Salome Kurth

Mapping of Cortical Activity in the First Two Decades of Life: A High-Density Sleep Electroencephalogram Study

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.

EEG Sleep Slow-Wave Activity as a Mirror of 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.

Mapping the electrophysiological marker of sleep depth reveals skill maturation in children and adolescents.

Electroencephalographically (EEG) recorded slow wave activity (SWA, 1-4.5Hz), reflecting the depth of sleep, is suggested to play a crucial role in synaptic plasticity. Mapping of SWA by means of high-density EEG reveals that cortical regions showing signs of maturational changes (structural and behavioral) during childhood and adolescence exhibit more SWA. Moreover, the maturation of specific skills is predicted by the topographical distribution of SWA. Thus, SWA topography may serve as a promising neuroimaging tool with prognostic potential. Finally, our data suggest that deep sleep SWA in humans is involved in cortical development that optimizes performance.

Topography of sleep slow wave activity in children with attention-deficit/hyperactivity disorder.

INTRODUCTION Sleep slow wave activity (SWA, EEG power between 1 and 4.5 Hz) is a major characteristic of non-rapid eye movement (NREM) sleep, which seems to be critically involved in cortical plasticity. Studies using high-density electroencephalography (hd-EEG) showed that the topographical distribution of SWA mirrors cortical maturation, expressing a local maximum that is characteristic for a certain age range. We compared the sleep EEG of children with attention-deficit/hyperactivity disorder (ADHD) with healthy controls to explore differences in sleep SWA. METHODS All-night hd-EEG recordings (128 electrodes) were performed in a group of nine children diagnosed with ADHD and nine age- and sex-matched healthy controls. SWA topography was calculated and contrasted between the groups. RESULTS We found a local increase of SWA in a cluster of six electrodes over central regions in children with ADHD compared to control children (+17% ± 6% SE, p < .01). This group difference was specific for the SWA range and stable across the night. CONCLUSIONS Children with ADHD showed a less mature topographical SWA distribution in comparison to healthy children of the same age and sex. This neuromaturational delay in ADHD is in accordance with neuroimaging and behavioral studies. Thus, our study supports the use of sleep SWA topography as a reliable imaging tool for the study of cortical plasticity.

Sleep Slow-Wave Activity Reveals Developmental Changes in Experience-Dependent Plasticity

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.

Development of Brain EEG Connectivity across Early Childhood: Does Sleep Play a Role?

Sleep has beneficial effects on brain function and learning, which are reflected in plastic changes in the cortex. Early childhood is a time of rapid maturation in fundamental skills—e.g., language, cognitive control, working memory—that are predictive of future functioning. Little is currently known about the interactions between sleep and brain maturation during this developmental period. We propose coherent electroencephalogram (EEG) activity during sleep may provide unique insight into maturational processes of functional brain connectivity. Longitudinal sleep EEG assessments were performed in eight healthy subjects at ages 2, 3 and 5 years. Sleep EEG coherence increased across development in a region- and frequency-specific manner. Moreover, although connectivity primarily decreased intra-hemispherically across a night of sleep, an inter-hemispheric overnight increase occurred in the frequency range of slow waves (0.8–2 Hz), theta (4.8–7.8 Hz) and sleep spindles (10–14 Hz), with connectivity changes of up to 20% across a night of sleep. These findings indicate sleep EEG coherence reflects processes of brain maturation—i.e., programmed unfolding of neuronal networks—and moreover, sleep-related alterations of brain connectivity during the sensitive maturational window of early childhood.

Anatomical markers of sleep slow wave activity derived from structural magnetic resonance images

Sleep studies often observe differences in slow wave activity (SWA) during non‐rapid eye movement sleep between subjects. This study investigates to what extent these absolute differences in SWA can be explained with differences in grey matter volume, white matter volume or the thickness of skull and outer liquor rooms. To do this, we selected the 10‐min interval showing maximal SWA of 20 young adult subjects and correlated these values lobe‐wise with grey matter, skull and liquor thickness and globally with white matter as well as segments of the corpus callosum. Whereas grey matter, skull thickness and liquor did not correlate significantly with maximal slow wave activity, there were significant correlations with the anterior parts of the corpus callosum and with one other white matter region. In contrast, electroencephalogram power of higher frequencies correlates positively with grey matter volumes and cortical surface area. We discuss the possible role of white matter tracts on the synchronization of slow waves across the cortex.

The effects of caffeine on sleep and maturational markers in the rat.

Adolescence is a critical period for brain maturation during which a massive reorganization of cortical connectivity takes place. In humans, slow wave activity (<4.5 Hz) during NREM sleep was proposed to reflect cortical maturation which relies on use-dependent processes. A stimulant like caffeine, whose consumption has recently increased especially in adolescents, is known to affect sleep wake regulation. The goal of this study was to establish a rat model allowing to assess the relationship between cortical maturation and sleep and to further investigate how these parameters are affected by caffeine consumption. To do so, we assessed sleep and markers of maturation by electrophysiological recordings, behavioral and structural readouts in the juvenile rat. Our results show that sleep slow wave activity follows a similar inverted U-shape trajectory as already known in humans. Caffeine treatment exerted short-term stimulating effects and altered the trajectory of slow wave activity. Moreover, caffeine affected behavioral and structural markers of maturation. Thus, caffeine consumption during a critical developmental period shows long lasting effects on sleep and brain maturation.

Spike wave location and density disturb sleep slow waves in patients with CSWS (continuous spike waves during sleep)

In CSWS (continuous spike waves during sleep) activation of spike waves during slow wave sleep has been causally linked to neuropsychological deficits, but the pathophysiologic mechanisms are still unknown. In healthy subjects, the overnight decrease of the slope of slow waves in NREM (non–rapid eye movement) sleep has been linked to brain recovery to regain optimal cognitive performance. Here, we investigated whether the electrophysiologic hallmark of CSWS, the spike waves during sleep, is related to an alteration in the overnight decrease of the slope, and if this alteration is linked to location and density of spike waves.

Sleep electroencephalography topography and children's intellectual ability.

The aim of the study was to investigate the relationship between regional aspects of the children’s sleep electroencephalogram (EEG) (high-density EEG recordings) and their intellectual ability. The spectral power in the &agr;, &sgr;, and &bgr; frequency ranges of 109 EEG derivations was correlated with the scores of full-scale intelligence quotient, fluid intelligence quotient, and working memory (14 participants, mean age: 10.5±1.0 years; six girls). The previously reported relationship (derivation C3/A2) between spectral band power and intellectual ability could further be refined, particular spatial patterns over central and parietal areas with positive correlations were found. Thus, neurobiological correlates of intelligence during sleep may exhibit brain region-specific patterns.