Evidence that electroencephalography (EEG) slow-wave activity (SWA) (EEG spectral power in the 1–4.5 Hz band) during non-rapid eye movement sleep (NREM) reflects plastic changes is increasing (Tononi and Cirelli, 2006). Regional assessment of gray matter development from neuroimaging studies reveals a posteroanterior trajectory of cortical maturation in the first three decades of life (Shaw et al., 2008). Our aim was to test whether this regional cortical maturation is reflected in regional changes of sleep SWA. We evaluated all-night high-density EEG (128 channels) in 55 healthy human subjects (2.4–19.4 years) and assessed age-related changes in NREM sleep topography. As in adults, we observed frequency-specific topographical distributions of sleep EEG power in all subjects. However, from early childhood to late adolescence, the location on the scalp showing maximal SWA underwent a shift from posterior to anterior regions. This shift along the posteroanterior axis was only present in the SWA frequency range and remained stable across the night. Changes in the topography of SWA during sleep parallel neuroimaging study findings indicating cortical maturation starts early in posterior areas and spreads rostrally over the frontal cortex. Thus, SWA might reflect the underlying processes of cortical maturation. In the future, sleep SWA assessments may be used as a clinical tool to detect aberrations in cortical maturation.

Deep (slow wave) sleep shows extensive maturational changes from childhood through adolescence, which is reflected in a decrease of sleep depth measured as the activity of electroencephalographic (EEG) slow waves. This decrease in sleep depth is paralleled by massive synaptic remodeling during adolescence as observed in anatomical studies, which supports the notion that adolescence represents a sensitive period for cortical maturation. To assess the relationship between slow-wave activity (SWA) and cortical maturation, we acquired sleep EEG and magnetic resonance imaging data in children and adolescents between 8 and 19 years. We observed a tight relationship between sleep SWA and a variety of indexes of cortical maturation derived from magnetic resonance (MR) images. Specifically, gray matter volumes in regions correlating positively with the activity of slow waves largely overlapped with brain areas exhibiting an age-dependent decrease in gray matter. The positive relationship between SWA and cortical gray matter was present also for power in other frequency ranges (theta, alpha, sigma, and beta) and other vigilance states (theta during rapid eye movement sleep). Our findings indicate a strong relationship between sleep EEG activity and cortical maturation. We propose that in particular, sleep SWA represents a good marker for structural changes in neuronal networks reflecting cortical maturation during adolescence.

Slow waves, a major electrophysiological characteristic of non-rapid eye movement sleep, undergo prominent changes across puberty. This study provides a detailed description of sleep slow waves of prepubertal children and mature adolescents to better understand the mechanisms underlying the decrease of activity in the slow-wave frequency range across puberty. All-night sleep electroencephalographic recordings were performed for baseline and after sleep deprivation. N/A. Eight prepubertal children (Tanner 1/2, 11.9 ± 0.8 years, 3 boys) and 6 mature adolescents (Tanner 4/5,14.3 ± 1.4 years, 3 boys). Thirty-six hours of sleep deprivation. Both during baseline and after sleep deprivation, a steeper slope of slow waves was observed in prepubertal children (351.0 ± 49.5 µV/s), compared with mature adolescents (215.0 ± 27.2 µV/s, P < 0.05; mean of first 5 NREM sleep episodes from baseline), even accounting for overall amplitude differences. Based on a recent thalamocortical computer model, these findings may indicate a greater synaptic strength of neurons involved in the generation of sleep slow waves in prepubertal children, compared with mature adolescents. Such increased synaptic strength may be due to greater density or greater efficacy of cortical synapses or both.

To investigate the within-subject stability in the sleep EEG and the association between the sleep EEG and intellectual abilities in 9- to 12-year-old children. Intellectual ability (WISC-IV, full scale, fluid, and verbal IQ, working memory, speed of processing) were examined and all-night polysom-nography was performed (2 nights per subject). Sleep laboratory. Fourteen healthy children (mean age 10.5 ± 1.0 years; 6 girls). Spectral analysis was performed on artifact-free NREM sleep epochs (C3/A2). To determine intra-individual stability and inter-individual variability of the sleep EEG, power spectra were used as feature vectors for the estimation of Euclidean distances, and intra-class correlation coeffcients (ICC) were calculated for the 2 nights. Sleep spindle peaks were identifed for each individual and individual sigma band power was determined. Trait-like aspects of the sleep EEG were observed for sleep stage variables and spectral power. Within-subject distances were smaller than between-subject distances and ICC values ranged from 0.72 to 0.96. Correlations between spectral power in individual frequency bins and intelligence scores revealed clusters of positive associations in the alpha, sigma, and beta range for full scale IQ, fluid IQ, and working memory. Similar to adults, sigma power correlated with full scale (r = 0.67) and fluid IQ (r = 0.65), but not with verbal IQ. Spindle peak frequency was negatively related to full scale IQ (r = -0.56). The sleep EEG during childhood shows high within-subject stability and may be a marker for intellectual ability.

Experience-dependent plasticity, the ability of the brain to constantly adapt to an ever-changing environment, has been suggested to be highest during childhood and to decline thereafter. However, empirical evidence for this is rather scarce. Slow-wave activity (SWA; EEG activity of 1–4.5 Hz) during deep sleep can be used as a marker of experience-dependent plasticity. For example, performing a visuomotor adaptation task in adults increased SWA during subsequent sleep over a locally restricted region of the right parietal cortex, which is known to be involved in visuomotor adaptation. Here, we investigated whether local experience-dependent changes in SWA vary as a function of brain maturation. Three age groups (children, adolescents, and adults) participated in a high-density EEG study with two conditions (baseline and adaptation) of a visuomotor learning task. Compared with the baseline condition, sleep SWA was increased after visuomotor adaptation in a cluster of eight electrodes over the right parietal cortex. The local boost in SWA was highest in children. Baseline SWA in the parietal cluster and right parietal gray matter volume, which both indicate region-specific maturation, were significantly correlated with the local increase in SWA. Our findings indicate that processes of brain maturation favor experience-dependent plasticity and determine how sensitive a specific brain region is for learning experiences. Moreover, our data confirm that SWA is a highly sensitive tool to map maturational differences in experience-dependent plasticity.