How COVID-19 Affected Sleep Talking Episodes, Sleep and Dreams?

BACKGROUND: The COVID-19 pandemic increased symptoms of stress and anxiety and induced changes in sleep quality, dream activity, and parasomnia episodes. It has been shown that stressful factors and/or bad sleep habits can affect parasomnia behaviors. However, investigations on how COVID-19 has affected sleep, dreams, and episode frequency in parasomnias are rare. The current study focuses on the impact of the pandemic on a specific parasomnia characterized by speech production (sleep talking, ST). METHODS: We selected 27 participants with frequent ST episodes (STs) during the pandemic and compared them with 27 participants with frequent STs from a previous study conducted during a pre-pandemic period. All participants performed home monitoring through sleep logs and recorded their nocturnal STs for one week. RESULTS: We observed a higher frequency of STs in the pandemic group. Moreover, STs were related to the emotional intensity of dreams, independent of the pandemic condition. The pandemic was associated with lower bizarreness of dreams in the pandemic group. There were no differences in sleep variables between the two groups. CONCLUSION: Overall, these results suggest a stressful effect of COVID-19 on the frequency of STs. Both the pandemic and the frequency of STs affect qualitative characteristics of dreams in this population.

Longitudinal Findings on the Oneiric Activity Changes Across the Pandemic.

Purpose: COVID-19 pandemic waves have strongly influenced individuals' behaviors and mental health. Here, we analyzed longitudinal data collected in the Spring 2020 and 2021 from a large Italian sample with the aim of assessing changes in dream features between the first and third wave. Specifically, we evaluated the modifications of pandemic dream activity as a function of the general distress variations over time. Also, we detected the best explanatory variables of nightmare frequency and distress. Materials and Methods: Participants previously involved in the web survey during the first wave of the pandemic were asked to complete a new online survey on sleep and dream features available in Spring 2021 (N=728). Subjects decreasing their level of psychological general distress in the third (T3) vs the first (T1) pandemic wave were defined as "Improved" (N=330). In contrast, participants with an unchanged or increased level of general distress were defined as "Not Improved" (N=398). Results: Statistical comparisons revealed that dream recall frequency, nightmare frequency, lucid dream frequency, and emotional intensity show a reduction in T3 than T1. Moreover, the Improved group is characterized by lower nightmare rate and nightmare distress than Not Improved people. Our findings confirmed that beyond the trait-like variables (ie, age, sex), specific sleep-related measures are related to nightmare features. In particular, poor sleep hygiene was one of the best determinants of nightmare distress among Not Improved subjects. Conclusion: Our findings revealed that people experienced an adaptation to the pandemic during the third wave. We also strengthen the notion that nightmares and their variations over time are strongly related to human well-being, suggesting that specific trait-like and sleep-related factors could modulate the relationship between mental health and nightmare features.

The Influence of Sleep Talking on Nocturnal Sleep and Sleep-Dependent Cognitive Processes.

BACKGROUND: Sleep talking (ST) is characterized by the production of unaware verbal vocal activations (VBs) during sleep. ST seems potentially linked to linguistic and memory consolidation processes. However, sleep and dream characteristics and the relationship between verbal vocalizations (VBs) and cognitive functions are still unknown. Our study aimed to investigate qualitative sleep and dream features in sleep talkers (STs) compared to healthy subjects (CNTs) through retrospective and longitudinal measures and explore the relationship between ST and memory consolidation. METHODS: We recruited N = 29 STs and N = 30 CNTs (age range of 18-35). Participants recorded their dreams and filled out sleep logs for seven consecutive days. Vocal activations of STs were audio-recorded. On the eighth day, we administered a word-pair task. RESULTS: We showed that STs had significantly worse self-reported sleep quality. VBs were positively correlated with sleep fragmentation and negatively associated with the oneiric emotional load. No difference between groups was found in the memory consolidation rate. CONCLUSIONS: Although ST is a benign phenomenon, we revealed that ST is associated with more sleep alterations and lower emotional intensity of dreams. In this vein, we support that ST depends on sleep fragmentation and could represent a potential window into sleep-dependent cognitive processes.

Sleep talking versus sleep moaning: electrophysiological patterns preceding linguistic vocalizations during sleep.

STUDY OBJECTIVES: Sleep talking (ST) has been rarely studied as an isolated phenomenon. Late investigations over the psycholinguistic features of vocal production in ST pointed to coherence with wake language formal features. Therefore, we investigated the EEG correlates of Verbal ST as the overt manifestation of sleep-related language processing, with the hypothesis of shared electrophysiological correlates with wake language production. METHODS: From a sample of 155 Highly frequent STs, we recorded 13 participants (age range 19-30 years, mean age 24.6 ± 3.3; 7F) via vPSG for at least two consecutive nights, and a total of 28 nights. We first investigated the sleep macrostructure of STs compared to 13 age and gender-matched subjects. We then compared the EEG signal before 21 Verbal STs versus 21 Nonverbal STs (moaning, laughing, crying, etc.) in six STs reporting both vocalization types in Stage 2 NREM sleep. RESULTS: The 2 × 2 mixed analysis of variance Group × Night interaction showed no statistically significant effect for macrostructural variables, but significant main effects for Group with lower REM (%), total sleep time, total bedtime, sleep efficiency index, and greater NREM (%) for STs compared to controls. EEG statistical comparisons (paired-samples Student's t-test) showed a decrement in power spectra for Verbal STs versus Nonverbal STs within the theta and alpha EEG bands, strongly lateralized to the left hemisphere and localized on centro-parietal-occipitals channels. A single left parietal channel (P7) held significance after Bonferroni correction. CONCLUSIONS: Our results suggest shared neural mechanisms between Verbal ST and language processing during wakefulness and a possible functional overlapping with linguistic planning in wakefulness.

Age-Related Effect of Sleepiness on Driving Performance: A Systematic-Review.

BACKGROUND: Several studies highlighted that sleepiness affects driving abilities. In particular, road traffic injuries due to excessive daytime sleepiness are about 10-20%. Considering that aging is related to substantial sleep changes and the number of older adults with driving license is increasing, the current review aims to summarize recent studies on this issue. Further, we intend to provide insights for future research. METHODS: From the 717 records screened, ten articles were selected and systematically reviewed. RESULTS: Among the selected articles, (a) five studies investigated sleepiness only by self-reported standardized measures; (b) two studies assessed sleepiness also using a behavioral task; (c) three studies obtained objective measures by electroencephalographic recordings. CONCLUSIONS: The available literature on the topic reports several limitations. Overall, many findings converge in evidencing that older drivers are less vulnerable to sleep loss and sleepiness-related driving impairments than young adults. These discrepancies in sleepiness vulnerability between age groups may be ascribed to differences in subjects' lifestyles. Moreover, it has been hypothesized that older adults self-regulate their driving and avoid specific dangerous situations. We believe that an easy protocol to objectively evaluate the vigilance level in elderly and young adults is required, and further studies are needed.

EEG Patterns Prior to Motor Activations of Parasomnias: A Systematic Review.

INTRODUCTION: Non-rapid eye movement (NREM) parasomnias are defined as abnormal nocturnal behaviors that typically arise from the NREM sleep stage 3 during the first sleep cycle. The polysomnographic studies showed an increase in sleep fragmentation and an atypical slow wave activity (SWA) in participants with NREM parasomnias compared to healthy controls. To date, the pathophysiology of NREM parasomnias is still poorly understood. The recent investigation of the EEG patterns immediately before parasomnia events could shed light on the motor activations' processes. This systematic review aims to summarize empirical evidence about these studies and provide an overview of the methodological issues. METHODS: A systematic literature search was carried out in PubMed, Web of Science, and Scopus, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The documents obtained were evaluated using the Newcastle-Ottawa Scale (NOS). RESULTS: Nine studies were included in the qualitative synthesis. The major evidence revealed an increased slow frequency EEG activity immediately before the motor activations in frontal and central areas and increased beta activity in the anterior cingulate cortices. DISCUSSION: The investigation of EEG patterns before parasomniac episodes could provide new insight into the study of NREM parasomnia pathophysiology. The high- and low-frequency EEG increase before the episodes could represent a predictive electrophysiological pattern of the motor activations' onset. Overall, identifying specific sleep markers before parasomnias might also help differentiate between NREM parasomnias and other motor sleep disorders. Different methodological protocols should be integrated for overcoming the lack of consistent empirical findings. Thus, future studies should focus on the topographical examination of canonical EEG frequency bands to better understand spatial and time dynamics before the episodes and identify the networks underlying the onset of activations.

Electrophysiological Correlates of Dream Recall During REM Sleep: Evidence from Multiple Awakenings and Within-Subjects Design.

PURPOSE: In the current study, we aimed to investigate the EEG correlates of dream recall (DR) monitoring both the homeostatic and state-trait like factors. We assessed the influence of the time of night on the EEG correlates of DR from REM sleep. Specifically, we tested the continuity-hypothesis (on the theta EEG band) and the activation-hypothesis (on the delta and beta bands). METHODS: Twenty-seven subjects underwent polysomnography with multiple provoked awakenings during REM sleep. Only the subjects showing combinations of dream recall (REC) and non-REC (NREC) conditions in both first (1st-2nd sleep cycle) and second (3rd-4th sleep cycle) part of the night were included in the analyses. The final sample was composed of 10 subjects (mean age 24±0.70). EEG power spectra of the 5-min of REM sleep preceding each awakening were computed by a fast Fourier transform. The following frequency bands were considered: delta (0.50-4.75 Hz), theta (5.00-7.75 Hz), and beta (16.00-24.75 Hz). We also calculated the delta/beta power ratio as an integrated EEG index of activation. RESULTS: The 2×2 within-subjects ANOVA recall × time revealed: a) no significant effect for time and no interaction; b) significant differences over the occipital area in the beta band; c) significant differences over the parietal area for the activation index values. Overall, the results indicated that DR is associated with higher activation regardless of homeostatic pressure across the night of sleep. CONCLUSION: In line with recent findings, we have shown that DR is predicted by desynchronized EEG activity during REM sleep, providing clear evidence in favor of the activation-hypothesis. We have also confirmed that the EEG pattern of DR can be ascribed to state-like factors. Further studies should assess whether homeostatic modulation may interact with some dream features and the related EEG predictors.