Sleep Spindle Characteristics in Children with Neurodevelopmental Disorders and Their Relation to Cognition

Spindle chirp and other sleep oscillatory features in young children with autism

OBJECTIVES

To determine whether spindle chirp and other sleep oscillatory features differ in young children with and without autism.

METHODS

Automated processing software was used to re-assess an extant set of polysomnograms representing 121 children (91 with autism [ASD], 30 typically-developing [TD]), with an age range of 1.35-8.23 years. Spindle metrics, including chirp, and slow oscillation (SO) characteristics were compared between groups. SO and fast and slow spindle (FS, SS) interactions were also investigated. Secondary analyses were performed assessing behavioural data associations, as well as exploratory cohort comparisons to children with non-autism developmental delay (DD).

RESULTS

Posterior FS and SS chirp was significantly more negative in ASD than TD. Both groups had comparable intra-spindle frequency range and variance. Frontal and central SO amplitude were decreased in ASD. In contrast to previous manual findings, no differences were detected in other spindle or SO metrics. The ASD group displayed a higher parietal coupling angle. No differences were observed in phase-frequency coupling. The DD group demonstrated lower FS chirp and higher coupling angle than TD. Parietal SS chirp was positively associated with full developmental quotient.

CONCLUSIONS

For the first time spindle chirp was investigated in autism and was found to be significantly more negative than in TD in this large cohort of young children. This finding strengthens previous reports of spindle and SO abnormalities in ASD. Further investigation of spindle chirp in healthy and clinical populations across development will help elucidate the significance of this difference and better understand this novel metric.

A Thalamocortical Perspective on Sleep Spindle Alterations in Neurodevelopmental Disorders

Purpose of Review

Neurodevelopmental disorders are a group of conditions that affect the development and function of the nervous system, typically arising early in life. These disorders can have various genetic, environmental, and/or neural underpinnings, which can impact the thalamocortical system. Sleep spindles, brief bursts of oscillatory activity that occur during NREM sleep, provide a unique in vivo measure of the thalamocortical system. In this manuscript, we review the development of the thalamocortical system and sleep spindles in rodent models and humans. We then utilize this as a foundation to discuss alterations in sleep spindle activity in four of the most pervasive neurodevelopmental disorders-intellectual disability, attention deficit hyperactivity disorder, autism, and schizophrenia.

Recent Findings

Recent work in humans has shown alterations in sleep spindles across several neurodevelopmental disorders. Simultaneously, rodent models have elucidated the mechanisms which may underlie these deficits in spindle activity. This review merges recent findings from these two separate lines of research to draw conclusions about the pathogenesis of neurodevelopmental disorders.

Summary

We speculate that deficits in the thalamocortical system associated with neurodevelopmental disorders are exquisitely reflected in sleep spindle activity. We propose that sleep spindles may represent a promising biomarker for drug discovery, risk stratification, and treatment monitoring.

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.

Blindness affects the developmental trajectory of the sleeping brain

Sleep plays a crucial role in brain development, sensory information processing, and consolidation. Sleep spindles are markers of these mechanisms as they mirror the activity of the thalamocortical circuits. Spindles can be subdivided into two groups, slow (10-13 Hz) and fast (13-16 Hz), which are each associated with different functions. Specifically, fast spindles oscillate in the high-sigma band and are associated with sensorimotor processing, which is affected by visual deprivation. However, how blindness influences spindle development has not yet been investigated. We recorded nap video-EEG of 50 blind/severely visually impaired (BSI) and 64 sighted children aged 5 months to 6 years old. We considered aspects of both macro- and micro-structural spindles. The BSI children lacked the evolution of developmental spindles within the central area. Specifically, young BSI children presented low central high-sigma and high-beta (25-30 Hz) event-related spectral perturbation and showed no signs of maturational decrease. High-sigma and high-beta activity in the BSI group correlated with clinical indices predicting perceptual and motor disorders. Our findings suggest that fast spindles are pivotal biomarkers for identifying an early developmental deviation in BSI children. These findings are critical for initial therapeutic intervention.

New Electrographic Marker? Evaluation of Sleep Spindles in Children with Attention Deficit Hyperactivity Disorder

Introduction: Attention deficit and hyperactivity disorder (ADHD) is one of the most common developmental disorders in childhood which lasts lifelong. Sleep structure and sleep spindle features are disorganized in ADHD. In this study, we aimed to look for a new, simple, inexpensive, and an easily detectable electrographic marker in the diagnosis of ADHD by using electroencephalography (EEG). Method: We included treatment free 35 patients with ADHD and 32 healthy children (HC) who were examined by polysomnography (PSG) and EEG for sleep disorders. The ADHD group were separated into three groups according to predominant presentations of ADHD. We determined the sleep staging and slow and fast sleep spindles, calculated each spindle's amplitude, frequency, activity, duration and density at non rapid eye movement (REM) sleep stage 2. Results: Slow sleep spindle's amplitude, duration, density and activity are significantly higher in ADHD group (most significant in ADHD-I) than the HC group (p < 0,05). Sleep spindle's features are not statistically significant between in ADHD subgroups. Conclusions: In children with ADHD, slow sleep spindles showed higher amplitude, activity, density and duration in the frontal regions. These results indicate that slow sleep spindles in children with ADHD may reflect executive dysfunction and slow frontal spindles may be useful as a new electrographic marker in children with ADHD. This is the first study of its kind evaluating all aspects of sleep spindles in ADHD patients.

Age-Dependent Electroencephalogram Features in Infants Under Spinal Anesthesia Appear to Mirror Physiologic Sleep in the Developing Brain: A Prospective Observational Study

BACKGROUND

Infants under spinal anesthesia appear to be sedated despite the absence of systemic sedative medications. In this prospective observational study, we investigated the electroencephalogram (EEG) of infants under spinal anesthesia and hypothesized that we would observe EEG features similar to those seen during sleep.

METHODS

We computed the EEG power spectra and spectrograms of 34 infants undergoing infraumbilical surgeries under spinal anesthesia (median age 11.5 weeks postmenstrual age, range 38-65 weeks postmenstrual age). Spectrograms were visually scored for episodes of EEG discontinuity or spindle activity. We characterized the relationship between EEG discontinuity or spindles and gestational age, postmenstrual age, or chronological age using logistic regression analyses.

RESULTS

The predominant EEG patterns observed in infants under spinal anesthesia were slow oscillations, spindles, and EEG discontinuities. The presence of spindles, observed starting at about 49 weeks postmenstrual age, was best described by postmenstrual age ( P =.002) and was more likely with increasing postmenstrual age. The presence of EEG discontinuities, best described by gestational age ( P = .015), was more likely with decreasing gestational age. These age-related changes in the presence of spindles and EEG discontinuities in infants under spinal anesthesia generally corresponded to developmental changes in the sleep EEG.

CONCLUSIONS

This work illustrates 2 separate key age-dependent transitions in EEG dynamics during infant spinal anesthesia that may reflect the maturation of underlying brain circuits: (1) diminishing discontinuities with increasing gestational age and (2) the appearance of spindles with increasing postmenstrual age. The similarity of these age-dependent transitions under spinal anesthesia with transitions in the developing brain during physiological sleep supports a sleep-related mechanism for the apparent sedation observed during infant spinal anesthesia.

Altered sleep architecture in children and adolescents with Down syndrome

OBJECTIVE

Children with Down syndrome (DS) may experience changes in sleep architecture (i.e., different sleep stages) that then affect waketime functioning, including learning, mood, and disruptive behavior. For designing and testing interventions, it is important to document any differences in sleep architecture in children with DS with and without co-occurring diagnoses, including neuropsychiatric diagnoses and obstructive sleep apnea (OSA).

METHODS

A retrospective cohort study was performed at Massachusetts General Hospital for children and adolescents with DS who underwent polysomnography (PSG) between August 2016 and July 2022. Patient data collected from the electronic medical record included diagnoses, age at PSG, and PSG report. Statistical analysis included unpaired T tests to test hypotheses about differences in sleep architecture within age groups, and differences between children with DS and a co-occurring diagnosis. One way ANOVA was used to determine statistical significance of OSA severity within patients with DS.

RESULTS

When compared by age group, those with DS had negative changes in sleep architecture (e.g., less sleep and more wake) when compared to normative data. Within this cohort, having a co-occurring diagnosis of autism resulted in further, negative effects on sleep architecture. 89% of those with DS had diagnosed OSA but only those with severe OSA experienced negative effects on sleep architecture.

CONCLUSION

Age is an important covariate when studying the sleep of children with DS and neurotypical children. Studies are needed to test whether minimizing the observed differences in sleep architecture will translate to improved learning, mood, and behavioral outcomes, and how treating OSA affects sleep architecture.

Spindle Chirp and other Sleep Oscillatory Features in Young Children with Autism

Objectives

To determine whether spindle chirp and other sleep oscillatory features differ in young children with and without autism.

Methods

Automated processing software was used to re-assess an extant set of polysomnograms representing 121 children (91 with autism [ASD], 30 typically-developing [TD]), with an age range of 1.35-8.23 years. Spindle metrics, including chirp, and slow oscillation (SO) characteristics were compared between groups. SO and fast and slow spindle (FS, SS) interactions were also investigated. Secondary analyses were performed assessing behavioural data associations, as well as exploratory cohort comparisons to children with non-autism developmental delay (DD).

Results

Posterior FS and SS chirp was significantly more negative in ASD than TD. Both groups had comparable intra-spindle frequency range and variance. Frontal and central SO amplitude were decreased in ASD. In contrast to previous manual findings, no differences were detected in other spindle or SO metrics. The ASD group displayed a higher parietal coupling angle. No differences were observed in phase-frequency coupling. The DD group demonstrated lower FS chirp and higher coupling angle than TD. Parietal SS chirp was positively associated with full developmental quotient.

Conclusions

For the first time spindle chirp was investigated in autism and was found to be significantly more negative than in TD in this large cohort of young children. This finding strengthens previous reports of spindle and SO abnormalities in ASD. Further investigation of spindle chirp in healthy and clinical populations across development will help elucidate the significance of this difference and better understand this novel metric.

Sleep spindles are reduced in children with Down syndrome and sleep-disordered breathing

BACKGROUND

Children with Down syndrome (DS) are at increased risk of sleep-disordered breathing (SDB). We investigated sleep spindle activity, as a marker of sleep quality, and its relationship with daytime functioning in children with DS compared to typically developing (TD) children.

METHODS

Children with DS and SDB (n = 44) and TD children matched for age, sex and SDB severity underwent overnight polysomnography. Fast or Slow sleep spindles were identified manually during N2/N3 sleep. Spindle activity was characterized as spindle number, density (number of spindles/h) and intensity (density × average duration) on central (C) and frontal (F) electrodes. Parents completed the Child Behavior Check List and OSA-18 questionnaires.

RESULTS

In children with DS, spindle activity was lower compared to TD children for F Slow and F Slow&Fast spindles combined (p < 0.001 for all). Furthermore, there were no correlations between spindle activity and CBCL subscales; however, spindle activity for C Fast and C Slow&Fast was negatively correlated with OSA-18 emotional symptoms and caregiver concerns and C Fast activity was also negatively correlated with daytime function and total problems.

CONCLUSIONS

Reduced spindle activity in children with DS may underpin the increased sleep disruption and negative effects of SDB on quality of life and behavior.

IMPACT

Children with Down syndrome (DS) are at increased risk of sleep-disordered breathing (SDB), which is associated with sleep disruption affecting daytime functioning. Sleep spindles are a sensitive marker of sleep quality. We identified for the first time that children with DS had reduced sleep spindle activity compared to typically developing children matched for SDB severity. The reduced spindle activity likely underpins the more disrupted sleep and may be associated with reduced daytime functioning and quality of life and may also be an early biomarker for an increased risk of developing dementia later in life in children with DS.

Restless Legs Syndrome and Restless Sleep Disorder in Children

Restless legs syndrome (RLS) affects 2% of children presenting with symptoms of insomnia, restless sleep, decreased quality of life, and effects on cognition and behavior. The International RLS Study Group and the American Academy of Sleep Medicine have published guidelines for the diagnosis and treatment of RLS in children. Restless sleep disorder has been recently identified in children and presents with frequent movements during sleep and daytime symptoms with polysomnography findings of at least 5 large muscle movements at night. Treatment options for both disorders include iron supplementation, either oral or intravenous with improvement in nighttime and daytime symptoms.

Sleep Architecture and EEG Power Spectrum Following Cumulative Sleep Restriction: A Comparison between Typically Developing Children and Children with ADHD

No studies have looked at the effects of cumulative sleep restriction (CSR) on sleep architecture or the power spectrum of sleep EEG (electroencephalogram) in school-age children, as recorded by PSG (polysomnography). This is true for both typically developing (TD) children and children with ADHD (attention deficit/hyperactivity disorder), who are known to have more sleep difficulties. Participants were children (ages 6-12 years), including 18 TD and 18 ADHD, who were age- and sex-matched. The CSR protocol included a two-week baseline and two randomized conditions: Typical (six nights of sleep based on baseline sleep schedules) and Restricted (one-hour reduction of baseline time in bed). This resulted in an average of 28 min per night difference in sleep. Based on ANOVAs (analysis of variance), children with ADHD took longer to reach N3 (non-rapid eye movement), had more WASO (wake after sleep onset) (within the first 5.1 h of the night), and had more REM (rapid eye movement) sleep than TD children regardless of condition. During CSR, ADHD participants had less REM and a trend toward longer durations of N1 and N2 compared to the TD group. No significant differences in the power spectrum were found between groups or conditions. In conclusion, this CSR protocol impacted some physiological aspects of sleep but may not be sufficient to cause changes in the power spectrum of sleep EEG. Although preliminary, group-by-condition interactions suggest that the homeostatic processes in children with ADHD may be impaired during CSR.

A comparative analysis of sleep spindle characteristics of sleep-disordered patients and normal subjects

Spindles differ in density, amplitude, and frequency, and these variations reflect different physiological processes. Sleep disorders are characterized by difficulty in falling asleep and maintaining sleep. In this study, we proposed a new spindle wave detection algorithm, which was more effective compared with traditional detection algorithms such as wavelet algorithm. Besides, we recorded EEG data from 20 subjects with sleep disorders and 10 normal subjects, and then we compared the spindle characteristics of sleep-disordered subjects and normal subjects (those without any sleep disorder) to assess the spindle activity during human sleep. Specifically, we scored 30 subjects on the Pittsburgh Sleep Quality Index and then analyzed the association between their sleep quality scores and spindle characteristics, reflecting the effect of sleep disorders on spindle characteristics. We found a significant correlation between the sleep quality score and spindle density (p = 1.84 × 10−8, p-value &lt;0.05 was considered statistically significant.). We, therefore, concluded that the higher the spindle density, the better the sleep quality. The correlation analysis between the sleep quality score and mean frequency of spindles yielded a p-value of 0.667, suggesting that the spindle frequency and sleep quality score were not significantly correlated. The p-value between the sleep quality score and spindle amplitude was 1.33 × 10−4, indicating that the mean amplitude of the spindle decreases as the score increases, and the mean spindle amplitude is generally slightly higher in the normal population than in the sleep-disordered population. The normal and sleep-disordered groups did not show obvious differences in the number of spindles between symmetric channels C3/C4 and F3/F4. The difference in the density and amplitude of the spindles proposed in this paper can be a reference characteristic for the diagnosis of sleep disorders and provide valuable objective evidence for clinical diagnosis. In summary, our proposed detection method can effectively improve the accuracy of sleep spindle wave detection with stable performance. Meanwhile, our study shows that the spindle density, frequency and amplitude are different between the sleep-disordered and normal populations.

Thalamic control of sensory processing and spindles in a biophysical somatosensory thalamoreticular circuit model of wakefulness and sleep

Thalamoreticular circuitry plays a key role in arousal, attention, cognition, and sleep spindles, and is linked to several brain disorders. A detailed computational model of mouse somatosensory thalamus and thalamic reticular nucleus has been developed to capture the properties of over 14,000 neurons connected by 6 million synapses. The model recreates the biological connectivity of these neurons, and simulations of the model reproduce multiple experimental findings in different brain states. The model shows that inhibitory rebound produces frequency-selective enhancement of thalamic responses during wakefulness. We find that thalamic interactions are responsible for the characteristic waxing and waning of spindle oscillations. In addition, we find that changes in thalamic excitability control spindle frequency and their incidence. The model is made openly available to provide a new tool for studying the function and dysfunction of the thalamoreticular circuitry in various brain states.

Childhood absence epilepsy patients with cognitive impairment have decreased sleep spindle density

OBJECTIVE

To explore the differences in sleep spindle (SS) characteristics during stage N2 sleep between children with childhood absence epilepsy and healthy controls, and between children with childhood absence epilepsy with or without cognitive impairment.

METHODS

We recruited 29 children (14 females, 15 males, mean age: 8 (2.5) years) with childhood absence epilepsy who did not undergone antiseizure treatments previously and 30 age-matched controls (14 females, 16 males, mean age: 9 (3.0) years). For all patients, data on medical history were collected. Each child was monitored overnight by long-term video electroencephalography and was evaluated by the Wechsler Intelligence Scale for Children-Fourth Edition. Next, we compared anterior SS characteristics, including density, frequency, cycle length, duration, amplitude, and percentage of sleep stages.

RESULTS

The childhood absence epilepsy group exhibited lower spindle density and duration in the first 37.5 min of stage N2 sleep than the control group (P < 0.01). A decrease in spindle density could be observed in the childhood absence epilepsy group with aggravated cognition impairment. The spindle density was substantially lower in the cognitively impaired group than in the cognitively unimpaired group (P < 0.01). No significant differences were observed in SS amplitude, SS frequency, SS cycle length, and the distribution of sleep stages.

CONCLUSIONS

Reduction in spindle density and duration is associated with the mechanisms underlying childhood absence epilepsy. The deficit in SS density is related with impaired cognition. This deficiency in SSs may be a useful predictive indicator of cognitive impairment in children with absence epilepsy, indicating that SSs may become a useful biomarker and potential adjuvant anti-seizure target for cognitive impairment caused by childhood absence epilepsy.

The effects of sleep disordered breathing on sleep spindle activity in children and the relationship with sleep, behavior and neurocognition

STUDY OBJECTIVES

Obstructive sleep disordered breathing (SDB), has adverse neurocognitive and behavioral sequelae in children, despite conventional measures of sleep disruption being unaffected. There is growing evidence that sleep spindles may serve as a more sensitive marker of sleep quality. We investigated the relationship between sleep spindles and sleep fragmentation and neurocognition across the spectrum of SDB severity in children.

METHODS

Children 3-12 years old referred for clinical assessment of SDB and age matched control children from the community were recruited and underwent polysomnography. Sleep spindles were identified manually during N2 and N3 sleep. Spindle activity was characterised as spindle number, density (number of spindles/h) and intensity (spindle density x average spindle duration). Children completed a battery of tests assessing global intellectual ability, language, attention, visuospatial ability, sensorimotor skills, adaptive behaviors and skills and problem behaviors and emotional difficulties.

RESULTS

Children were grouped into control, Primary Snoring, Mild OSA and Moderate/severe OSA, N = 10/group. All measures of spindle activity were lower in the SDB groups compared to the Control children and this reached statistical significance for Mild OSA (p < 0.05 for all). Higher spindle indices were associated with better performance on executive function and visual ability assessments but poorer performance on auditory attention and communication skills. Higher spindle indices were associated with better behavior.

CONCLUSION

The reduced spindle activity observed in the children with SDB, particularly Mild OSA, indicates that sleep micro-architecture is disrupted and that this disruption may underpin the negative effects of SDB on attention, learning and memory.

Restless Sleep Disorder (RSD): a New Sleep Disorder in Children. A Rapid Review

PURPOSE OF REVIEW

Restless sleep disorder (RSD) is a recently identified pediatric sleep disorder characterized by frequent movements during sleep associated with daytime symptoms. In this review we summarize the expanding evidence of the clinical presentation of RSD, potential pathophysiology, associated comorbidities, and current treatment options that will help the pediatrician identify children with RSD in a timely manner.

RECENT FINDINGS

RSD is diagnosed in 7.7% of children referred evaluated in a pediatric sleep center. Children with RSD present with frequent nightly movements during sleep for at least 3 months, and have daytime symptoms related to poor sleep quality including excessive sleepiness, hyperactivity, irritability among other symptoms. Current evidence shows an increased sympathetic predominance, increased NREM sleep instability, and iron deficiency, as well as increased prevalence in parasomnias and attention deficit hyperactivity disorder. Consensus diagnostic criteria were recently published to diagnose RSD and emergent evidence suggests that iron supplementation improves its nighttime and daytime symptoms.

Convergent validity of the child behavior checklist sleep items in children with moderate to severe traumatic brain injury

AIM

The Child Behavior Checklist (CBCL) includes several sleep items. We aimed to examine the convergent validity of CBCL sleep scores with validated sleep measures, and to explore their functional correlates.

METHODS

This cross-sectional study included 44 children with moderate to severe TBI, aged 6-15 years. Parents completed the CBCL and Sleep Disturbance Scale for Children (SDSC), and children wore actigraphy watches.

RESULTS

We found significant, albeit differential, associations between CBCL and SDSC sleep scores. Specifically: (i) "trouble sleeping" with SDSC total score, (ii) "trouble sleeping" and "nightmares" with SDSC initiating and maintaining sleep, (iii) "talks/walks in sleep" with SDSC arousal, and (iv) "overtired," "sleeps more" and CBCL sleep composite with SDSC excessive somnolence. The CBCL item "sleeps less" was the only significant predictor of functioning; children who slept less had lower social competence. No associations were found between CBCL sleep scores and actigraphy.

CONCLUSIONS

The CBCL does not provide a comprehensive assessment of sleep disturbances in children with moderate to severe TBI. Nevertheless, certain CBCL sleep items demonstrate initial convergent validity with subscales of the SDSC assessing select types of sleep disturbances. The CBCL may be useful in research and clinical situations when administration of more comprehensive assessment sleep tools is not viable.

Evaluation of electroencephalography biomarkers for Angelman syndrome during overnight sleep

Angelman syndrome (AS) is a neurodevelopmental disorder caused by loss‐of‐function mutations in the maternal copy of the UBE3A gene. AS is characterized by intellectual disability, impaired speech and motor skills, epilepsy, and sleep disruptions. Multiple treatment strategies to re‐express functional neuronal UBE3A from the dormant paternal allele were successful in rodent models of AS and have now moved to early phase clinical trials in children. Developing reliable and objective AS biomarkers is essential to guide the design and execution of current and future clinical trials. Our prior work quantified short daytime electroencephalograms (EEGs) to define promising biomarkers for AS. Here, we asked whether overnight sleep is better suited to detect AS EEG biomarkers. We retrospectively analyzed EEGs from 12 overnight sleep studies from individuals with AS with age and sex‐matched Down syndrome and neurotypical controls, focusing on low frequency (2–4 Hz) delta rhythms and sleep spindles. Delta EEG rhythms were increased in individuals with AS during all stages of overnight sleep, but overnight sleep did not provide additional benefit over wake in the ability to detect increased delta. Abnormal sleep spindles were not reliably detected in EEGs from individuals with AS during overnight sleep, suggesting that delta rhythms represent a more reliable biomarker. Overall, we conclude that periods of wakefulness are sufficient, and perhaps ideal, to quantify delta EEG rhythms for use as AS biomarkers.

Source EEG reveals that Rolandic epilepsy is a regional epileptic encephalopathy

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Children with RE have fewer spindles but they have typical time–frequency features.

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Spindle deficits extend to multiple cortical regions in Rolandic epilepsy.

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Cognitive deficits are predicted by spindle rate in Rolandic epilepsy.

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Regional spindle rate predicts motor deficits better than Rolandic spindle deficit.

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Spindle features in RE identify a regional thalamocortical epileptic encephalopathy.

Rolandic epilepsy is the most common form of epileptic encephalopathy, characterized by sleep-potentiated inferior Rolandic epileptiform spikes, seizures, and cognitive deficits in school-age children that spontaneously resolve by adolescence. We recently identified a paucity of sleep spindles, physiological thalamocortical rhythms associated with sleep-dependent learning, in the Rolandic cortex during the active phase of this disease. Because spindles are generated in the thalamus and amplified through regional thalamocortical circuits, we hypothesized that: 1) deficits in spindle rate would involve but extend beyond the inferior Rolandic cortex in active epilepsy and 2) regional spindle deficits would better predict cognitive function than inferior Rolandic spindle deficits alone. To test these hypotheses, we obtained high-resolution MRI, high-density EEG recordings, and focused neuropsychological assessments in children with Rolandic epilepsy during active (n = 8, age 9–14.7 years, 3F) and resolved (seizure free for > 1 year, n = 10, age 10.3–16.7 years, 1F) stages of disease and age-matched controls (n = 8, age 8.9–14.5 years, 5F). Using a validated spindle detector applied to estimates of electrical source activity in 31 cortical regions, including the inferior Rolandic cortex, during stages 2 and 3 of non-rapid eye movement sleep, we compared spindle rates in each cortical region across groups. Among detected spindles, we compared spindle features (power, duration, coherence, bilateral synchrony) between groups. We then used regression models to examine the relationship between spindle rate and cognitive function (fine motor dexterity, phonological processing, attention, and intelligence, and a global measure of all functions). We found that spindle rate was reduced in the inferior Rolandic cortices in active but not resolved disease (active P = 0.007; resolved P = 0.2) compared to controls. Spindles in this region were less synchronous between hemispheres in the active group (P = 0.005; resolved P = 0.1) compared to controls; but there were no differences in spindle power, duration, or coherence between groups. Compared to controls, spindle rate in the active group was also reduced in the prefrontal, insular, superior temporal, and posterior parietal regions (i.e., “regional spindle rate”, P < 0.039 for all). Independent of group, regional spindle rate positively correlated with fine motor dexterity (P < 1e-3), attention (P = 0.02), intelligence (P = 0.04), and global cognitive performance (P < 1e-4). Compared to the inferior Rolandic spindle rate alone, models including regional spindle rate trended to improve prediction of global cognitive performance (P = 0.052), and markedly improved prediction of fine motor dexterity (P = 0.006). These results identify a spindle disruption in Rolandic epilepsy that extends beyond the epileptic cortex and a potential mechanistic explanation for the broad cognitive deficits that can be observed in this epileptic encephalopathy.

Evolution of Cortical Functional Networks in Healthy Infants

During normal childhood development, functional brain networks evolve over time in parallel with changes in neuronal oscillations. Previous studies have demonstrated differences in network topology with age, particularly in neonates and in cohorts spanning from birth to early adulthood. Here, we evaluate the developmental changes in EEG functional connectivity with a specific focus on the first 2 years of life. Functional connectivity networks (FCNs) were calculated from the EEGs of 240 healthy infants aged 0-2 years during wakefulness and sleep using a cross-correlation-based measure and the weighted phase lag index. Topological features were assessed via network strength, global clustering coefficient, characteristic path length, and small world measures. We found that cross-correlation FCNs maintained a consistent small-world structure, and the connection strengths increased after the first 3 months of infancy. The strongest connections in these networks were consistently located in the frontal and occipital regions across age groups. In the delta and theta bands, weighted phase lag index networks decreased in strength after the first 3 months in both wakefulness and sleep, and a similar result was found in the alpha and beta bands during wakefulness. However, in the alpha band during sleep, FCNs exhibited a significant increase in strength with age, particularly in the 21-24 months age group. During this period, a majority of the strongest connections in the networks were located in frontocentral regions, and a qualitatively similar distribution was seen in the beta band during sleep for subjects older than 3 months. Graph theory analysis suggested a small world structure for weighted phase lag index networks, but to a lesser degree than those calculated using cross-correlation. In general, graph theory metrics showed little change over time, with no significant differences between age groups for the clustering coefficient (wakefulness and sleep), characteristics path length (sleep), and small world measure (sleep). These results suggest that infant FCNs evolve during the first 2 years with more significant changes to network strength than features of the network structure. This study quantifies normal brain networks during infant development and can serve as a baseline for future investigations in health and neurological disease.

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.

Abnormal sleep physiology in children with 15q11.2-13.1 duplication (Dup15q) syndrome

BACKGROUND

Sleep disturbances in autism spectrum disorder (ASD) represent a common and vexing comorbidity. Clinical heterogeneity amongst these warrants studies of the mechanisms associated with specific genetic etiologies. Duplications of 15q11.2-13.1 (Dup15q syndrome) are highly penetrant for neurodevelopmental disorders (NDDs) such as intellectual disability and ASD, as well as sleep disturbances. Genes in the 15q region, particularly UBE3A and a cluster of GABA_A receptor genes, are critical for neural development, synaptic protein synthesis and degradation, and inhibitory neurotransmission. During awake electroencephalography (EEG), children with Dup15q syndrome demonstrate increased beta band oscillations (12-30 Hz) that likely reflect aberrant GABAergic neurotransmission. Healthy sleep rhythms, necessary for robust cognitive development, are also highly dependent on GABAergic neurotransmission. We therefore hypothesized that sleep physiology would be abnormal in children with Dup15q syndrome.

METHODS

To test the hypothesis that elevated beta oscillations persist in sleep in Dup15q syndrome and that NREM sleep rhythms would be disrupted, we computed: (1) beta power, (2) spindle density, and (3) percentage of slow-wave sleep (SWS) in overnight sleep EEG recordings from a cohort of children with Dup15q syndrome (n = 15) and compared them to age-matched neurotypical children (n = 12).

RESULTS

Children with Dup15q syndrome showed abnormal sleep physiology with elevated beta power, reduced spindle density, and reduced or absent SWS compared to age-matched neurotypical controls.

LIMITATIONS

This study relied on clinical EEG where sleep staging was not available. However, considering that clinical polysomnograms are challenging to collect in this population, the ability to quantify these biomarkers on clinical EEG-routinely ordered for epilepsy monitoring-opens the door for larger-scale studies. While comparable to other human studies in rare genetic disorders, a larger sample would allow for examination of the role of seizure severity, medications, and developmental age that may impact sleep physiology.

CONCLUSIONS

We have identified three quantitative EEG biomarkers of sleep disruption in Dup15q syndrome, a genetic condition highly penetrant for ASD. Insights from this study not only promote a greater mechanistic understanding of the pathophysiology defining Dup15q syndrome, but also lay the foundation for studies that investigate the association between sleep and cognition. Abnormal sleep physiology may undermine healthy cognitive development and may serve as a quantifiable and modifiable target for behavioral and pharmacological interventions.

Sleep: Twitch in tempo

Sudden bursts of jerky movements during sleep, called twitches, aid early developmental brain wiring in mice. Translating these findings to humans, a new study reveals that quiet sleep twitches increase in early infancy and coordinate with sleep spindles to establish functional connectivity.

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.

Characteristics of sleep spindles in school-aged children with attention-deficit/hyperactivity disorder

OBJECTIVE

Attention deficit/hyperactivity disorder (ADHD) is a complex disorder, characterized by different presentations with distinct cognitive and neurobiological characterizations. Here we aimed to investigate whether sleep spindle activity, which has been associated with brain maturation, may be a potential biomarker able to differentiate ADHD presentations in school-aged children (7-11 years).

METHOD

Spindle characteristics were extracted from overnight polysomnography in 74 children (27 ADHD-Inattentive [IQ = 96.04], 25 ADHD-hyperactive/impulsive [IQ = 98.9], and 22 ADHD-combined [IQ = 96.1]). We obtained data of the frontal (Fz) and parietal (Pz) derivations using a validated spindle detection algorithm.

RESULTS

Children with ADHD showed a higher number and density of slow compared to fast spindles which were more frequent in frontal area. No differences were observed among ADHD presentations for any spindle characteristics. Spindle frequency and density increased with age, indicating an age-dependent maturation of different sleep spindles. However, no associations between IQ and spindle characteristics were observed.

CONCLUSIONS

In children with ADHD the spindle characteristics evolve with age but sleep spindle activity does not seem to be a valid biomarker of ADHD phenotypes or general cognitive ability.

Sleep spindles in children with restless sleep disorder, restless legs syndrome and normal controls

OBJECTIVE

To analyze and identify differences in sleep spindles in children with restless sleep disorder (RSD), restless legs syndrome (RLS) and normal controls.

METHODS

PSG (polysomnography) from children with RSD, RLS and normal controls were analyzed. Sleep spindle activity was detected on one frontal and one central electrode, for each epoch of N2 and N3 sleep. Sleep spindle density, duration and intensity (density × duration) were then obtained and used for analysis.

RESULTS

Thirty-eight children with RSD, twenty-three children with RLS and twenty-nine controls were included. The duration of frontal spindles in sleep stage N2 was longer in children with RSD than in controls. Frontal spindle density and intensity tended to be increased in RSD children. No significant differences were found for central spindles.

CONCLUSION

Children with RSD had longer frontal spindles. This finding may contribute to explain the occurrence of excessive movement activity during sleep and the presence of daytime symptoms.

SIGNIFICANCE

Recent research has demonstrated that children with RSD have increased NREM instability and sympathetic activation during sleep. Analyzing sleep spindles in children with RSD in comparison with children with RLS and controls adds to our understanding of the pathophysiology or RSD and its effects on daytime impairment.

CASK related disorder: Epilepsy and developmental outcome

OBJECTIVE

CASK pathogenic variants are associated with variable features, as intellectual disability, optic atrophy, brainstem/cerebellar hypoplasia, and epileptic encephalopathy. Few studies describe the electroclinical features of epilepsy in patients with CASK pathogenic variants and their relationship with developmental delay.

METHODS

this national multicentre cohort included genetically confirmed patients with different CASK pathogenic variants. Our findings were compared with cohorts reported in the literature.

RESULTS

we collected 34 patients (29 females) showing from moderate (4 patients) to severe (22) and profound (8) developmental delay; all showed pontine and cerebellar hypoplasia, all except three with microcephaly. Seventeen out of 34 patients (50%) suffered from epileptic seizures, including spasms (11 patients, 32.3%), generalized (5) or focal seizures (1). In 8/17 individuals (47.1%), epilepsy started at or beyond the age of 24 months. Seven (3 males) out of the 11 children with spasms showed EEG features and a course supporting the diagnosis of a developmental and epileptic encephalopathy (DEE). Drug resistance was frequent in our cohort (52.9% of patients with epilepsy). EEG abnormalities included poorly organized background activity with diffuse or multifocal epileptiform abnormalities and sleep-activation, with possible appearance over the follow-up period. Developmental delay degree was not statistically different among patients with or without seizures but feeding difficulties were more frequent in patients with epilepsy.

CONCLUSIONS

epilepsy is a frequent comorbidity with a high incidence of spasms and drug resistance. Overall developmental disability does not seem to be more severe in the group of patients with epilepsy nor to be linked to specific epilepsy/EEG characteristics. A childhood onset of epilepsy is frequent, with possible worsening over time, so that serial and systematic monitoring is mandatory.

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.

Analysis of sleep spindles in children with Asperger's syndrome

Sleep spindles are an element of the sleep microstructure observed on the EEG during the NREM sleep phase. Sleep spindles are associated to sleep stability functions as well as memory consolidation and optimization of different cognitive processes. On the other hand, Asperger's syndrome (AS) is a generalized developmental disorder in which cognitive and sleep disturbances have been described. In this study we analyzed different characteristics of sleep spindles in a group of children with AS and compared them with sleep spindles of a group of children with typical development paired by age; both groups ranged from 6 to 12 years of age and were all male. We observed a statistically significant decrease in sleep spindles intrinsic frequency in different brain regions in the AS group in relation to the typical development group. This finding could be due to immaturity in brain regions related to the integration of sleep spindles; and this immaturity could be related with cognitive aspects in these patients.

Massive online data annotation, crowdsourcing to generate high quality sleep spindle annotations from EEG data

Spindle event detection is a key component in analyzing human sleep. However, detection of these oscillatory patterns by experts is time consuming and costly. Automated detection algorithms are cost efficient and reproducible but require robust datasets to be trained and validated. Using the MODA (Massive Online Data Annotation) platform, we used crowdsourcing to produce a large open-source dataset of high quality, human-scored sleep spindles (5342 spindles, from 180 subjects). We evaluated the performance of three subtype scorers: “experts, researchers and non-experts”, as well as 7 previously published spindle detection algorithms. Our findings show that only two algorithms had performance scores similar to human experts. Furthermore, the human scorers agreed on the average spindle characteristics (density, duration and amplitude), but there were significant age and sex differences (also observed in the set of detected spindles). This study demonstrates how the MODA platform can be used to generate a highly valid open source standardized dataset for researchers to train, validate and compare automated detectors of biological signals such as the EEG.

mPFC spindle cycles organize sparse thalamic activation and recently active CA1 cells during non-REM sleep

Sleep oscillations in the neocortex and hippocampus are critical for the integration of new memories into stable generalized representations in neocortex. However, the role of the thalamus in this process is poorly understood. To determine the thalamic contribution to non-REM oscillations (sharp-wave ripples, SWRs; slow/delta; spindles), we recorded units and local field potentials (LFPs) simultaneously in the limbic thalamus, mPFC, and CA1 in rats. We report that the cycles of neocortical spindles provide a key temporal window that coordinates CA1 SWRs with sparse but consistent activation of thalamic units. Thalamic units were phase-locked to delta and spindles in mPFC, and fired at consistent lags with other thalamic units within spindles, while CA1 units that were active during spatial exploration were engaged in SWR-coupled spindles after behavior. The sparse thalamic firing could promote an incremental integration of recently acquired memory traces into neocortical schemas through the interleaved activation of thalamocortical cells.

A mechanism for learning with sleep spindles

Spindles are ubiquitous oscillations during non-rapid eye movement (NREM) sleep. A growing body of evidence points to a possible link with learning and memory, and the underlying mechanisms are now starting to be unveiled. Specifically, spindles are associated with increased dendritic activity and high intracellular calcium levels, a situation favourable to plasticity, as well as with control of spiking output by feed-forward inhibition. During spindles, thalamocortical networks become unresponsive to inputs, thus potentially preventing interference between memory-related internal information processing and extrinsic signals. At the system level, spindles are co-modulated with other major NREM oscillations, including hippocampal sharp wave-ripples (SWRs) and neocortical slow waves, both previously shown to be associated with learning and memory. The sequential occurrence of reactivation at the time of SWRs followed by neuronal plasticity-promoting spindles is a possible mechanism to explain NREM sleep-dependent consolidation of memories. This article is part of the Theo Murphy meeting issue 'Memory reactivation: replaying events past, present and future'.

Loss of Snord116 alters cortical neuronal activity in mice: a preclinical investigation of Prader–Willi syndrome

Prader–Willi syndrome (PWS) is a neurodevelopmental disorder that is characterized by metabolic alteration and sleep abnormalities mostly related to rapid eye movement (REM) sleep disturbances. The disease is caused by genomic imprinting defects that are inherited through the paternal line. Among the genes located in the PWS region on chromosome 15 (15q11-q13), small nucleolar RNA 116 (Snord116) has been previously associated with intrusions of REM sleep into wakefulness in humans and mice. Here, we further explore sleep regulation of PWS by reporting a study with PWScrm+/p− mouse line, which carries a paternal deletion of Snord116. We focused our study on both macrostructural electrophysiological components of sleep, distributed among REMs and nonrapid eye movements. Of note, here, we study a novel electroencephalography (EEG) graphoelements of sleep for mouse studies, the well-known spindles. EEG biomarkers are often linked to the functional properties of cortical neurons and can be instrumental in translational studies. Thus, to better understand specific properties, we isolated and characterized the intrinsic activity of cortical neurons using in vitro microelectrode array. Our results confirm that the loss of Snord116 gene in mice influences specific properties of REM sleep, such as theta rhythms and, for the first time, the organization of REM episodes throughout sleep–wake cycles. Moreover, the analysis of sleep spindles present novel specific phenotype in PWS mice, indicating that a new catalog of sleep biomarkers can be informative in preclinical studies of PWS.

Low-Dose Perampanel Rescues Cortical Gamma Dysregulation Associated With Parvalbumin Interneuron GluA2 Upregulation in Epileptic Syngap1+/- Mice

BACKGROUND

Loss-of-function SYNGAP1 mutations cause a neurodevelopmental disorder characterized by intellectual disability and epilepsy. SYNGAP1 is a Ras GTPase-activating protein that underlies the formation and experience-dependent regulation of postsynaptic densities. The mechanisms that contribute to this proposed monogenic cause of intellectual disability and epilepsy remain unresolved.

METHODS

We established the phenotype of the epileptogenesis in a Syngap1^+/- mouse model using 24-hour video electroencephalography (vEEG)/electromyography recordings at advancing ages. We administered an acute low dose of perampanel, a Food and Drug Administration-approved AMPA receptor (AMPAR) antagonist, during a follow-on 24-hour vEEG to investigate the role of AMPARs in Syngap1 haploinsufficiency. Immunohistochemistry was performed to determine the region- and location-specific differences in the expression of the GluA2 AMPAR subunit.

RESULTS

A progressive worsening of the epilepsy with emergence of multiple seizure phenotypes, interictal spike frequency, sleep dysfunction, and hyperactivity was identified in Syngap1^+/- mice. Interictal spikes emerged predominantly during non-rapid eye movement sleep in 24-hour vEEG of Syngap1^+/- mice. Myoclonic seizures occurred at behavioral-state transitions both in Syngap1^+/- mice and during an overnight EEG from a child with SYNGAP1 haploinsufficiency. In Syngap1^+/- mice, EEG spectral power analyses identified a significant loss of gamma power modulation during behavioral-state transitions. A significant region-specific increase of GluA2 AMPAR subunit expression in the somas of parvalbumin-positive interneurons was identified.

CONCLUSIONS

Acute dosing with perampanel significantly rescued behavioral state-dependent cortical gamma homeostasis, identifying a novel mechanism implicating Ca²⁺-impermeable AMPARs on parvalbumin-positive interneurons underlying circuit dysfunction in SYNGAP1 haploinsufficiency.

Nonrapid eye movement sleep and risk for autism spectrum disorder in early development: A topographical electroencephalogram pilot study

OBJECTIVE

Autism spectrum disorder (ASD) is a pervasive neurodevelopmental disorder that emerges in the beginning years of life (12-48 months). Yet, an early diagnosis of ASD is challenging as it relies on the consistent presence of behavioral symptomatology, and thus, many children are diagnosed later in development, which prevents early interventions that could benefit cognitive and social outcomes. As a result, there is growing interest in detecting early brain markers of ASD, such as in the electroencephalogram (EEG) to elucidate divergence in early development. Here, we examine the EEG of nonrapid eye movement (NREM) sleep in the transition from infancy to toddlerhood, a period of rapid development and pronounced changes in early brain function. NREM features exhibit clear developmental trajectories, are related to social and cognitive development, and may be altered in neurodevelopmental disorders. Yet, spectral features of NREM sleep are poorly understood in infants/toddlers with or at high risk for ASD.

METHODS

The present pilot study is the first to examine NREM sleep in 13- to 30-month-olds with ASD in comparison with age-matched healthy controls (TD). EEG was recorded during a daytime nap with high-density array EEG.

RESULTS

We found topographically distinct decreased fast theta oscillations (5-7.25 Hz), decreased fast sigma (15-16 Hz), and increased beta oscillations (20-25 Hz) in ASD compared to TD.

CONCLUSION

These findings suggest a possible functional role of NREM sleep during this important developmental period and provide support for NREM sleep to be a potential early marker for ASD.

Sleep Spindles: Mechanisms and Functions

Sleep spindles are burstlike signals in the electroencephalogram (EEG) of the sleeping mammalian brain and electrical surface correlates of neuronal oscillations in thalamus. As one of the most inheritable sleep EEG signatures, sleep spindles probably reflect the strength and malleability of thalamocortical circuits that underlie individual cognitive profiles. We review the characteristics, organization, regulation, and origins of sleep spindles and their implication in non-rapid-eye-movement sleep (NREMS) and its functions, focusing on human and rodent. Spatially, sleep spindle-related neuronal activity appears on scales ranging from small thalamic circuits to functional cortical areas, and generates a cortical state favoring intracortical plasticity while limiting cortical output. Temporally, sleep spindles are discrete events, part of a continuous power band, and elements grouped on an infraslow time scale over which NREMS alternates between continuity and fragility. We synthesize diverse and seemingly unlinked functions of sleep spindles for sleep architecture, sensory processing, synaptic plasticity, memory formation, and cognitive abilities into a unifying sleep spindle concept, according to which sleep spindles 1) generate neural conditions of large-scale functional connectivity and plasticity that outlast their appearance as discrete EEG events, 2) appear preferentially in thalamic circuits engaged in learning and attention-based experience during wakefulness, and 3) enable a selective reactivation and routing of wake-instated neuronal traces between brain areas such as hippocampus and cortex. Their fine spatiotemporal organization reflects NREMS as a physiological state coordinated over brain and body and may indicate, if not anticipate and ultimately differentiate, pathologies in sleep and neurodevelopmental, -degenerative, and -psychiatric conditions.

Associations between cognitive performance and sigma power during sleep in children with attention-deficit/hyperactivity disorder, healthy children, and healthy adults

Sigma power during sleep is associated with cognitive abilities in healthy humans. We examined the relationship between sigma power in sleep EEG and intelligence and alertness in schoolchildren with ADHD (n = 17) in comparison to mentally healthy children (n = 16) and adults (n = 23). We observed a positive correlation between sigma power in sleep stage 2 and IQ in healthy adults but a negative correlation in children with ADHD. Furthermore, children with ADHD showed slower reaction times in alertness testing than both control groups. In contrast, only healthy children displayed a positive correlation between sigma power and reaction times. These data suggest that the associations between sigma power and cognitive performance underlie distinct developmental processes. A negative association between IQ and sigma power indicates a disturbed function of sleep in cognitive functions in ADHD, whereas the function of sleep appears to be matured early in case of motor-related alertness performance.

Atypicalities in sleep and semantic consolidation in autism

Sleep is known to support the neocortical consolidation of declarative memory, including the acquisition of new language. Autism spectrum disorder (ASD) is often characterized by both sleep and language learning difficulties, but few studies have explored a potential connection between the two. Here, 54 children with and without ASD (matched on age, nonverbal ability and vocabulary) were taught nine rare animal names (e.g., pipa). Memory was assessed via definitions, naming and speeded semantic decision tasks immediately after learning (pre‐sleep), the next day (post‐sleep, with a night of polysomnography between pre‐ and post‐sleep tests) and roughly 1 month later (follow‐up). Both groups showed comparable performance at pre‐test and similar levels of overnight change on all tasks; but at follow‐up children with ASD showed significantly greater forgetting of the unique features of the new animals (e.g., pipa is a flat frog). Children with ASD had significantly lower central non‐rapid eye movement (NREM) sigma power. Associations between spindle properties and overnight changes in speeded semantic decisions differed by group. For the TD group, spindle duration predicted overnight changes in responses to novel animals but not familiar animals, reinforcing a role for sleep in the stabilization of new semantic knowledge. For the ASD group, sigma power and spindle duration were associated with improvements in responses to novel and particularly familiar animals, perhaps reflecting more general sleep‐associated improvements in task performance. Plausibly, microstructural sleep atypicalities in children with ASD and differences in how information is prioritized for consolidation may lead to cumulative consolidation difficulties, compromising the quality of newly formed semantic representations in long‐term memory.

Reduced sleep spindle activity in children with primary snoring

BACKGROUND

Habitually snoring children are at risk of manifesting disease-related problems even if their sleep studies are overall within normal limits.

STUDY OBJECTIVES

To compare sleep spindle activity in children with primary snoring and healthy controls.

METHODS

Sleep spindle activity including analysis of fast and slow spindles (ie, >13 Hz and <13 Hz, respectively) was evaluated in polysomnographic (PSG) recordings of 20 randomly selected children with primary snoring (PS; normal PSG recordings except for objective presence of snoring; 12 boys, mean age 6.5 ± 2.1 years), and 20 age- and gender-matched PSG-confirmed non-snoring controls.

RESULTS

PS children showed significantly lower spindle indices in all non-rapid eye movement (NREM) sleep stages (p < 0.05). In contrast, fast spindles were found in 40% (n = 8) children with PS and in 25% (n = 5) controls. Sleep spindle activity was particularly higher in NREM sleep stage 2 in controls compared PS (76% versus 43% of all marked sleep spindles events in NREM sleep stage 2, p < 0.001).

CONCLUSIONS

Children with PS exhibit significantly reduced spindle activity when compared to matched controls. Reduced sleep spindle activity may be an indicator of sleep disruption and, therefore, could be involved in the development of disease-related consequences in snoring children.

Epilepsy and interictal epileptiform activity in patients with autism spectrum disorders

PURPOSE

The purpose of this study was to determine the prevalence of epilepsy and subclinical epileptiform abnormalities in children with autism spectrum disorder (ASD), and to investigate its effects on core autistic symptoms and adaptive behavior skills.

METHODS

Patients with diagnosis of ASD who met full criteria on Autism Diagnostic Interview-Revised (ADI-R) were included in the study. Adaptive behavior skills were assessed by Vineland Adaptive Behavior Scale-II (VABS-II). Clinical assessment for epilepsy and video electroencephalography (EEG) (v-EEG) examinations during wakefulness and/or sleep were prospectively performed in all patients.

RESULTS

A total of 112 patients with diagnosis of ASD of mean age 6.58 ± 3.72 were included in the study. Based on clinical and v-EEG assessments, three groups of patients were defined: 1) patients with epilepsy (n = 17; 15.2%); 2) patients with epileptiform discharges in absence of clinical seizures (n = 14; 12.5%); 3) patients without epilepsy and without epileptiform discharges (n = 81; 72.3%). There were no significant differences between three groups of patients on ADI-R subscores. Speech development was also not significantly related to epilepsy. There was a slight tendency of the VABS-II motor skills score to be higher in the group of patients with autism without clinical diagnosis of epilepsy and without subclinical epileptiform discharges (p < 0.05) in comparison with the two other groups. According to this tendency, we might claim that patients with higher scores on motor skills could have 0.88 times lower odds for having epileptiform EEG activity.

CONCLUSIONS

According to our results, we were not able to detect differences in the ADI-R between the three populations with ASD, all with unknown etiology. Epilepsy, as well as subclinical epileptic discharges, showed small effects on Motor Skills in patients with autism, and had no effect on adaptive behavior Communication/Socialization/Daily Living Skills.

Transient extreme spindles in a young child with anti-NMDAR encephalitis: A case report

Anti-N-methyl-d-aspartate receptor (anti-NMDAR) encephalitis is a type of immune-mediated encephalitis, which is a new category of treatment-responsive paraneoplastic encephalitis. In patients with this disease, electroencephalography (EEG) shows non-specific findings, but recently, a unique EEG pattern, named the extreme delta brush, was detected in 40% of adult patients and was suggested to be specific to this type of encephalitis. Here, we describe a two-year-old boy with anti-NMDAR encephalitis, who presented with speech arrest and disturbances of gait and cognition several weeks after developing febrile convulsions. In the early stages of the disease, EEG showed 14-16 Hz, continuous, fast waves characterized by a high amplitude (200-500 µV), very diffuse spreading, and a sharp morphology, during light sleep only, which was compatible with extreme spindles. As the patient's symptoms worsened, this finding was replaced by rhythmic, diffuse, high-voltage, slow waves. Immediately after immunomodulatory therapies, including intravenous methylprednisolone and immunoglobulin, his clinical manifestations and EEG abnormalities appeared to improve. We propose that although the extreme spindle is a non-specific finding of this type of encephalitis, early EEG monitoring might be necessary to detect not only the extreme delta brush pattern, but also non-specific findings, including extreme spindles, which would aid early diagnosis and treatment.

A sleep spindle detection algorithm that emulates human expert spindle scoring

BACKGROUND

Sleep spindles are a marker of stage 2 NREM sleep that are linked to learning & memory and are altered by many neurological diseases. Although visual inspection of the EEG is considered the gold standard for spindle detection, it is time-consuming, costly and can introduce inter/ra-scorer bias.

NEW METHOD

Our goal was to develop a simple and efficient sleep-spindle detector (algorithm #7, or 'A7') that emulates human scoring. 'A7' runs on a single EEG channel and relies on four parameters: the absolute sigma power, relative sigma power, and correlation/covariance of the sigma band-passed signal to the original EEG signal. To test the performance of the detector, we compared it against a gold standard spindle dataset derived from the consensus of a group of human experts.

RESULTS

The by-event performance of the 'A7' spindle detector was 74% precision, 68% recall (sensitivity), and an F1-score of 0.70. This performance was equivalent to an individual human expert (average F1-score = 0.67).

COMPARISON WITH EXISTING METHOD(S)

The F1-score of 'A7' was 0.17 points higher than other spindle detectors tested. Existing detectors have a tendency to find large numbers of false positives compared to human scorers. On a by-subject basis, the spindle density estimates produced by A7 were well correlated with human experts (r² = 0.82) compared to the existing detectors (average r² = 0.27).

CONCLUSIONS

The 'A7' detector is a sensitive and precise tool designed to emulate human spindle scoring by minimizing the number of 'hidden spindles' detected. We provide an open-source implementation of this detector for further use and testing.

Abnormal coherence and sleep composition in children with Angelman syndrome: a retrospective EEG study

Background

Angelman syndrome (AS) is a neurodevelopmental disorder characterized by intellectual disability, speech and motor impairments, epilepsy, abnormal sleep, and phenotypic overlap with autism. Individuals with AS display characteristic EEG patterns including high-amplitude rhythmic delta waves. Here, we sought to quantitatively explore EEG architecture in AS beyond known spectral power phenotypes. We were motivated by studies of functional connectivity and sleep spindles in autism to study these EEG readouts in children with AS.

Methods

We analyzed retrospective wake and sleep EEGs from children with AS (age 4-11) and age-matched neurotypical controls. We assessed long-range and short-range functional connectivity by measuring coherence across multiple frequencies during wake and sleep. We quantified sleep spindles using automated and manual approaches.

Results

During wakefulness, children with AS showed enhanced long-range EEG coherence across a wide range of frequencies. During sleep, children with AS showed increased long-range EEG coherence specifically in the gamma band. EEGs from children with AS contained fewer sleep spindles, and these spindles were shorter in duration than their neurotypical counterparts.

Conclusions

We demonstrate two quantitative readouts of dysregulated sleep composition in children with AS-gamma coherence and spindles-and describe how functional connectivity patterns may be disrupted during wakefulness. Quantitative EEG phenotypes have potential as biomarkers and readouts of target engagement for future clinical trials and provide clues into how neural circuits are dysregulated in children with AS.

Abnormal coherence and sleep composition in children with Angelman syndrome: a retrospective EEG study

Background

Angelman syndrome (AS) is a neurodevelopmental disorder characterized by intellectual disability, speech and motor impairments, epilepsy, abnormal sleep, and phenotypic overlap with autism. Individuals with AS display characteristic EEG patterns including high-amplitude rhythmic delta waves. Here, we sought to quantitatively explore EEG architecture in AS beyond known spectral power phenotypes. We were motivated by studies of functional connectivity and sleep spindles in autism to study these EEG readouts in children with AS.

Methods

We analyzed retrospective wake and sleep EEGs from children with AS (age 4–11) and age-matched neurotypical controls. We assessed long-range and short-range functional connectivity by measuring coherence across multiple frequencies during wake and sleep. We quantified sleep spindles using automated and manual approaches.

Results

During wakefulness, children with AS showed enhanced long-range EEG coherence across a wide range of frequencies. During sleep, children with AS showed increased long-range EEG coherence specifically in the gamma band. EEGs from children with AS contained fewer sleep spindles, and these spindles were shorter in duration than their neurotypical counterparts.

Conclusions

We demonstrate two quantitative readouts of dysregulated sleep composition in children with AS—gamma coherence and spindles—and describe how functional connectivity patterns may be disrupted during wakefulness. Quantitative EEG phenotypes have potential as biomarkers and readouts of target engagement for future clinical trials and provide clues into how neural circuits are dysregulated in children with AS.

Electronic supplementary material

The online version of this article (10.1186/s13229-018-0214-8) contains supplementary material, which is available to authorized users.

Visually detected non-rapid eye movement stage 2 sleep spindle density at age five years predicted prosocial behavior positively and hyperactivity scores negatively at age nine years

OBJECTIVE

A higher density of sleep electroencephalogram (EEG) spindles has been cross-sectionally associated with more efficient cortical-subcortical connectivity, superior intellectual and learning abilities, and healthier emotional and behavioral traits. In the present study, we explored to what extent sleep spindle density (SSD) at age five years could predict emotional and behavioral traits at six and nine years.

METHODS

A total of 19 healthy preschoolers at age five years underwent in-home sleep EEG recordings for visual scoring of non-rapid eye movement stage 2 (NREM-S2) sleep spindles, and SSD in NREM-S2 was calculated. Parents and teachers rated children's emotional and behavioral characteristics at ages five, six, and nine years.

RESULTS

Higher SSD at five years predicted higher prosocial behavior scores at nine years, as rated by parents and teachers, and lower hyperactivity scores as rated by teachers. Multiple regression analyses showed that SSD predicted prosocial behavior and hyperactivity independently of earlier prosocial behavior or hyperactivity.

CONCLUSION

The pattern of results suggests that a higher SSD at five years is predictive of higher scores for positive emotional and behavioral characteristics four years later. Therefore, spindle density indices might be acknowledged as an indicator not only of cognitive but also of emotional-behavioral development in children.

Consolidation of vocabulary is associated with sleep in typically developing children, but not in children with dyslexia

Sleep is known to play an active role in consolidating new vocabulary in adults; however, the mechanisms by which sleep promotes vocabulary consolidation in childhood are less well understood. Furthermore, there has been no investigation into whether previously reported differences in sleep architecture might account for variability in vocabulary consolidation in children with dyslexia. Twenty-three children with dyslexia and 29 age-matched typically developing peers were exposed to 16 novel spoken words. Typically developing children showed overnight improvements in novel word recall; the size of the improvement correlated positively with slow wave activity, similar to previous findings with adults. Children with dyslexia showed poorer recall of the novel words overall, but nevertheless showed overnight improvements similar to age-matched peers. However, comparisons with younger children matched on initial levels of novel word recall pointed to reduced consolidation in dyslexics after 1 week. Crucially, there were no significant correlations between overnight consolidation and sleep parameters in the dyslexic group. This suggests a reduced role of sleep in vocabulary consolidation in dyslexia, possibly as a consequence of lower levels of learning prior to sleep, and highlights how models of sleep-associated memory consolidation can be usefully informed by data from typical and atypical development.