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The aim of this study is to validate the Italian version of the Pittsburgh Sleep Quality Index (PSQI), comparing five different groups of individuals (healthy young and elderly, sleep apnoea syndrome patients, depressed patients, individuals with dementia) by both questionnaire scores and polysomnographic measures. Fifty individuals (10 for each group) participated in the study. Each of them filled in the PSQI and slept for two consecutive nights in the sleep laboratory. The PSQI showed an overall reliability coefficient (Cronbach's α) of 0.835, indicating a high degree of internal consistency. The mean PSQI global score showed significant differences between groups, with an impaired overall quality of sleep in patients' groups with respect to both the healthy groups. Results also indicated that the best cut-off score (differentiating "good" from "bad" sleepers) is 5. Pittsburgh Sleep Quality Index is a useful, valid and reliable tool for the assessment of sleep quality, with an overall efficiency comparable to the mother language version and differentiate "good" from "bad" sleepers. The Italian version of the questionnaire provides a good and reliable differentiation between normal and pathological groups, with higher scores reported by people characterized by impaired objectively evaluated sleep quality.

In the last decade, combined transcranial magnetic stimulation (TMS)-neuroimaging studies have greatly stimulated research in the field of TMS and neuroimaging. Here, we review how TMS can be combined with various neuroimaging techniques to investigate human brain function. When applied during neuroimaging (online approach), TMS can be used to test how focal cortex stimulation acutely modifies the activity and connectivity in the stimulated neuronal circuits. TMS and neuroimaging can also be separated in time (offline approach). A conditioning session of repetitive TMS (rTMS) may be used to induce rapid reorganization in functional brain networks. The temporospatial patterns of TMS-induced reorganization can be subsequently mapped by using neuroimaging methods. Alternatively, neuroimaging may be performed first to localize brain areas that are involved in a given task. The temporospatial information obtained by neuroimaging can be used to define the optimal site and time point of stimulation in a subsequent experiment in which TMS is used to probe the functional contribution of the stimulated area to a specific task. In this review, we first address some general methodologic issues that need to be taken into account when using TMS in the context of neuroimaging. We then discuss the use of specific brain mapping techniques in conjunction with TMS. We emphasize that the various neuroimaging techniques offer complementary information and have different methodologic strengths and weaknesses.

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Humans have an individual profile of the electroencephalographic power spectra at the 8 to 16 Hz frequency during non-rapid eye movement sleep that is stable over time and resistant to experimental perturbations. We tested the hypothesis that this electroencephalographic "fingerprint" is genetically determined, by recording 40 monozygotic and dizygotic twins during baseline and recovery sleep after prolonged wakefulness. We show a largely greater similarity within monozygotic than dizygotic pairs, resulting in a heritability estimate of 96%, not influenced by sleep need and intensity. If replicated, these results will establish the electroencephalographic profile during sleep as one of the most heritable traits of humans.

COVID-19 has critically impacted the world. Recent works have found substantial changes in sleep and mental health during the COVID-19 pandemic. Dreams could give us crucial information about people's well-being, so here we have directly investigated the consequences of lockdown on the oneiric activity in a large Italian sample: 5,988 adults completed a web-survey during lockdown. We investigated sociodemographic and COVID-19-related information, sleep quality (by the Medical Outcomes Study-Sleep Scale), mental health (by the Depression, Anxiety, and Stress Scales), dream and nightmare frequency, and related emotional aspects (by the Mannheim Dream Questionnaire). Comparisons between our sample and a population-based sample revealed that Italians are having more frequent nightmares and dreams during the pandemic. A multiple logistic regression model showed the predictors of high dream recall (young age, female gender, not having children, sleep duration) and high nightmare frequency (young age, female gender, modification of napping, sleep duration, intrasleep wakefulness, sleep problem index, anxiety, depression). Moreover, we found higher emotional features of dream activity in workers who have stopped working, in people who have relatives/friends infected by or who have died from COVID-19 and in subjects who have changed their sleep habits. Our findings point to the fact that the predictors of high dream recall and nightmares are consistent with the continuity between sleep mentation and daily experiences. According to the arousal-retrieval model, we found that poor sleep predicts a high nightmare frequency. We suggest monitoring dream changes during the epidemic, and also considering the implications for clinical treatment and prevention of mental and sleep disorders.

Under the assumption that dream recall is a peculiar form of declarative memory, we have hypothesized that (1) the encoding of dream contents during sleep should share some electrophysiological mechanisms with the encoding of episodic memories of the awake brain and (2) recalling a dream(s) after awakening from non-rapid eye movement (NREM) and rapid eye movement (REM) sleep should be associated with different brain oscillations. Here, we report that cortical brain oscillations of human sleep are predictive of successful dream recall. In particular, after morning awakening from REM sleep, a higher frontal 5-7 Hz (theta) activity was associated with successful dream recall. This finding mirrors the increase in frontal theta activity during successful encoding of episodic memories in wakefulness. Moreover, in keeping with the different EEG background, a different predictive relationship was found after awakening from stage 2 NREM sleep. Specifically, a lower 8 -12 Hz (alpha) oscillatory activity of the right temporal area was associated with a successful dream recall. These findings provide the first evidence of univocal cortical electroencephalographic correlates of dream recall, suggesting that the neurophysiological mechanisms underlying the encoding and recall of episodic memories may remain the same across different states of consciousness.