Early adolescent cognitive gains are marked by increased sleep EEG coherence

The impacts of intra-individual daily sleep variability on daytime functioning and sleep architecture in healthy young adults: An experimental study

Sleep variability is commonly seen in the young populations. This study aimed to examine the impacts of experimentally induced sleep variability on sleepiness, mood, cognitive performance and sleep architectures among young adults. Thirty-six healthy individuals (aged 18-22 years) were randomly assigned to either variable sleep schedule (n = 20) or control (n = 16) groups. The protocol involved 1 week of regular sleep (time in bed = 7.5 hr) in the home setting, followed by one adaptation night (time in bed = 7.5 hr), one baseline night (time in bed = 7.5 hr), and 6 nights of sleep manipulation in the laboratory monitored by polysomnography (three cycles of variable sleep schedule by changing daily time in bed alternating between 6 hr and 9 hr for variable sleep schedule group versus fixed sleep schedule with daily time in bed for 7.5 hr for control group). Sleepiness, mood, sustained attention, processing speed, response inhibition and working memory were measured every morning and evening. The variable sleep schedule group reported a higher level of sleepiness, especially in the mornings, and increased negative mood in the evenings. There were no significant differences in positive mood, cognitive performance and sleep macro- and micro-structures. Our results showed the negative effects of sleep variability on daytime functioning especially sleepiness and negative mood, suggesting the need to address variable sleep schedules through sleep intervention.

Bedtime to the brain: how infants' sleep behaviours intertwine with non-rapid eye movement sleep electroencephalography features

Adequate sleep is critical for development and facilitates the maturation of the neurophysiological circuitries at the basis of cognitive and behavioural function. Observational research has associated early life sleep problems with worse later cognitive, psychosocial, and somatic health outcomes. Yet, the extent to which day-to-day sleep behaviours (e.g., duration, regularity) in early life relate to non-rapid eye movement (NREM) neurophysiology-acutely and the long-term-remains to be studied. We measured sleep behaviours in 32 healthy 6-month-olds assessed with actimetry and neurophysiology with high-density electroencephalography (EEG) to investigate the association between NREM sleep and habitual sleep behaviours. Our study revealed four findings: first, daytime sleep behaviours are related to EEG slow-wave activity (SWA). Second, night-time movement and awakenings from sleep are connected with spindle density. Third, habitual sleep timing is linked to neurophysiological connectivity quantified as delta coherence. And lastly, delta coherence at 6 months predicts night-time sleep duration at 12 months. These novel findings widen our understanding that infants' sleep behaviours are closely intertwined with three particular levels of neurophysiology: sleep pressure (determined by SWA), the maturation of the thalamocortical system (spindles), and the maturation of cortical connectivity (coherence). The crucial next step is to extend this concept to clinical groups to objectively characterise infants' sleep behaviours 'at risk' that foster later neurodevelopmental problems.

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.

Semi-Automatic Analysis of Specific Electroencephalographic Patterns during NREM2 Sleep in a Pediatric Population after SARS-CoV-2 Infection

The post-COVID-19 condition is defined by the World Health Organization as the persistence of symptoms or development of new symptoms three months after the initial SARS-CoV-2 infection, lasting for at least two months without a clear explanation. Neuropsychiatric disorders associated with this condition include asthenia, memory and concentration problems, and sleep disturbances. Our study aims to investigate sleep patterns following SARS-CoV-2 infection using EEG findings and a sleep quality questionnaire completed by parents (Sleep Disturbance Scale for Children-SDSC). Notably, our investigation is based on a convenience sample. The patients in our sample, aged 1 to 14 years, are not currently taking any medications; rather, they are undergoing follow-up assessments at the Child Neuropsychiatry department of the University Hospital of Messina for neurodevelopmental evaluations. Specifically, we are analyzing amplitude and power spectrum data in the first five minutes of NREM2 sleep, calculated from EEG recordings obtained via bipolar leads within three months after the onset of the disease. These results will be compared with controls performed on the same subjects in the six months preceding the infection. The focus of the study was sleep spindles, which are generated by the thalamocortical systems and play a role in sleep modulation, memory, and learning. Preliminary analysis suggests a predominant increase in the slow component of the spindles in the right-frontal lead.

The sleeping brain's connectivity and family environment: characterizing sleep EEG coherence in an infant cohort

Brain connectivity closely reflects brain function and behavior. Sleep EEG coherence, a measure of brain's connectivity during sleep, undergoes pronounced changes across development under the influence of environmental factors. Yet, the determinants of the developing brain's sleep EEG coherence from the child's family environment remain unknown. After characterizing high-density sleep EEG coherence in 31 healthy 6-month-old infants by detecting strongly synchronized clusters through a data-driven approach, we examined the association of sleep EEG coherence from these clusters with factors from the infant's family environment. Clusters with greatest coherence were observed over the frontal lobe. Higher delta coherence over the left frontal cortex was found in infants sleeping in their parents' room, while infants sleeping in a room shared with their sibling(s) showed greater delta coherence over the central parts of the frontal cortex, suggesting a link between local brain connectivity and co-sleeping. Finally, lower occipital delta coherence was associated with maternal anxiety regarding their infant's sleep. These interesting links between sleep EEG coherence and family factors have the potential to serve in early health interventions as a new set of targets from the child's immediate environment.

Sex differences within sleep in gonadally intact rats

Sleep impacts diverse physiological and neural processes and is itself affected by the menstrual cycle; however, few studies have examined the effects of the estrous cycle on sleep in rodents. Studies of disease mechanisms in females therefore lack critical information regarding estrous cycle influences on relevant sleep characteristics. We recorded electroencephalographic (EEG) activity from multiple brain regions to assess sleep states as well as sleep traits such as spectral power and interregional spectral coherence in freely cycling females across the estrous cycle and compared with males. Our findings show that the high hormone phase of proestrus decreases the amount of nonrapid eye movement (NREM) sleep and rapid eye movement (REM) sleep and increases the amount of time spent awake compared with other estrous phases and to males. This spontaneous sleep deprivation of proestrus was followed by a sleep rebound in estrus which increased NREM and REM sleep. In proestrus, spectral power increased in the delta (0.5-4 Hz) and the gamma (30-60 Hz) ranges during NREM sleep, and increased in the theta range (5-9 Hz) during REM sleep during both proestrus and estrus. Slow-wave activity (SWA) and cortical sleep spindle density also increased in NREM sleep during proestrus. Finally, interregional NREM and REM spectral coherence increased during proestrus. This work demonstrates that the estrous cycle affects more facets of sleep than previously thought and reveals both sex differences in features of the sleep-wake cycle related to estrous phase that likely impact the myriad physiological processes influenced by sleep.

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

STUDY OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Environmental Factors Shape Sleep EEG Connectivity During Early Adolescence

Quantifying the degree to which genetic and environmental factors shape brain network connectivity is critical to furthering our understanding of the developing human brain. Sleep, a state of sensory disengagement, provides a unique opportunity to study brain network activity noninvasively by means of sleep electroencephalography (EEG) coherence. We conducted a high-density sleep EEG study in monozygotic (MZ; n = 38; mean age = 12.46; 20 females) and dizygotic (DZ; n = 24; mean age = 12.50; 12 females) twins to assess the heritability of sleep EEG coherence in early adolescence—a period of significant brain rewiring. Structural equation modeling was used to estimate three latent factors: genes, environmental factors shared between twins and environmental factors unique to each twin. We found a strong contribution of unique environmental factors (66% of the variance) and moderate genetic influence (19% of the variance) on sleep EEG coherence across frequencies and sleep states. An exception to this was sleep spindle activity, an index of the thalamocortical network, which showed on average a genetic contribution of 48% across connections. Furthermore, we observed high intraindividual stability of coherence across two consecutive nights suggesting that despite only a modest genetic contribution, sleep EEG coherence is like a trait. Our findings in adolescent humans are in line with earlier findings in animals that show the primordial cerebral map and its connections are plastic and it is through interaction with the environment that the pattern of brain network connectivity is shaped. Therefore, even in twins living together, small differences in the environment may cascade into meaningful differences in brain connectivity.

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.

Maturation changes the excitability and effective connectivity of the frontal lobe: A developmental TMS-EEG study

The combination of transcranial magnetic stimulation with simultaneous electroencephalography (TMS-EEG) offers direct neurophysiological insight into excitability and connectivity within neural circuits. However, there have been few developmental TMS-EEG studies to date, and they all have focused on primary motor cortex stimulation. In the present study, we used navigated high-density TMS-EEG to investigate the maturation of the superior frontal cortex (dorsal premotor cortex [PMd]), which is involved in a broad range of motor and cognitive functions known to develop with age. We demonstrated that reactivity to frontal cortex TMS decreases with development. We also showed that although frontal cortex TMS elicits an equally complex TEP waveform in all age groups, the statistically significant between-group differences in the topography of the TMS-evoked peaks and differences in current density maps suggest changes in effective connectivity of the right PMd with maturation. More generally, our results indicate that direct study of the brain's excitability and effective connectivity via TMS-EEG co-registration can also be applied to pediatric populations outside the primary motor cortex, and may provide useful information for developmental studies and studies on developmental neuropsychiatric disorders.

Sleep spindles in adolescence: a comparison across sleep restriction and sleep extension

BACKGROUND

The tendency for adolescents to have restricted sleep has been examined in numerous studies; however, the impact of sleep restriction on adolescents' neural activity during sleep (measured by electroencephalography (EEG)) is less extensively researched, particularly regarding sleep spindles.

METHODS

In this experimental study, 34 adolescents attended a 10-day laboratory study where they received five consecutive nights of either 5 h, 7.5 h or 10 h of sleep opportunity, with one adaptation, one baseline and two recovery nights of 10 h of sleep opportunity before and after the experimental phase.

RESULTS

Both within- and between-subjects effects were observed for fast sleep spindle characteristics of density, duration and amplitude. Overall, when experiencing severe sleep restriction, fast spindles in adolescents were lower in amplitude and longer in duration. Sex differences were also seen for fast spindle amplitude.

CONCLUSIONS

This investigation adds to the knowledge in this field by investigating specific sleep spindle characteristics in the context of experimentally manipulated sleep. Sleep restriction is highly prevalent among adolescents. These findings indicate that chronic sleep restriction has an impact on brain activity related to sleep spindles.

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.

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

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

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

Background

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

Methods

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

Findings

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

Interpretation

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

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

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

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

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