Dream experience (DE) represents a fascinating condition linked to emotional processes and the human inner world. Although the overlap between REM sleep and dreaming has been overcome, several studies point out that emotional and perceptually vivid contents are more frequent when reported upon awakenings from this sleep stage. Actually, it is well-known that REM sleep plays a pivotal role in the processing of salient and emotional waking-life experiences, strongly contributing to the emotional memory consolidation. In this vein, we highlighted that, to some extent, neuroimaging studies showed that the processes that regulate dreaming and emotional salience in sleep mentation share similar neural substrates of those controlling emotions during wakefulness. Furthermore, the research on EEG correlates of the presence/absence of DE and the results on EEG pattern related to the incorporated memories converged to assign a crucial role of REM theta oscillations in emotional re-processing. In particular, the theta activity is involved in memory processes during REM sleep as well as during the waking state, in line with the continuity hypothesis. Also, the gamma activity seems to be related to emotional processes and dream recall as well as to lucid dreams. Interestingly, similar EEG correlates of DE have been found in clinical samples when nightmares or dreams occur. Research on clinical samples revealed that promoting the rehearsal of frightening contents aimed to change them is a promising method to treat nightmares, and that lucid dreams are associated with an attenuation of nightmares. In this view, DE can defuse emotional traumatic memories when the emotional regulation and the fear extinction mechanisms are compromised by traumatic and frightening events. Finally, dreams could represent a sort of simulation of reality, providing the possibility to create a new scenario with emotional mastery elements to cope with dysphoric items included in nightmares. In addition, it could be hypothesized that the insertion of bizarre items besides traumatic memories might be functional to “impoverish” the negative charge of the experiences.

Several studies have identified two types of sleep spindles: fast (13–15 Hz) centroparietal and slow (11–13 Hz) frontal spindles. Alterations in spindle activity have been observed in Alzheimer’s disease (AD) and Mild Cognitive Impairment (MCI). Only few studies have separately assessed fast and slow spindles in these patients showing a reduction of fast spindle count, but the possible local specificity of this phenomenon and its relation to cognitive decline severity are not clear. Moreover, fast and slow spindle density have never been assessed in AD/MCI. We have assessed fast and slow spindles in 15 AD patients, 15 amnesic MCI patients, and 15 healthy elderly controls (HC). Participants underwent baseline polysomnographic recording (19 cortical derivations). Spindles during nonrapid eye movements sleep were automatically detected, and spindle densities of the three groups were compared in the derivations where fast and slow spindles exhibited their maximum expression (parietal and frontal, resp.). AD and MCI patients showed a significant parietal fast spindle density decrease, positively correlated with Minimental State Examination scores. Our results suggest that AD-related changes in spindle density are specific for frequency and location, are related to cognitive decline severity, and may have an early onset in the pathology development.

The crucial role of sleep in physical and mental health is well known, especially during the developmental period. In recent years, there has been a growing interest in examining the relationship between sleep patterns and school performance in adolescents. At this stage of life, several environmental and biological factors may affect both circadian and homeostatic regulation of sleep. A large part of this population does not experience adequate sleep, leading to chronic sleep restriction and/or disrupted sleep–wake cycles. Studies investigating the effects of different sleep–wake schedules on academic achievement showed that impaired sleep quality and quantity are associated with decreased learning ability and compromised daytime functioning. This review focuses on the most recent studies that evaluated the effects of modified school start time on sleep patterns and related outcomes. Moreover, based on the available empirical evidence, we intend to propose a direction for future studies targeted to implement prevention or treatment programs by modifying sleep timing.

Although a slowing of electroencephalographic (EEG) activity during wakefulness and –to some extent- sleep of Alzheimer disease (AD) patients (i.e., increased slow-frequency activity) was documented, recent findings in healthy elderly show a decreased 0.6–1 Hz slow wave activity (SWA) during NREM, which was associated to β-amyloid deposition and impaired hippocampal memory consolidation. We hypothesize that the apparent contradiction may be explained by the partial overlap between 0.6–1 Hz EEG activity and K-Complex (KC). According to this view, we studied both frontal KCs and SWA in 20 AD patients and 20 healthy age-matched controls (HC) during nightly sleep, under the hypothesis that KCs better discriminate patients from healthy elderly than ≤1 Hz SWA. A drastic decrease of KC density during stage 2 NREM was found in AD compared to HC. Patients show more than 40% reduction of the KC density, allowing a correct classification of 80%. On the other hand, ≤1 Hz SWA of AD patients is slightly (not significantly) higher in most cortical areas compared to HC. Although no significant changes of ≤1 Hz SWA are detectable over frontal areas in AD, KC density decreases over the same location, and its decrease is related to the cognitive decline.

There is a general consensus that sleep is strictly linked to memory, learning, and, in general, to the mechanisms of neural plasticity, and that this link may directly affect recovery processes. In fact, a coherent pattern of empirical findings points to beneficial effect of sleep on learning and plastic processes, and changes in synaptic plasticity during wakefulness induce coherent modifications in EEG slow wave cortical topography during subsequent sleep. However, the specific nature of the relation between sleep and synaptic plasticity is not clear yet. We reported findings in line with two models conflicting with respect to the underlying mechanisms, that is, the “synaptic homeostasis hypothesis” and the “consolidation” hypothesis, and some recent results that may reconcile them. Independently from the specific mechanisms involved, sleep loss is associated with detrimental effects on plastic processes at a molecular and electrophysiological level. Finally, we reviewed growing evidence supporting the notion that plasticity‐dependent recovery could be improved managing sleep quality, while monitoring EEG during sleep may help to explain how specific rehabilitative paradigms work. We conclude that a better understanding of the sleep‐plasticity link could be crucial from a rehabilitative point of view.