Developmental Changes in Sleep Spindle Characteristics and Sigma Power across Early Childhood

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

STUDY OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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.

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.

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

Importance

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

Objectives

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

Design setting and participants

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

Main outcomes and measures

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

Results

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

Conclusion and relevance

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

The sleep and wake electroencephalogram over the lifespan

Both sleep and wake encephalograms (EEG) change over the lifespan. While prior studies have characterized age-related changes in the EEG, the datasets span a particular age group, or focused on sleep and wake macrostructure rather than the microstructure. Here, we present sex-stratified data from 3372 community-based or clinic-based otherwise neurologically and psychiatrically healthy participants ranging from 11 days to 80 years of age. We estimate age norms for key sleep and wake EEG parameters including absolute and relative powers in delta, theta, alpha, and sigma bands, as well as sleep spindle density, amplitude, duration, and frequency. To illustrate the potential use of the reference measures developed herein, we compare them to sleep EEG recordings from age-matched participants with Alzheimer's disease, severe sleep apnea, depression, osteoarthritis, and osteoporosis. Although the partially clinical nature of the datasets may bias the findings towards less normal and hence may underestimate pathology in practice, age-based EEG reference values enable objective screening of deviations from healthy aging among individuals with a variety of disorders that affect brain health.

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 <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.

Dexmedetomidine-mediated sleep phase modulation ameliorates motor and cognitive performance in a chronic blast-injured mouse model

Multiple studies have shown that blast injury is followed by sleep disruption linked to functional sequelae. It is well established that improving sleep ameliorates such functional deficits. However, little is known about longitudinal brain activity changes after blast injury. In addition, the effects of directly modulating the sleep/wake cycle on learning task performance after blast injury remain unclear. We hypothesized that modulation of the sleep phase cycle in our injured mice would improve post-injury task performance. Here, we have demonstrated that excessive sleep electroencephalographic (EEG) patterns are accompanied by prominent motor and cognitive impairment during acute stage after secondary blast injury (SBI) in a mouse model. Over time we observed a transition to more moderate and prolonged sleep/wake cycle disturbances, including changes in theta and alpha power. However, persistent disruptions of the non-rapid eye movement (NREM) spindle amplitude and intra-spindle frequency were associated with lasting motor and cognitive deficits. We, therefore, modulated the sleep phase of injured mice using subcutaneous (SC) dexmedetomidine (Dex), a common, clinically used sedative. Dex acutely improved intra-spindle frequency, theta and alpha power, and motor task execution in chronically injured mice. Moreover, dexmedetomidine ameliorated cognitive deficits a week after injection. Our results suggest that SC Dex might potentially improve impaired motor and cognitive behavior during daily tasks in patients that are chronically impaired by blast-induced injuries.

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

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

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.

Scalp EEG markers of normal infant development using visual and computational approaches

The infant brain is rapidly developing, and these changes are reflected in scalp electroencephalography (EEG) features, including power spectrum and sleep spindle characteristics. These biomarkers not only mirror infant development, but they are also altered by conditions such as epilepsy, autism, developmental delay, and trisomy 21. Prior studies of early development were generally limited by small cohort sizes, lack of a specific focus on infancy (0-2 years), and exclusive use of visual marking for sleep spindles. Therefore, we measured the EEG power spectrum and sleep spindles in 240 infants ranging from 0-24 months. To rigorously assess these metrics, we used both clinical visual assessment and computational techniques, including automated sleep spindle detection. We found that the peak frequency and power of the posterior dominant rhythm (PDR) increased with age, and a corresponding peak occurred in the EEG power spectra. Based on both clinical and computational measures, spindle duration decreased with age, and spindle synchrony increased with age. Our novel metric of spindle asymmetry suggested that peak spindle asymmetry occurs at 6-9 months of age.Clinical Relevance- Here we provide a robust characterization of the development of EEG brain rhythms during infancy. This can be used as a basis of comparison for studies of infant neurological disease, including epilepsy, autism, developmental delay, and trisomy 21.

The memory benefits of two naps per day during infancy: A pilot investigation

In infancy, sleep occurs in multiple nap and overnight bouts that change developmentally in quantity and distribution. Though studies suggest that infant memory benefits from a single nap, no work has assessed the relative benefits of different naps (morning vs. afternoon), nor how multiple naps support memory across the day. We investigated the memory benefit of a morning nap, relative to morning wake, and the effect of these intervals on afternoon nap function in 9-month-olds (n = 15). Infants participated in two within-subjects conditions (separated by 1-2 weeks). In the Nap-Nap condition, infants took their morning and afternoon naps; in the Wake-Nap condition, infants were kept awake during morning naptime, but napped unrestricted in the afternoon. Before each nap/wake interval, infants completed an imitation memory task, with memory assessed again shortly after the nap/wake interval. In the Nap-Nap condition, infants showed memory retention across morning and afternoon naps. In contrast, infants tended to forget items learned across morning wake in the Wake-Nap condition. Moreover, morning wake was associated with a significant decline in post-nap retention of items learned in the afternoon. Furthermore, relations between nap slow-wave activity (SWA) and memory varied across naps, with SWA either not predicting (morning naps) or positively predicting (afternoon naps) memory change in the Nap-Nap condition, but negatively predicting afternoon memory change in the Wake-Nap condition. We conclude that two naps per day (rather than one) aids memory at 9 months, and that skipping the morning nap may moderate relations between afternoon nap physiology and memory.

Ageing-related changes in nap neuroscillatory activity are mediated and moderated by grey matter volume

Ageing‐related changes in grey matter result in changes in the intensity and topography of sleep neural activity. However, it is unclear whether these findings can be explained by ageing‐related differences in sleep pressure or circadian influence. The current study used high‐density electroencephalography to assess how grey matter volume differences between young and older adults mediate and moderate neuroscillatory activity differences during a midday nap following a motor sequencing task. Delta, theta, and sigma amplitude were reduced in older relative to young adults, especially over frontocentral scalp, leading to increases in relative delta frontality and relative sigma lateral centroposteriority. Delta reductions in older adults were mediated by grey matter loss in frontal medial cortex, primary motor cortex, thalamus, caudate, putamen, and pallidum, and were moderated by putamen grey matter volume. Theta reductions were mediated by grey matter loss in primary motor cortex, thalamus, and caudate, and were moderated by putamen and pallidum grey matter volume. Sigma changes were moderated by putamen and pallidum grey matter volume. Moderation results suggested that across frequencies, young adults with more grey matter had increased activity, whereas older adults with more grey matter had unchanged or decreased activity. These results provide a critical extension of previous findings from overnight sleep in a midday nap, indicating that they are not driven by sleep pressure or circadian confounds. Moreover, these results suggest brain regions associated with motor sequence learning contribute to sleep neural activity following a motor sequencing task.

Spindle-AI: Sleep spindle number and duration estimation in infant EEG

OBJECTIVE

Sleep spindle features show developmental changes during infancy and have the potential to provide an early biomarker for abnormal brain maturation. Manual identification of sleep spindles in the electroencephalogram (EEG) is time-consuming and typically requires highly-trained experts. Automated detection of sleep spindles would greatly facilitate this analysis. Research on the automatic detection of sleep spindles in infant EEG has been limited to-date.

METHODS

We present a random forest-based sleep spindle detection method (Spindle-AI) to estimate the number and duration of sleep spindles in EEG collected from 141 ex-term born infants, recorded at 4 months of age. The signal on channel F4-C4 was split into a training set (81 ex-term) and a validation set (30 ex-term). An additional 30 ex-term infant EEGs (channel F4-C4 and channel F3-C3) were used as an independent test set. Fourteen features were selected for input into a random forest algorithm to estimate the number and duration of spindles and the results were compared against sleep spindles annotated by an experienced clinical physiologist.

RESULTS

The prediction of the number of sleep spindles in the independent test set demonstrated 93.3% to 93.9% sensitivity, 90.7% to 91.5% specificity, and 89.2% to 90.1% precision. The duration estimation of sleep spindle events in the independent test set showed a percent error of 5.7% to 7.4%.

CONCLUSION AND SIGNIFICANCE

Spindle-AI has been implemented as a web server that has the potential to assist clinicians in the fast and accurate monitoring of sleep spindles in infant EEGs.

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.

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.

Slow wave sleep in naps supports episodic memories in early childhood

Naps have been shown to benefit visuospatial learning in early childhood. This benefit has been associated with sleep spindles during the nap. However, whether young children's naps and their accompanying physiology benefit other forms of declarative learning is unknown. Using a novel storybook task, we found performance in children (N = 22, mean age = 51.23 months) was better following a nap compared to performance following an equivalent interval spent awake. Moreover, performance remained better the following day if a nap followed learning. Change in post-nap performance was positively associated with the amount of time spent in slow wave sleep during the nap. This suggests that slow wave sleep in naps may support episodic memory consolidation in early childhood. Taken in conjunction with prior work, these results suggest that multiple features of brain physiology during naps may contribute to declarative memory processing in early childhood.

Current ideas about the roles of rapid eye movement and non-rapid eye movement sleep in brain development

Understanding the links between sleep and brain development is important, as rapid eye movement (REM) sleep and non-REM (NREM) sleep seem to contribute to different aspects of brain maturation. If children have sleep problems, REM sleep and NREM sleep are likely to have different consequences for their developing brain, depending on their age. We highlight important discoveries from human and animal research on the role sleep plays in brain development. A hypothetical model is presented to explain the dynamic relationship of REM sleep and NREM sleep with different processes of brain maturation, with implications for current neonatal care and future research.

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.

Construction and disruption of spatial memory networks during development

Spatial memory, the aspect of memory involving encoding and retrieval of information regarding one's environment and spatial orientation, is a complex biological function incorporating multiple neuronal networks. Hippocampus-dependent spatial memory is not innate and emerges during development in both humans and rodents. In children, nonhippocampal dependent egocentric (self-to-object) memory develops before hippocampal-dependent allocentric (object-to-object) memory. The onset of allocentric spatial memory abilities in children around 22 mo of age occurs at an age-equivalent time in rodents when spatially tuned grid and place cells arise from patterned activity propagating through the entorhinal-hippocampal circuit. Neuronal activity, often driven by specific sensory signals, is critical for the normal maturation of brain circuits This patterned activity fine-tunes synaptic connectivity of the network and drives the emergence of specific firing necessary for spatial memory. Whereas normal activity patterns are required for circuit maturation, aberrant neuronal activity during development can have major adverse consequences, disrupting the development of spatial memory. Seizures during infancy, involving massive bursts of synchronized network activity, result in impaired spatial memory when animals are tested as adolescents or adults. This impaired spatial memory is accompanied by alterations in spatial and temporal coding of place cells. The molecular mechanisms by which early-life seizures lead to disruptions at the cellular and network levels are now becoming better understood, and provide a target for intervention, potentially leading to improved cognitive outcome in individuals experiencing early-life seizures.

Sleep spindle characteristics in adolescents

OBJECTIVE

Sleep changes substantially during adolescence; however, our understanding of age-related differences in specific electroencephalographic waveforms during this developmental period is limited.

METHOD

Sigma power, spindle characteristics and cognitive data were calculated for fast (∼13 Hz) central and slow (∼11 Hz) frontal sleep spindles for a large cross-sectional sample of adolescents (N = 134, aged 12-21 years, from the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) study).

RESULTS

Older age (and advanced pubertal development) was associated with lower absolute sigma power and greater fast spindle density, with spindles having a shorter duration and smaller amplitude and occurring at a faster average frequency than at a younger age. Spindle characteristics were not directly associated with cognition. An indirect relationship (age * density) provided some evidence for an association between better episodic memory performance and greater spindle density only for younger adolescents.

CONCLUSION

Spindle characteristics in adolescents differed according to age, possibly reflecting underlying differences in thalamo-cortical connectivity, and may play a role in episodic memory early in adolescence.

SIGNIFICANCE

Sleep spindles may serve as a marker of adolescent development, likely reflecting brain maturational status. Investigating specific spindle characteristics, in addition to sigma power, is necessary to fully characterize spindles during adolescence.

Nature and Nurture: Brain Region-Specific Inheritance of Sleep Neurophysiology in Adolescence

Sleep-specific oscillations of spindles and slow waves are generated through thalamocortical and corticocortical loops, respectively, and provide a unique opportunity to measure the integrity of these neuronal systems. Understanding the relative contribution of genetic factors to sleep oscillations is important for determining whether they constitute useful endophenotypes that mark vulnerability to psychiatric illness. Using high-density sleep EEG recordings in human adolescent twin pairs (n = 60; 28 females), we find that over posterior regions 80-90% of the variance in slow oscillations, slow wave, and spindle activity is due to genes. Surprisingly, slow (10-12 Hz) and fast (12-16 Hz) anterior spindle amplitude and σ power are largely driven by environmental factors shared among the twins. To our knowledge this is the first example of a neural phenotype that exhibits a strong influence of nature in one brain region, and nurture in another. Overall, our findings highlight the utility of the sleep EEG as a reliable and easy to measure endophenotype during adolescence. This measure may be used to measure disease risk in development before the onset of a psychiatric disorder; the location within the brain of deficits in sleep neurophysiology may suggest whether the ultimate cause is genetic or environmental.SIGNIFICANCE STATEMENT Two cardinal oscillations of sleep, slow waves and sleep spindles, play an important role in the core functions of sleep including memory consolidation, synaptic plasticity, and the recuperative function of sleep. In this study, we use a behavioral genetics approach to examine the heritability of sleep neurophysiology using high-density EEG in a sample of early adolescent twins. Our findings reveal a strong influence of both environmental and genetic factors in shaping these oscillations, dependent on brain region. Thus, during a developmental period when brain structure and function is in flux, we find that the sleep EEG is among the most heritable of human traits over circumscribed brain regions.

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

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

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.

Social, motor, and cognitive development through the lens of sleep network dynamics in infants and toddlers between 12 and 30 months of age

Widespread change in behavior and the underlying brain network substrate is a hallmark of early development. Sleep plays a fundamental role in this process. Both slow waves and spindles are key features of nonrapid eye movement sleep (NREM) that exhibit pronounced developmental trajectories from infancy to adulthood. Yet, these prominent features of NREM sleep are poorly understood in infants and toddlers in the age range of 12 to 30 months. Moreover, it is unknown how network dynamics of NREM sleep are associated with outcomes of early development. Addressing this gap in our understanding of sleep during development will enable the subsequent study of pathological changes in neurodevelopmental disorders. The aim of the current study was to characterize the sleep topography with high-density electroencephalography in this age group. We found that δ, θ, and β oscillations and sleep spindles exhibited clear developmental changes. Low δ and high θ oscillations correlated with motor, language, and social skills, independent of age. These findings suggest an important role of network dynamics of NREM sleep in cortical maturation and the associated development of skills during this important developmental period.

Different maturational changes of fast and slow sleep spindles in the first four years of life

OBJECTIVE/BACKGROUND

Massive changes in brain morphology and function in the first years of life reveal a postero-anterior trajectory of cortical maturation accompanied by regional modifications of NREM sleep. One of the most sensible marker of this maturation process is represented by electroencephalographic (EEG) activity within the frequency range of sleep spindles. However, direct evidence that these changes actually reflect maturational modifications of fast and slow spindles still lacks. Our study aimed at answering the following questions: 1. Do cortical changes at 11.50 Hz frequency correspond to slow spindles? 2. Do fast and slow spindles show different age trajectories and different topographical distributions? 3. Do changes in peak frequency explain age changes of slow and fast spindles?

PATIENTS/METHODS

We measured the antero-posterior changes of slow and fast spindles in the first 60 min of nightly sleep of 39 infants and children (0-48 mo.).

RESULTS

We found that (A) changes of slow spindles from birth to childhood mostly affect frontal areas (B) variations of fast and slow spindles across age groups go in opposite direction, the latter progressively increasing across ages; (C) this process is not merely reducible to changes of spindle frequency.

CONCLUSIONS

As a main finding, our cross-sectional study shows that the first form of mature spindle (i.e., corresponding to the adult phasic event of NREM sleep) is marked by the emergence of slow spindles on anterior regions around the age of 12 months.

Developmental Changes in Sleep Oscillations during Early Childhood

Although quantitative analysis of the sleep electroencephalogram (EEG) has uncovered important aspects of brain activity during sleep in adolescents and adults, similar findings from preschool-age children remain scarce. This study utilized our time-frequency method to examine sleep oscillations as characteristic features of human sleep EEG. Data were collected from a longitudinal sample of young children (n = 8; 3 males) at ages 2, 3, and 5 years. Following sleep stage scoring, we detected and characterized oscillatory events across age and examined how their features corresponded to spectral changes in the sleep EEG. Results indicated a developmental decrease in the incidence of delta and theta oscillations. Spindle oscillations, however, were almost absent at 2 years but pronounced at 5 years. All oscillatory event changes were stronger during light sleep than slow-wave sleep. Large interindividual differences in sleep oscillations and their characteristics (e.g., "ultrafast" spindle-like oscillations, theta oscillation incidence/frequency) also existed. Changes in delta and spindle oscillations across early childhood may indicate early maturation of the thalamocortical system. Our analytic approach holds promise for revealing novel types of sleep oscillatory events that are specific to periods of rapid normal development across the lifespan and during other times of aberrant changes in neurobehavioral function.

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

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

The Stress Acceleration Hypothesis of Nightmares

Adverse childhood experiences can deleteriously affect future physical and mental health, increasing risk for many illnesses, including psychiatric problems, sleep disorders, and, according to the present hypothesis, idiopathic nightmares. Much like post-traumatic nightmares, which are triggered by trauma and lead to recurrent emotional dreaming about the trauma, idiopathic nightmares are hypothesized to originate in early adverse experiences that lead in later life to the expression of early memories and emotions in dream content. Accordingly, the objectives of this paper are to (1) review existing literature on sleep, dreaming and nightmares in relation to early adverse experiences, drawing upon both empirical studies of dreaming and nightmares and books and chapters by recognized nightmare experts and (2) propose a new approach to explaining nightmares that is based upon the Stress Acceleration Hypothesis of mental illness. The latter stipulates that susceptibility to mental illness is increased by adversity occurring during a developmentally sensitive window for emotional maturation—the infantile amnesia period—that ends around age 3½. Early adversity accelerates the neural and behavioral maturation of emotional systems governing the expression, learning, and extinction of fear memories and may afford short-term adaptive value. But it also engenders long-term dysfunctional consequences including an increased risk for nightmares. Two mechanisms are proposed: (1) disruption of infantile amnesia allows normally forgotten early childhood memories to influence later emotions, cognitions and behavior, including the common expression of threats in nightmares; (2) alterations of normal emotion regulation processes of both waking and sleep lead to increased fear sensitivity and less effective fear extinction. These changes influence an affect network previously hypothesized to regulate fear extinction during REM sleep, disruption of which leads to nightmares. This network consists of a fear circuit that includes amygdala, hippocampus, and medial prefrontal cortex and whose substantial overlap with the stress acceleration findings allows the latter to be incorporated into a wider, more developmentally coherent framework.