiencing higher stress levels and was higher for younger than older infants; the reverse pattern was true for day sleep duration. Interestingly, objective and subjective measures did not yield the same patterns of association with developmental domains, indicating that sleep method choice can influence which associations are found between sleep and cognitive development. However, results converged across day sleep and problem-solving skills, highlighting the importance of studying day sleep in future studies. We discuss implications of sleep method choice for investigating sleep in the context of studying infant development and behaviour.

•

A range of equivalence analyses showed mixed agreement between subjective and objective sleep measures.

•

Cross-method agreement was associated with maternal stress levels and infant age.

•

Objective and subjective measures did not yield the same patterns of association with developmental domains except for day sleep duration.

Developmental features of sleep electrophysiology in family dogs

Age-related differences in dog sleep and the age at which dogs reach adulthood as indexed by sleep electrophysiology are unknown. We assessed, in (1) a Juvenile sample (n = 60) of 2-14-month-old dogs (weight range: 4-68 kg), associations between age, sleep macrostructure, and non-rapid eye movement (NREM) EEG power spectrum, whether weight moderates associations, and (2) an extended sample (n = 91) of 2-30-months-old dogs, when sleep parameters stabilise. In Juvenile dogs, age was positively associated with time in drowsiness between 2 and 8 months, and negatively with time in rapid eye movement (REM) sleep between 2 and 6 months. Age was negatively associated with delta and positively with theta and alpha power activity, between 8 and 14 months. Older dogs exhibited greater sigma and beta power activity. Larger, > 8-month-old dogs had less delta and more alpha and beta activity. In extended sample, descriptive data suggest age-related power spectrum differences do not stabilise by 14 months. Drowsiness, REM, and delta power findings are consistent with prior results. Sleep electrophysiology is a promising index of dog neurodevelopment; some parameters stabilise in adolescence and some later than one year. Determination of the effect of weight and timing of power spectrum stabilisation needs further inquiry. The dog central nervous system is not fully mature by 12 months of age.

Pediatric Sleep Apnea: The Overnight Electroencephalogram as a Phenotypic Biomarker

Pediatric obstructive sleep apnea (OSA) is a prevalent disorder that disrupts sleep and is associated with neurocognitive and behavioral negative consequences, potentially hampering the development of children for years. However, its relationships with sleep electroencephalogram (EEG) have been scarcely investigated. Here, our main objective was to characterize the overnight EEG of OSA-affected children and its putative relationships with polysomnographic measures and cognitive functions. A two-step analysis involving 294 children (176 controls, 57% males, age range: 5-9 years) was conducted for this purpose. First, the activity and irregularity of overnight EEG spectrum were characterized in the typical frequency bands by means of relative spectral power and spectral entropy, respectively: δ1 (0.1-2 Hz), δ2 (2-4 Hz), θ (4-8 Hz), α (8-13 Hz), σ (10-16 Hz), β1 (13-19 Hz), β2 (19-30 Hz), and γ (30-70 Hz). Then, a correlation network analysis was conducted to evaluate relationships between them, six polysomnography variables (apnea-hypopnea index, respiratory arousal index, spontaneous arousal index, overnight minimum blood oxygen saturation, wake time after sleep onset, and sleep efficiency), and six cognitive scores (differential ability scales, Peabody picture vocabulary test, expressive vocabulary test, design copying, phonological processing, and tower test). We found that as the severity of the disease increases, OSA broadly affects sleep EEG to the point that the information from the different frequency bands becomes more similar, regardless of activity or irregularity. EEG activity and irregularity information from the most severely affected children were significantly associated with polysomnographic variables, which were coherent with both micro and macro sleep disruptions. We hypothesize that the EEG changes caused by OSA could be related to the occurrence of respiratory-related arousals, as well as thalamic inhibition in the slow oscillation generation due to increases in arousal levels aimed at recovery from respiratory events. Furthermore, relationships between sleep EEG and cognitive scores emerged regarding language, visual-spatial processing, and executive function with pronounced associations found with EEG irregularity in δ1 (Peabody picture vocabulary test and expressive vocabulary test maximum absolute correlations 0.61 and 0.54) and β2 (phonological processing, 0.74; design copying, 0.65; and Tow 0.52). Our results show that overnight EEG informs both sleep alterations and cognitive effects of pediatric OSA. Moreover, EEG irregularity provides new information that complements and expands the classic EEG activity analysis. These findings lay the foundation for the use of sleep EEG to assess cognitive changes in pediatric OSA.

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.

Sex and Pubertal Differences in the Maturational Trajectories of Sleep Spindles in the Transition from Childhood to Adolescence: A Population-Based Study

Sleep spindles, bursts of electroencephalogram (EEG) activity in the σ-frequency (11–16 Hz) range, may be biomarkers of cortical development. Studies capturing the transition to adolescence are needed to delineate age-related, sex-related, and pubertal-related changes in sleep spindles at the population-level. We analyzed the sleep EEG of 572 subjects 6–21 years (48% female) and 332 subjects 5–12 years (46% female) followed-up at 12–22 years. From 6 to 21 years, spindle density (p quadratic = 0.019) and fast (12–16 Hz) spindle percent (p quadratic = 0.016) showed inverted U-shaped trajectories, with plateaus after 15 and 19 years, respectively. Spindle frequency increased (p linear < 0.001), while spindle power decreased (p linear < 0.001) from 6 to 21 years. The trajectories of spindle density, frequency, and fast spindle percent diverged between females and males, in whom density plateaued by 14 years, fast spindle percent by 16 years, and frequency by 18 years, while fast spindle percent and spindle frequency continued to increase until 21 years in females. Males experienced a longitudinal increase in spindle density 31% greater than females by 12–14 years (p = 0.006). Females experienced an increase in spindle frequency and fast spindle percent 2% and 41% greater, respectively, than males by 18–22 years (both p = 0.004), while males experienced a 14% greater decline in spindle power by 18–22 years (p = 0.018). Less mature adolescents (86% male) experienced a longitudinal increase in spindle density 36% greater than mature adolescents by 12–14 years (p = 0.002). Overall, males experience greater maturational changes in spindle density in the transition to adolescence, driven by later pubertal development, and sex differences become prominent in early adulthood when females have greater spindle power, frequency, and fast spindle percent.

Aperiodic sleep networks promote memory consolidation

Hierarchical synchronization of sleep oscillations establishes communication pathways to support memory reactivation, transfer, and consolidation. From an information-theoretical perspective, oscillations constitute highly structured network states that provide limited information-coding capacity. Recent findings indicate that sleep oscillations occur in transient bursts that are interleaved with aperiodic network states, which were previously considered to be random noise. We argue that aperiodic activity exhibits unique and variable spatiotemporal patterns, providing an ideal information-rich neurophysiological substrate for imprinting new mnemonic patterns onto existing circuits. We discuss novel avenues in conceptualizing and quantifying aperiodic network states during sleep to further understand their relevance and interplay with sleep oscillations in support of memory consolidation.

Altered Sleep-Related Consolidation and Neurocognitive Comorbidity in CECTS

Our aim is to use neurophysiological sleep-related consolidation (SRC) phenomena to identify putative pathophysiological mechanisms in CECTS linked to diffuse neurocognitive deficits. We argue that there are numerous studies on the association between seizure aspects and neurocognitive functioning but not as many on interictal variables and neurocognitive deficits. We suggest two additional foci. First, the interictal presentation in CECTS and second, neuronal oscillations involved in SRC processes. Existing data on mechanisms through which interictal epileptiform spikes (IES) impact upon SRC indicate that they have the potential to: (a) perturb cross-regional coupling of neuronal oscillations, (b) mimic consolidation processes, (c) alter the precision of the spatiotemporal coupling of oscillations, and (d) variably impact upon SRC performance. Sleep spindles merit systematic study in CECTS in order to clarify: (a) the state of the slow oscillations (SOs) with which they coordinate, (b) the precision of slow oscillation-spindle coupling, and (c) whether their developmental trajectories differ from those of healthy children. We subsequently review studies on the associations between IES load during NREM sleep and SRC performance in childhood epilepsy. We then use sleep consolidation neurophysiological processes and their interplay with IES to help clarify the diffuse neurocognitive deficits that have been empirically documented in CECTS. We claim that studying SRC in CECTS will help to clarify pathophysiological mechanisms toward diverse neurocognitive deficits. Future developments could include close links between the fields of epilepsy and sleep, as well as new therapeutic neurostimulation targets. At the clinical level, children diagnosed with CECTS could benefit from close monitoring with respect to epilepsy, sleep and neurocognitive functions.

EEG Patterns Prior to Motor Activations of Parasomnias: A Systematic Review

INTRODUCTION

Non-rapid eye movement (NREM) parasomnias are defined as abnormal nocturnal behaviors that typically arise from the NREM sleep stage 3 during the first sleep cycle. The polysomnographic studies showed an increase in sleep fragmentation and an atypical slow wave activity (SWA) in participants with NREM parasomnias compared to healthy controls. To date, the pathophysiology of NREM parasomnias is still poorly understood. The recent investigation of the EEG patterns immediately before parasomnia events could shed light on the motor activations' processes. This systematic review aims to summarize empirical evidence about these studies and provide an overview of the methodological issues.

METHODS

A systematic literature search was carried out in PubMed, Web of Science, and Scopus, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The documents obtained were evaluated using the Newcastle-Ottawa Scale (NOS).

RESULTS

Nine studies were included in the qualitative synthesis. The major evidence revealed an increased slow frequency EEG activity immediately before the motor activations in frontal and central areas and increased beta activity in the anterior cingulate cortices.

DISCUSSION

The investigation of EEG patterns before parasomniac episodes could provide new insight into the study of NREM parasomnia pathophysiology. The high- and low-frequency EEG increase before the episodes could represent a predictive electrophysiological pattern of the motor activations' onset. Overall, identifying specific sleep markers before parasomnias might also help differentiate between NREM parasomnias and other motor sleep disorders. Different methodological protocols should be integrated for overcoming the lack of consistent empirical findings. Thus, future studies should focus on the topographical examination of canonical EEG frequency bands to better understand spatial and time dynamics before the episodes and identify the networks underlying the onset of activations.

Maturational trajectories of non-rapid eye movement slow wave activity and odds ratio product in a population-based sample of youth

BACKGROUND

Brain maturation is reflected in the sleep electroencephalogram (EEG) by a decline in non-rapid eye movement (NREM) slow wave activity (SWA) throughout adolescence and a related decrease in sleep depth. However, this trajectory and its sex and pubertal differences lack replication in population-based samples. We tested age-related changes in SWA (0.4-4 Hz) power and odds ratio product (ORP), a standardized measure of sleep depth.

METHODS

We analyzed the sleep EEG of 572 subjects aged 6-21 y (48% female, 26% racial/ethnic minority) and 332 subjects 5-12 y followed-up at 12-22 y. Multivariable-adjusted analyses tested age-related cross-sectional and longitudinal trajectories of SWA and ORP.

RESULTS

SWA remained stable from age 6 to 10, decreased between ages 11 and 17, and plateaued from age 18 to 21 (p-cubic<0.001); females showed a longitudinal decline 23% greater than males by 13 y, while males experienced a steeper slope after 14 y and their longitudinal decline was 21% greater by 19 y. More mature adolescents (75% female) experienced a greater longitudinal decline in SWA than less mature adolescents by 14 y. ORP showed an age-related increasing trajectory (p-linear<0.001) with no sex or pubertal differences.

CONCLUSIONS

We provide population-level evidence for the maturational decline and sex and pubertal differences in SWA in the transition from childhood to adolescence, while introducing ORP as a novel metric in youth. Along with previous studies, the distinct trajectories observed suggest that age-related changes in SWA reflect brain maturation and local/synaptic processes during this developmental period, while those of ORP may reflect global/state control of NREM sleep depth.

Sleep-Based Interventions in Alzheimer's Disease: Promising Approaches from Prevention to Treatment along the Disease Trajectory

The multifactorial nature of Alzheimer’s disease (AD) has led scientific researchers to focus on the modifiable and treatable risk factors of AD. Sleep fits into this context, given the bidirectional relationship with AD confirmed by several studies over the last years. Sleep disorders appear at an early stage of AD and continue throughout the entire course of the pathology. Specifically, sleep abnormalities, such as more fragmented sleep, increase in time of awakenings, worsening of sleep quality and primary sleep disorders raise with the severity and progression of AD. Intervening on sleep, therefore, means acting both with prevention strategies in the pre-clinical phase and with treatments during the course of the disease. This review explores sleep disturbances in the different stages of AD, starting from the pre-clinical stage. Particular attention is given to the empirical evidence investigating obstructive sleep apnea (OSA) disorder and the mechanisms overlapping and sharing with AD. Next, we discuss sleep-based intervention strategies in the healthy elderly population, mild cognitive impairment (MCI) and AD patients. We mention interventions related to behavioral strategies, combination therapies, and bright light therapy, leaving extensive space for new and raising evidence on continuous positive air pressure (CPAP) treatment effectiveness. Finally, we clarify the role of NREM sleep across the AD trajectory and consider the most recent studies based on the promising results of NREM sleep enhancement, which use innovative experimental designs and techniques.

Aerobic fitness and the sleeping brain of adolescents-a pilot study

STUDY OBJECTIVES

Aerobic fitness (AF) and sleep are major determinants of health in adolescents and impact neurocognitive and psychological development. However, little is known about the interactions between AF and sleep during the developmental transition experienced across adolescence. This study aimed to consider the relationships between AF and habitual sleep patterns and sleep neurophysiology in healthy adolescents.

METHODS

Subjects (mean age = 14.6 ± 2.3 years old, range 11-17, 11 females) were evaluated for AF (peak VO2 assessed by ramp-type progressive cycle ergometry in the laboratory), habitual sleep duration and efficiency (7-14 days actigraphy), and topographic patterns of spectral power in slow wave, theta, and sleep spindle frequencies in non-rapid eye movement (NREM) sleep using overnight polysomnography (PSG) with high-density electroencephalography (hdEEG, 128 channels).

RESULTS

Significant relationships were observed between peak VO2 and habitual bedtime (r = -0.650, p = .009) and wake-up time (r = -0.603, p = .017), with greater fitness associated with going to bed and waking up earlier. Peak VO2 significantly predicted slow oscillations (0.5-1 Hz, p = .018) and theta activity (4.5-7.5 Hz, p = .002) over anterior frontal and central derivations (p < .001 and p = .001, respectively) after adjusting for sex and pubertal development stage. Similar associations were detected for fast sleep spindle activity (13-16 Hz, p = .006), which was greater over temporo-parietal derivations.

CONCLUSIONS

Greater AF was associated with a more mature pattern of topographically-specific features of sleep EEG known to support neuroplasticity and cognitive processes and which are dependent on prefrontal cortex and hippocampal function in adolescents and adults. AF was also correlated with a smaller behavioral sleep phase delay commonly seen during adolescence.

HIV Increases Sleep-based Brain Age Despite Antiretroviral Therapy

STUDY OBJECTIVES

Age-related comorbidities and immune activation raise concern for advanced brain aging in people living with HIV (PLWH). The brain age index (BAI) is a machine learning model that quantifies deviations in brain activity during sleep relative to healthy individuals of the same age. High BAI was previously found to be associated with neurological, psychiatric, cardiometabolic diseases, and reduced life expectancy among people without HIV. Here, we estimated the effect of HIV infection on BAI by comparing PLWH and HIV-controls.

METHODS

Clinical data and sleep EEGs from 43 PLWH on antiretroviral therapy (HIV+) and 3,155 controls (HIV-) were collected from Massachusetts General Hospital. The effect of HIV infection on BAI, and on individual EEG features, was estimated using causal inference.

RESULTS

The average effect of HIV on BAI was estimated to be +3.35 years (p < 0.01, 95% CI = [0.67, 5.92]) using doubly robust estimation. Compared to HIV- controls, HIV+ participants exhibited a reduction in delta band power during deep sleep and rapid eye movement sleep.

CONCLUSION

We provide causal evidence that HIV contributes to advanced brain aging reflected in sleep EEG. A better understanding is greatly needed of potential therapeutic targets to mitigate the effect of HIV on brain health, potentially including sleep disorders and cardiovascular disease.

Sleep-Related Declarative Memory Consolidation in Children and Adolescents with Developmental Dyslexia

Sleep has a crucial role in memory processes, and maturational changes in sleep electrophysiology are involved in cognitive development. Albeit both sleep and memory alterations have been observed in Developmental Dyslexia (DD), their relation in this population has been scarcely investigated, particularly concerning topographical aspects. The study aimed to compare sleep topography and associated sleep-related declarative memory consolidation in participants with DD and normal readers (NR). Eleven participants with DD and 18 NR (9–14 years old) underwent a whole-night polysomnography. They were administered a word pair task before and after sleep to assess for declarative memory consolidation. Memory performance and sleep features (macro and microstructural) were compared between the groups, and the intercorrelations between consolidation rate and sleep measures were assessed. DD showed a deeper worsening in memory after sleep compared to NR and reduced slow spindles in occipito-parietal and left fronto-central areas. Our results suggest specific alterations in local sleep EEG (i.e., sleep spindles) and in sleep-dependent memory consolidation processes in DD. We highlight the importance of a topographical approach, which might shed light on potential alteration in regional cortical oscillation dynamics in DD. The latter might represent a target for therapeutic interventions aimed at enhancing cognitive functioning in DD.

Presence of Allergies and Their Impact on Sleep in Children Who Stutter

Purpose

Population-based research has identified insomnia or trouble sleeping, sleepiness during the day, and fatigue during the day as frequent coexisting conditions in children who stutter (CWS). Considering that allergies are well known to disturb sleep, the purpose of this study was to explore if there is an association between the presence of allergies and sleep issues among CWS, as well as if allergies are frequent in CWS.

Method

Data from the 2012 National Health Interview Survey were used. Children used in this sample were those whose caregivers answered definitively whether or not the child stuttered within the past 12 months. Additionally, caregivers identified the presence of allergies and/or asthma and the presence of insomnia or trouble sleeping in the sample child.

Results

The sample included 200 CWS and 9,951 children who do not stutter (CWNS). The odds of insomnia/trouble sleeping were greater in CWS who present with allergies and/or asthma, with the exception of food allergy, compared to CWS who do not present with with allergies and/or asthma. Additionally, the odds of insomnia/trouble sleeping were greater in CWS without any allergy, asthma, and coexisting disability ( OR = 7.48, p < .001) as compared to CWNS without any allergy, asthma, and coexisting disability. The presence of either any allergy or an asthma attack was higher among CWS (46.4%) compared to CWNS (29.5%), p < .001. Specifically, CWS were found to be at greater odds of presenting with any kind of respiratory allergy ( OR = 1.72, p = .034), food allergy ( OR = 2.32, p = .002), and skin allergy ( OR = 1.84, p = .009) than CWNS.

Conclusions

CWS were found to be at greater odds of allergies and asthma, conditions that also impair sleep. Interestingly, insomnia/trouble sleeping was prevalent among CWS, even when allergies, asthma, and coexisting disabilities were not present. The possible implications of these findings are discussed.

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

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

Advances in Understanding the Relationship between Sleep and Attention Deficit-Hyperactivity Disorder (ADHD)

Starting from the consolidated relationship between sleep and cognition, we reviewed the available literature on the association between Attention Deficit-Hyperactivity Disorder (ADHD) and sleep. This review analyzes the macrostructural and microstructural sleep features, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses criteria (PRISMA). We included the polysomnographic studies published in the last 15 years. The results of macrostructural parameters are mixed. Almost half of the 18 selected investigations did not find differences between sleep architecture of children with ADHD and controls. Five studies observed that children with ADHD show a longer Rapid Eye Movement (REM) sleep duration than controls. Eight studies included microstructural measures. Remarkable alterations in sleep microstructure of ADHD are related to slow wave activity (SWA) and theta oscillations, respectively, during Non-REM (NREM) and REM sleep. Specifically, some studies found higher SWA in the ADHD group than controls. Similarly, higher theta activity appears to be detrimental for memory performance and inhibitory control in ADHD. These patterns could be interpreted as a maturational delay in ADHD. Also, the increased amount of these activities would be consistent with the hypothesis that the poor sleep could imply a chronic sleep deprivation in children with ADHD, which in turn could affect their cognitive functioning.

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.