Precise temporal coordination of slow oscillations (SO) and sleep spindles is a fundamental mechanism of sleep-dependent memory consolidation. SO and spindle morphology changes considerably throughout development. Critically, it remains unknown how the precise temporal coordination of these two sleep oscillations develops during brain maturation and whether their synchronization indexes the development of memory networks. Here, we use a longitudinal study design spanning from childhood to adolescence, where participants underwent polysomnography and performed a declarative word-pair learning task. Performance on the memory task was better during adolescence. After disentangling oscillatory components from 1/f activity, we found frequency shifts within SO and spindle frequency bands. Consequently, we devised an individualized cross-frequency coupling approach, which demonstrates that SO-spindle coupling strength increases during maturation. Critically, this increase indicated enhanced memory formation from childhood to adolescence. Our results provide evidence that improved coordination between SOs and spindles indexes the development of sleep-dependent memory networks.

The present study aimed at identifying the neurophysiological responses associated with auditory stimulation during non-rapid eye movement (NREM) sleep using simultaneous electroencephalography (EEG)/functional magnetic resonance imaging (fMRI) recordings. It was reported earlier that auditory stimuli produce bilateral activation in auditory cortex, thalamus, and caudate during both wakefulness and NREM sleep. However, due to the spontaneous membrane potential fluctuations cortical responses may be highly variable during NREM. Here we now examine the modulation of cerebral responses to tones depending on the presence or absence of sleep spindles and the phase of the slow oscillation. Thirteen healthy young subjects were scanned successfully during stage 2–4 NREM sleep in the first half of the night in a 3 T scanner. Subjects were not sleep-deprived and sounds were post hoc classified according to (i) the presence of sleep spindles or (ii) the phase of the slow oscillation during (±300 ms) tone delivery. These detected sounds were then entered as regressors of interest in fMRI analyses. Interestingly wake-like responses – although somewhat altered in size and location – persisted during NREM sleep, except during present spindles (as previously published in Dang-Vu et al., 2011) and the negative going phase of the slow oscillation during which responses became less consistent or even absent. While the phase of the slow oscillation did not alter brain responses in primary sensory cortex, it did modulate responses at higher cortical levels. In addition EEG analyses show a distinct N550 response to tones during the presence of light sleep spindles and suggest that in deep NREM sleep the brain is more responsive during the positive going slope of the slow oscillation. The presence of short temporal windows during which the brain is open to external stimuli is consistent with the fact that even during deep sleep meaningful events can be detected. Altogether, our results emphasize the notion that spontaneous fluctuations of brain activity profoundly modify brain responses to external information across all behavioral states, including deep NREM sleep.

Slow sleep spindles (11-13 Hz) in children age 8-11 y are associated with inter-individual differences in general cognitive abilities and learning efficiency.

Sleep spindles are related to sleep-dependent memory consolidation and general cognitive abilities. However, they undergo drastic maturational changes during adolescence. Here we used a longitudinal approach (across 7 years) to explore whether developmental changes in sleep spindle density can explain individual differences in sleep-dependent memory consolidation and general cognitive abilities. Ambulatory polysomnography was recorded during four nights in 34 healthy subjects (24 female) with two nights (baseline and experimental) at initial recording (age range 8-11 years) and two nights at follow-up recording (age range 14-18 years). For declarative learning, participants encoded word pairs with a subsequent recall before and after sleep. General cognitive abilities were measured by the Wechsler Intelligence Scale. Higher slow (11-13 Hz) than fast (13-15 Hz) spindle density at frontal, central, and parietal sites during initial recordings, followed by a shift to higher fast than slow spindle density at central and parietal sites during follow-up recordings, suggest that mature spindle topography develops throughout adolescence. Fast spindle density increases from baseline to experimental night were positively related to sleep-dependent memory consolidation. In addition, we found that the development of fast spindles predicted the improvement in memory consolidation across the two longitudinal measurements, a finding that underlines a crucial role for mature fast spindles for sleep-dependent memory consolidation. Furthermore, slow spindle changes across adolescence were related to general cognitive abilities, a relationship that could indicate the maturation of frontal networks relevant for efficient cognitive processing.

See Thibault et al. (doi:) for a scientific commentary on this article.Neurofeedback has been claimed to have therapeutic efficacy in multiple disorders. In a double-blind, placebo-controlled trial in insomnia, Schabus et al. report that sensorimotor rhythm neurofeedback (12–15 Hz) neither changes the EEG nor objectively improves sleep. While patients do report subjective improvements, these do not differ from those seen with placebo feedback.

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Information processing has been suggested to depend on the current state of the brain as well as stimulus characteristics (e.g. salience). We compared processing of salient stimuli (subject's own names [SONs] and angry voice [AV] stimuli) to processing of unfamiliar names (UNs) and neutral voice (NV) stimuli across different vigilance stages (i.e. wakefulness as well as sleep stages N1 and N2) by means of event-related oscillatory responses during wakefulness and a subsequent afternoon nap. Our findings suggest that emotional prosody and self-relevance drew more attentional resources during wakefulness with specifically AV stimuli being processed more strongly. During N1, SONs were more arousing than UNs irrespective of prosody. Moreover, emotional and self-relevant stimuli evoked stronger responses also during N2 sleep suggesting a 'sentinel processing mode' of the brain during this state of naturally occurring unconsciousness. Finally, this initial preferential processing of salient stimuli during N2 sleep seems to be followed by an inhibitory sleep-protecting process, which is reflected by a K-complex-like response.

Based on physiological models of neurovisceral integration, different studies have shown how cognitive processes modulate heart rate and how the heartbeat, on the other hand, modulates brain activity. We tried to further determine interactions between cardiac and electrical brain activity by means of EEG. We investigated how the heartbeat modulates EEG in 23 healthy controls from wakefulness to deep sleep and showed that frontocentral heartbeat evoked EEG amplitude and phase locking (as measured by intertrial phase locking), at about 300-400 ms after the R peak, decreased with increasing sleep depth with a renewed increase during REM sleep, which underpins the assumption that the heartbeat evoked positivity constitutes an active frontocortical response to the heartbeat. Additionally, we found that individual heart rate was correlated with the frequency of the EEG's spectral peak (i.e., alpha peak frequency during wakefulness). This correlation was strongest during wakefulness and declined linearly with increasing sleep depth. Furthermore, we show that the QRS complex modulates spindle phase possibly related to the correspondence between the frequency of the QRS complex and the spindle frequency of about 12-15 Hz. Finally, during deep sleep stages, a loose temporal coupling between heartbeats and slow oscillation (0.8 Hz) could be observed. These findings indicate that cardiac activity such as heart rate or individual heartbeats can modulate or be modulated by ongoing oscillatory brain activity.