An infant sleep electroencephalographic marker of thalamocortical connectivity predicts behavioral outcome in late infancy

Pediatric sleep electrophysiology: Using polysomnography in developmental cognitive neuroscience

Research suggests a bidirectional relationship between brain and cognitive development and sleep in early childhood. Polysomnography is essential for the investigation of the mechanisms underlying sleep's role in brain and cognitive development. This paper outlines methods for integrating measures of sleep and sleep physiology into cognitive developmental neuroscience research. There are various options when choosing a polysomnography system depending on the research question. We offer considerations such as application time, recording time, montage density and analysis options, and cost. We also review suggestions for modifying procedures with developmental populations to support high quality polysomnography data collection. We hope that this overview will facilitate more developmental cognitive neuroscience studies of sleep to advance our understanding of early brain and cognitive development.

NapBiome trial: Targeting gut microbiota to improve sleep rhythm and developmental and behavioural outcomes in early childhood in a birth cohort in Switzerland - a study protocol

INTRODUCTION

The gut-brain axis plays a crucial role in the regulation and development of psychological and physical processes. The first year of life is a critical period for the development of the gut microbiome, which parallels important milestones in establishing sleep rhythm and brain development. Growing evidence suggests that the gut microbiome influences sleep, cognition and early neurodevelopment. For term-born and preterm-born infants, difficulties in sleep regulation may have consequences on health. Identifying effective interventions on the gut-brain axis in early life is likely to have long-term implications for the health and development of at-risk infants.

METHODS AND ANALYSES

In this multicentre, four-group, double-blinded, placebo (PLC)-controlled randomised trial with a factorial design, 120 preterm-born and 260 term-born infants will be included. The study will investigate whether the administration of daily synbiotics or PLC for a duration of 3 months improves sleep patterns and neurodevelopmental outcomes up to 2 years of age. The trial will also: (1) determine the association between gut microbiota, sleep patterns and health outcomes in children up to 2 years of age; and (2) leverage the interactions between gut microbiota, brain and sleep to develop new intervention strategies for at-risk infants.

ETHICS AND DISSEMINATION

The NapBiome trial has received ethical approval by the Committee of Northwestern and Central Switzerland and Canton Vaud, Switzerland (#2024-01681). Outcomes will be disseminated through publication and will be presented at scientific conferences. Metagenomic data will be shared through the European Nucleotide Archive.

TRIAL REGISTRATION NUMBER

The US National Institutes of Health NCT06396689.

Infant sleep EEG features at 4 months as biomarkers of neurodevelopment at 18 months

BACKGROUND

Sleep parameters evolve in parallel with neurodevelopment. Sleep participates in synaptic homeostasis and memory consolidation and infant sleep parameters correlate with later aspects of early childhood cognition.

METHODS

Typically developing, term-born infants had a diurnal sleep-EEG at 4 months and Griffiths III developmental assessment at 18 months. EEG analysis included sleep macrostructure (i.e. durations of total sleep and sleep stages, and latencies to sleep and REM), sleep spindle features, and quantitative EEG features (qEEG): interhemispheric connectivity and spectral power. We assessed the correlations between these EEG features and Griffiths III quotients.

RESULTS

Sleep recordings from 92 infants were analyzed. Sleep latency was positively associated with the Griffiths III Foundations of Learning subscale and N3 sleep duration was positively correlated with the Personal-Social-Emotional subscale. Sleep spindle synchrony was negatively associated with Eye and Hand Coordination, Personal-Social-Emotional, Gross Motor, and General Development quotients. Sleep spindle duration was negatively associated with the Personal-Social-Emotional and Gross Motor subscales. In some sleep states, delta 1 and 2 EEG spectral power and interhemispheric coherence measures were correlated with subscale quotients.

CONCLUSION

Certain sleep features in the EEG of 4-month-old infants are associated with neurodevelopment at 18 months and may be useful early biomarkers of neurodevelopment.

IMPACT

This study shows that the EEG during infant sleep may provide insights into later neurodevelopmental outcomes. We have examined novel EEG sleep spindle features and shown that spindle duration and synchrony may help predict neurodevelopmental outcomes. Sleep macrostructure elements such as latency to sleep, N3 duration, and qEEG features such as interhemispheric coherence and spectral power measures at 4 months may be useful for the assessment of future neurodevelopmental outcomes. Due to exceptional neuroplasticity in infancy, EEG biomarkers of neurodevelopment may support early and targeted intervention to optimize outcomes.

The importance of sleep for the developing brain

Purpose of review

This paper summarizes recent research regarding the possible contribution of sleep to brain development. Major milestones in brain development and the methods used to track these changes are reviewed. Changes in sleep, at both behavioral and neural levels, that take place during the same developmental periods are discussed. Finally, a few empirical examples that have contributed new knowledge regarding how sleep contributes to brain development are highlighted.

Recent findings

Empirical examples demonstrating associations between development of sleep and the brain include: predictive associations between SWA topography and myelin development, associations between SWS and hippocampal development, and links between sleep duration and both white matter volume and whole-brain functional connectivity in developing populations.

Summary

There is evidence that sleep is important for the developing brain. However, studies utilizing longitudinal, objective measures of sleep, high-resolution brain imaging, and behavioral measures across developmental are critical for understanding sleep function.

Development of slow oscillation-spindle coupling from infancy to toddlerhood

Sleep has been demonstrated to support memory formation from early life on. The precise temporal coupling of slow oscillations (SOs) with spindles has been suggested as a mechanism facilitating this consolidation process in thalamocortical networks. Here, we investigated the development of sleep spindles and SOs and their coordinate interplay by comparing frontal, central, and parietal electroencephalogram recordings during a nap between infants aged 2-3 months (n = 31) and toddlers aged 14-17 months (n = 49). Spindles and SOs showed quite different maturational patterns between age groups, as to topography, amplitude, and density. Notably, spindle-SO co-occurrence in the infants did not exceed chance levels and was increased to significant levels only in the toddlers. In the infants, the slow SO upstate over frontocortical regions was even associated with a significant decrease in spindles, contrasting with the adult-like increase in spindles seen in toddlers. These results point to an immature processing in thalamocortical networks during sleep in early infancy, possibly diminishing the efficacy of sleep-dependent memory formation at this age.

Color density spectral array findings on continuous EEG during therapeutic hypothermia in children with acute encephalopathy

BACKGROUND

Quantitative EEG is frequently used to monitor children affected by acute encephalopathy (AE), with the expectation of providing comprehensive insights into continuous EEG monitoring. However, the potential of quantitative EEG for estimating outcomes in this context remains unclear. We sought reliable prognostic markers within the color density spectral array (CDSA) of the continuous EEG for AE-affected children undergoing therapeutic hypothermia (TH).

METHODS

This retrospective study analyzed CDSA data from eight scalp electrodes of 15 AE-affected children undergoing TH. Two CDSA features were investigated-high-frequency lines (HFLs) and periodic elevation in the low frequency band (PLFB)-along with the corresponding EEG characteristics. The inter-rater reliability for CDSA was assessed by four pediatric neurologists. Outcomes were grouped into either no/mild or severe decline in motor and cognitive functions, then compared with CDSA features.

RESULTS

The median EEG recording time was 114 (81-151) h per child. While at least 41 % of HFLs corresponded to typical sleep spindles, 94 % of PLFB aligned with cyclic changes in the amplitude of delta/theta waves on the raw EEG. Inter-rater reliability was higher for HFLs than for PLFB (kappa values: 0.69 vs. 0.46). HFLs were significantly more prevalent in children with no/mild decline than in children with severe decline (p = 0.017), whereas PLFB did not differ significantly (p = 0.33).

CONCLUSIONS

This study provides preliminary evidence that reduced HFLs on CDSA predict unfavorable outcomes in AE-affected children undergoing TH. This suggests that maintaining high-frequency waves is critical for optimal brain function.

Infant sleep spindle measures from EEG improve prediction of cerebral palsy

OBJECTIVE

Early identification of infants at risk of cerebral palsy (CP) enables interventions to optimize outcomes. Central sleep spindles reflect thalamocortical sensorimotor circuit function. We hypothesized that abnormal infant central spindle activity would predict later contralateral CP.

METHODS

We trained and validated an automated detector to measure spindle rate, duration, and percentage from central electroencephalogram (EEG) channels in high-risk infants (n = 35) and age-matched controls (n = 42). Neonatal magnetic resonance imaging (MRI) findings, infant motor exam, and CP outcomes were obtained from chart review. Using univariable and multivariable logistic regression models, we examined whether spindle activity, MRI abnormalities, and/or motor exam predicted future contralateral CP.

RESULTS

The detector had excellent performance (F1 = 0.50). Spindle rate (p = 0.005, p = 0.0004), duration (p < 0.001, p < 0.001), and percentage (p < 0.001, p < 0.001) were decreased in hemispheres corresponding to future CP compared to those without. In this cohort, PLIC abnormality (p = 0.004) and any MRI abnormality (p = 0.004) also predicted subsequent CP. After controlling for MRI findings, spindle features remained significant predictors and improved model fit (p < 0.001, all tests). Using both spindle duration and MRI findings had highest accuracy to classify hemispheres corresponding to future CP (F1 = 0.98, AUC 0.999).

CONCLUSION

Decreased central spindle activity improves the prediction of future CP in high-risk infants beyond early MRI or clinical exam alone.

SIGNIFICANCE

Decreased central spindle activity provides an early biomarker for CP.

Sleep-dependent memory consolidation in young and aged brains

Young children and aged individuals are more prone to memory loss than young adults. One probable reason is insufficient sleep-dependent memory consolidation. Sleep timing and sleep-stage duration differ between children and aged individuals compared to adults. Frequent daytime napping and fragmented sleep architecture are common in children and older individuals. Moreover, sleep-dependent oscillations that play crucial roles in long-term memory storage differ among age groups. Notably, the frontal cortex, which is important for long-term memory storage undergoes major structural changes in children and aged subjects. The similarities in sleep dynamics between children and aged subjects suggest that a deficit in sleep-dependent consolidation contributes to memory loss in both age groups.

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.

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.

Lack of association between behavioral development and simplified topographical markers of the sleep EEG in infancy

The sleep EEG mirrors neuronal connectivity, especially during development when the brain undergoes substantial rewiring. As children grow, the slow-wave activity (SWA; 0.75-4.25 Hz) spatial distribution in their sleep EEG changes along a posterior-to-anterior gradient. Topographical SWA markers have been linked to critical neurobehavioral functions, such as motor skills, in school-aged children. However, the relationship between topographical markers in infancy and later behavioral outcomes is still unclear. This study aims to explore reliable indicators of neurodevelopment in infants by analyzing their sleep EEG patterns. Thirty-one 6-month-old infants (15 female) underwent high-density EEG recordings during nighttime sleep. We defined markers based on the topographical distribution of SWA and theta activity, including central/occipital and frontal/occipital ratios and an index derived from local EEG power variability. Linear models were applied to test whether markers relate to concurrent, later, or retrospective behavioral scores, assessed by the parent-reported Ages & Stages Questionnaire at ages 3, 6, 12, and 24 months. Results indicate that the topographical markers of the sleep EEG power in infants were not significantly linked to behavioral development at any age. Further research, such as longitudinal sleep EEG in newborns, is needed to better understand the relationship between these markers and behavioral development and assess their predictive value for individual differences.