Patients suffering from disorders of consciousness still present a diagnostic challenge due to the fact that their assessment is mainly based on behavioral scales with their motor responses often being strongly impaired. We therefore focused on resting electroencephalography (EEG) in order to reveal potential alternative measures of the patient's current state independent of rather complex abilities (e.g., language comprehension). Resting EEG was recorded in nine minimally conscious state (MCS) and eight vegetative state/unresponsive wakefulness syndrome (VS/UWS) patients. Behavioral assessments were conducted using the Coma-Recovery Scale-Revised (CRS-R). The signal was analyzed in the frequency domain and association between resting EEG and CRS-R score as well as clinical diagnosis were calculated using Pearson correlation and repeated-measures ANOVAs. The analyses revealed robust positive correlations between CRS-R score and ratios between frequencies above 8 Hz and frequencies below 8 Hz. Furthermore, the frequency of the spectral peak was also highly indicative of the patient's CRS-R score. Concerning differences between clinical diagnosis and healthy controls, it could be revealed that while VS/UWS patients showed higher delta and theta activity than controls, MCS did not differ from controls in this frequency range. Alpha activity, on the other hand, was strongly decreased in both patient groups as compared to controls. The strong relationship between various resting EEG parameters and CRS-R score provides significant clinical relevance. Not only is resting activity easily acquired at bedside, but furthermore, it does not depend on explicit cooperation of the patient. Especially in cases where behavioral assessment is difficult or ambiguous, spectral analysis of resting EEG can therefore complement clinical diagnosis.

Sleep has been shown to facilitate the consolidation of newly acquired motor memories in adults. However, the role of sleep in motor memory consolidation is less clear in children and adolescents, especially concerning real‐life gross‐motor skills. Therefore, we investigated the effects of sleep and wakefulness on a complex gross‐motor adaptation task by using a bicycle with an inverse steering device. A total of 29 healthy adolescents aged between 11 and 14 years (five female) were either trained to ride an inverse steering bicycle (learning condition) or a stationary bicycle (control condition). Training took place in the morning (wake, n = 14) or in the evening (sleep, n = 15) followed by a 9‐hr retention interval and a subsequent re‐test session. Slalom cycling performance was assessed by speed (riding time) and accuracy (standard deviation of steering angle) measures. Behavioural results showed no evidence for sleep‐dependent memory consolidation. However, overnight gains in accuracy were associated with an increase in left hemispheric N2 slow sleep spindle activity from control to learning night. Furthermore, decreases in REM and tonic REM duration were related to higher overnight improvements in accuracy. Regarding speed, an increase in REM and tonic REM duration was favourable for higher overnight gains in riding time. Thus, although not yet detectable on a behavioural level, sleep seemed to play a role in the acquisition of gross‐motor skills. A promising direction for future research is to focus on the possibility of delayed performance gains in adolescent populations.

Previously, we demonstrated that precise temporal coordination between slow oscillations (SOs) and sleep spindles indexes declarative memory network development (Hahn et al., 2020). However, it is unclear whether these findings in the declarative memory domain also apply in the motor memory domain. Here, we compared adolescents and adults learning juggling, a real-life gross-motor task. Juggling performance was impacted by sleep and time of day effects. Critically, we found that improved task proficiency after sleep lead to an attenuation of the learning curve, suggesting a dynamic juggling learning process. We employed individualized cross-frequency coupling analyses to reduce inter- and intragroup variability of oscillatory features. Advancing our previous findings, we identified a more precise SO–spindle coupling in adults compared to adolescents. Importantly, coupling precision over motor areas predicted overnight changes in task proficiency and learning curve, indicating that SO–spindle coupling relates to the dynamic motor learning process. Our results provide first evidence that regionally specific, precisely coupled sleep oscillations support gross-motor learning.

Smartphone usage strongly increased in the last decade, especially before bedtime. There is growing evidence that short-wavelength light affects hormonal secretion, thermoregulation, sleep and alertness. Whether blue light filters can attenuate these negative effects is still not clear. Therefore, here, we present preliminary data of 14 male participants (21.93 ± 2.17 years), who spent three nights in the sleep laboratory, reading 90 min either on a smartphone (1) with or (2) without a blue light filter, or (3) on printed material before bedtime. Subjective sleepiness was decreased during reading on a smartphone, but no effects were present on evening objective alertness in a GO/NOGO task. Cortisol was elevated in the morning after reading on the smartphone without a filter, which resulted in a reduced cortisol awakening response. Evening melatonin and nightly vasodilation (i.e., distal-proximal skin temperature gradient) were increased after reading on printed material. Early slow wave sleep/activity and objective alertness in the morning were only reduced after reading without a filter. These results indicate that short-wavelength light affects not only circadian rhythm and evening sleepiness but causes further effects on sleep physiology and alertness in the morning. Using a blue light filter in the evening partially reduces these negative effects.