Life's Essential 8 Cardiovascular Health Score and Cardiorespiratory Fitness in the Community.

BACKGROUND: The relation of cardiorespiratory fitness (CRF) to lifestyle behaviors and factors linked with cardiovascular health remains unclear. We aimed to understand how the American Heart Association's Life's Essential 8 (LE8) score (and its changes over time) relate to CRF and complementary exercise measures in community-dwelling adults. METHODS AND RESULTS: Framingham Heart Study (FHS) participants underwent maximum effort cardiopulmonary exercise testing for direct quantification of peak oxygen uptake (V̇O2). A 100-point LE8 score was constructed as the average across 8 factors: diet, physical activity, nicotine exposure, sleep, body mass index, lipids, blood glucose, and blood pressure. We related total LE8 score, score components, and change in LE8 score over 8 years with peak V̇O2 (log-transformed) and complementary CRF measures. In age- and sex-adjusted linear models (N=1838, age 54±9 years, 54% women, LE8 score 76±12), a higher LE8 score was associated favorably with peak V̇O2, ventilatory efficiency, resting heart rate, and blood pressure response to exercise (all P<0.0001). A clinically meaningful 5-point higher LE8 score was associated with a 6.0% greater peak V̇O2 (≈1.4 mL/kg per minute at sample mean). All LE8 components were significantly associated with peak V̇O2 in models adjusted for age and sex, but blood lipids, diet, and sleep health were no longer statistically significant after adjustment for all LE8 components. Over an ≈8-year interval, a 5-unit increase in LE8 score was associated with a 3.7% higher peak V̇O2 (P<0.0001). CONCLUSIONS: Higher LE8 score and improvement in LE8 over time was associated with greater CRF, highlighting the importance of the LE8 factors in maintaining CRF.

Correspondence to "association of sleep patterns and cardiovascular disease risk is modified by glucose tolerance status".

After reading the article written by Wang et al., we have encountered several concerns that may compromise the credibility of the article. There are some factors, such as changes in sleep patterns, glucose tolerance status, and the use of hypnotics, which may interfere with the research results. Additionally, the design of the sleep pattern could lead to biased outcomes. Therefore, we are writing this letter to recommend that further research should take these concerns into consideration.

Early sleep intervention for improving infant sleep quality: a randomized controlled trial, preliminary result.

BACKGROUND: Healthy sleep issues should provide to family within first 6 months of infant's life. This study aimed to evaluate the effect of early sleep intervention on nighttime sleep quality. METHODS: Eligible infants aged 4 months ± 2 weeks were randomized to receive early sleep intervention or usual care. Data on sleep variables were obtained via parental interview at baseline and 6 months of age. Using logistic regression to analyze the efficacy of early sleep intervention. RESULTS: At baseline, 335 eligible infants were enrolled and randomized. In total, 306 participants were final analyzed: early sleep intervention group (n = 148) and the usual care group (n = 158). The early sleep intervention group had a significantly longer nighttime sleep duration and a shorter night waking duration than the usual care group (585.20 ± 80.38 min vs. 496.14 ± 87.78 min, p < .001 and 61.01 ± 36.38 min vs. 89.72 ± 45.54 min, p < .001). At 6 months of age, the early sleep intervention group had a longer night sleep duration (≥ 4 h/time) than the usual care group (adjusted odds ratio: 2.39, 95% confidence interval: 1.34-4.28). CONCLUSIONS: Early sleep intervention should be recommended to infants at 4 months of age as a part of well childcare to improve infant sleep quality. TRIAL REGISTRATION: Thai Clinical Trials Registry (thaiclinicaltrial.org). Retrospective registered TCTR20230117001 (17/01/2023).

Self-reported and accelerometry measures of sleep components in adolescents living in Pacific Island countries and territories: Exploring the role of sociocultural background.

OBJECTIVES: The objective of this study is to assess the concordance and its association with sociocultural background of a four-question survey with accelerometry in a multiethnic adolescent population, regarding sleep components. Based on questions from the Pittsburgh Sleep Quality Index and adapted to a school context, the questionnaire focussed on estimating sleep onset time, wake-up time and sleep duration on both weekdays and weekends. This subjective survey was compared with accelerometry data while also considering the influence of sociocultural factors (sex, place of living, ethnic community and socio-economic status). METHODS: Adolescents aged 10.5-16 years (n = 182) in New Caledonia completed the survey and wore an accelerometer for seven consecutive days. Accelerometry was used to determine sleep onset and wake-up time using validated algorithms. Based on response comparison, Bland-Altman plots provided agreement between subjective answers and objective measures. We categorized participants' answers to the survey into underestimated, aligned and overestimated categories based on time discrepancies with accelerometry data. Multinomial regressions highlighted the sociocultural factors associated with discrepancies. RESULTS: Concordance between the accelerometer and self-reported assessments was low particularly during weekends (18%, 26% and 19% aligned for onset sleep time, wake-up time and sleep duration respectively) compared with weekdays (36%, 53% and 31% aligned, respectively). This means that the overall concordance was less than 30%. When considering the sociocultural factors, only place of living was associated with discrepancies in onset sleep time and wake-up time primarily on weekdays. Rural adolescents were more likely to overestimate both onset sleep time (B = -1.97, p < 0.001) and wake-up time (B = -1.69, p = 0.003). CONCLUSIONS: The study found low concordance between self-assessment and accelerometry outputs for sleep components. This was particularly low for weekend days and for participants living in rural areas. While the adapted four-item questionnaire was useful and easy to complete, caution should be taken when making conclusions about sleep habits based solely on this measurement.

Microglial TNFα controls daily changes in synaptic GABAARs and sleep slow waves.

Microglia sense the changes in their environment. How microglia actively translate these changes into suitable cues to adapt brain physiology is unknown. We reveal an activity-dependent regulation of cortical inhibitory synapses by microglia, driven by purinergic signaling acting on P2RX7 and mediated by microglia-derived TNFα. We demonstrate that sleep induces microglia-dependent synaptic enrichment of GABAARs in a manner dependent on microglial TNFα and P2RX7. We further show that microglia-specific depletion of TNFα alters slow waves during NREM sleep and blunt memory consolidation in sleep-dependent learning tasks. Together, our results reveal that microglia orchestrate sleep-intrinsic plasticity of synaptic GABAARs, sculpt sleep slow waves, and support memory consolidation.

Fatigue Risk Management Preferences for Consumer Sleep Technologies and Data Sharing in Aviation.

INTRODUCTION: Employees from any type of aviation services industry were asked to give their opinions about the usefulness of consumer sleep technologies (CSTs) during operations and their willingness to share data from CSTs with their organizations for fatigue risk management purposes under a variety of circumstances.METHODS: Respondents provided information about position in aviation and use of CST devices. Respondents ranked sleep issues and feedback metrics by perceived level of importance to operational performance. Respondents rated their likelihood to share data with their organization under a series of hypothetical situations.RESULTS: Between January-July 2023, 149 (N = 149) aviation professionals responded. Pilots comprised 72% (N = 108) of respondents; 84% (N = 125) of all respondents worked short- or medium-haul operations. "Nighttime operations" and "inconsistent sleep routines" ranked as the most important issues affecting sleep. "Sleep quality history" and "projected alertness levels" ranked as most important feedback metrics for personal management of fatigue. Respondents were split between CST users (N = 64) and nonusers (N = 68). CST users did not indicate a strong preference for a specific device brand. The most-reported reason for not using a CST was due to not owning one or no perceived need. Respondents indicated greater likelihood of data sharing under conditions where the device was provided to them by their organization.DISCUSSION: These results suggest that aviation professionals are more concerned about schedule-related disturbances to sleep than they are about endogenous sleep problems. Organizations may be able to increase compliance to data collection for fatigue risk management by providing employees with company-owned CSTs of any brand.Devine JK, Choynowski J, Hursh SR. Fatigue risk management preferences for consumer sleep technologies and data sharing in aviation. Aerosp Med Hum Perform. 2024; 95(5):265-272.

Large-language models facilitate discovery of the molecular signatures regulating sleep and activity.

Sleep, locomotor and social activities are essential animal behaviors, but their reciprocal relationships and underlying mechanisms remain poorly understood. Here, we elicit information from a cutting-edge large-language model (LLM), generative pre-trained transformer (GPT) 3.5, which interprets 10.2-13.8% of Drosophila genes known to regulate the 3 behaviors. We develop an instrument for simultaneous video tracking of multiple moving objects, and conduct a genome-wide screen. We have identified 758 fly genes that regulate sleep and activities, including mre11 which regulates sleep only in the presence of conspecifics, and NELF-B which regulates sleep regardless of whether conspecifics are present. Based on LLM-reasoning, an educated signal web is modeled for understanding of potential relationships between its components, presenting comprehensive molecular signatures that control sleep, locomotor and social activities. This LLM-aided strategy may also be helpful for addressing other complex scientific questions.

"The worst thing is lying in bed thinking 'I want a cigarette'" a qualitative exploration of smoker's and ex-smoker's perceptions of sleep during a quit attempt and the use of cognitive behavioural therapy for insomnia to aid cessation.

Smokers report poorer sleep quality than non-smokers and sleep quality deteriorates further during cessation, increasing risk of smoking relapse. Despite the use of cognitive behavioural therapy for insomnia (CBT-I) to aid quit attempts emerging in the area, little is known about smokers and ex smoker's experiences of sleep during a quit attempt or their perceptions of CBT-I. This study addresses this gap by exploring smoker's and ex-smoker's experiences of the link between smoking and sleep and how this may change as a function of smoking/smoking abstinence. It also explores views of traditional CBT-I components (i.e., perceived feasibility, effectiveness, barriers of use). We conducted semi-structured interviews with current and recently quit smokers (n = 17) between January and September 2022. The framework method was used for analysis. Four themes addressing research questions were described. These included: 1) A viscous cycle; poor sleep quality and negative psychological state during cessation; 2) Perceived engagement and effectiveness; the importance of feasibility, experience, value, identity and psychological state in assessing CBT-I as a cessation tool; 3) Striking a balance; tailoring CBT-I to reduce psychological overload in a time of lifestyle transition; and 4) Personalisation and digital delivery helping overcome psychological barriers during cessation. The analysis suggested during quit attempts smokers experienced a range of sleep problems that could increase risk of relapse due to a negative impact on psychological state. It also revealed participants thought that CBT-I is something they would use during a quit attempt but suggested changes and additions that would improve engagement and be better tailored to quitting smokers. Key additions included the integration of smoking-based cognitive restructuring, starting the intervention prior to a quit attempt, and the need for personalisation and tailoring.

The 24-h movement behaviours composition is associated with parasympathetic modulation in preschoolers.

AIM: To investigate the associations between 24-h movement behaviours and heart rate variability (HRV) in preschool children. METHODS: A total of 123 preschoolers (4.52 ± 0.25 years old; 62 girls) were assessed for physical activity (PA) and sedentary behaviour (SB) using an accelerometer (Actigraph WGT3x). Sleep duration (SD) was parent-reported. Children were laid down in a supine position for 10 min to assess HRV data. The R-R intervals recorded during the last 5 min of this period were analysed. We conducted compositional analysis in R studio, and the significance level was 95%. All ethical procedures were followed, and the study had the approval of the local ethical board. RESULTS: When considered as a composition, adjusted for age, body mass index and sex, the 24-h movement composition (PA, SB and SD) significantly predicted better parasympathetic modulation (Root mean square of the successive differences [RMSSD] [p = 0.04; r2 = 0.13]), but not high frequency (HF) (nu) (p = 0.51, r2 = 0.01), low frequency (nu) (p = 0.52, r2 = 0.02),or standard deviation (standard deviation of normal-to-normal intervals) (p = 0.55, r2 = 0.02), respectively. CONCLUSION: These results suggest the 24-h movement composition predicted the RMSSD time-domain index related to parasympathetic activity.

Association Between Sleep Quality and Deep Learning-Based Sleep Onset Latency Distribution Using an Electroencephalogram.

To evaluate sleep quality, it is necessary to monitor overnight sleep duration. However, sleep monitoring typically requires more than 7 hours, which can be inefficient in termxs of data size and analysis. Therefore, we proposed to develop a deep learning-based model using a 30 sec sleep electroencephalogram (EEG) early in the sleep cycle to predict sleep onset latency (SOL) distribution and explore associations with sleep quality (SQ). We propose a deep learning model composed of a structure that decomposes and restores the signal in epoch units and a structure that predicts the SOL distribution. We used the Sleep Heart Health Study public dataset, which includes a large number of study subjects, to estimate and evaluate the proposed model. The proposed model estimated the SOL distribution and divided it into four clusters. The advantage of the proposed model is that it shows the process of falling asleep for individual participants as a probability graph over time. Furthermore, we compared the baseline of good SQ and SOL and showed that less than 10 minutes SOL correlated better with good SQ. Moreover, it was the most suitable sleep feature that could be predicted using early EEG, compared with the total sleep time, sleep efficiency, and actual sleep time. Our study showed the feasibility of estimating SOL distribution using deep learning with an early EEG and showed that SOL distribution within 10 minutes was associated with good SQ.

Energy intake, hydration status, and sleep of world-class male archers during competition.

BACKGROUND: Nutritional intake and sleep, play an important role for recovery and performance in elite sport but little work has been undertaken in archery. The present study aimed to assess energy intake (EI), hydration status, and sleep parameters in world-class male archers over the course of a four-day competition. METHODS: Results, Conclusions Six male, elite-standard archers participated in the study and measurements of hydration status, EI, competition load, and sleep were recorded throughout each day of competition. RESULTS: Daily energy, carbohydrate, and protein intake ranged between 2,563 and 3,986 kcal, 4 and 7.1 g/kg BM, 2.2 and 3.6 g/kg BM per day, respectively. Thus, archers practiced elements of periodized nutrition such that energy and carbohydrate intake was greater on the high-volume competition days (i.e. days 1 and 3; more numbers of arrows, longer duration, and walking distance) in comparison to low-volume days (days 2 and 4) over the tournament (all p > 0.01). Additionally, urine specific gravity was higher after waking, compared to pre- and post-competition, and before bed (all p < 0.05). This indicates that archers were euhydrated pre- and post-competition and before bedtime, while they were slightly hypohydrated after waking up. Sleep data show that disturbances were kept to a minimum. CONCLUSIONS: Collectively, archers appear capable of periodizing their nutritional intake according to daily physical loading during a tournament whilst, staying euhydrated and maintaining sleep quality. In part, such data can help to explain why these archers experience a sustained level of success.

Nocturnal exposure to a preferred ambient scent does not affect dream emotionality or post-sleep core affect valence in young adults.

Emotions experienced within sleep mentation (dreaming) affect mental functioning in waking life. There have been attempts at enhancing dream emotions using olfactory stimulation. Odors readily acquire affective value, but to profoundly influence emotional processing, they should bear personal significance for the perceiver rather than be generally pleasant. The main objective of the present sleep laboratory study was to examine whether prolonged nocturnal exposure to self-selected, preferred ambient room odor while asleep influences emotional aspects of sleep mentation and valence of post-sleep core affect. We asked twenty healthy participants (12 males, mean age 25 ± 4 years) to pick a commercially available scented room diffuser cartridge that most readily evoked positively valenced mental associations. In weekly intervals, the participants attended three sessions. After the adaptation visit, they were administered the odor exposure and odorless control condition in a balanced order. Participants were awakened five minutes into the first rapid eye movement (REM) stage that took place after 2:30 a.m. and, if they had been dreaming, they were asked to rate their mental sleep experience for pleasantness, emotional charge, and magnitude of positive and negative emotions and also to evaluate their post-sleep core affect valence. With rs < 0.20, no practically or statistically significant differences existed between exposure and control in any outcome measures. We conclude that in young, healthy participants, the practical value of olfactory stimulation with self-selected preferred scents for enhancement of dream emotions and post-sleep core affect valence is very limited.

Sleep duration, sleep efficiency, and amyloid ß among cognitively healthy later-life adults: a systematic review and meta-analysis.

BACKGROUND: Abnormal amyloid ß (Aß) deposits in the brain are a hallmark of Alzheimer's disease (AD). Insufficient sleep duration and poor sleep quality are risk factors for developing AD. Sleep may play a role in Aß regulation, but the magnitude of the relationship between sleep and Aß deposition remains unclear. This systematic review examines the relationship between sleep (i.e., duration and efficiency) with Aß deposition in later-life adults. METHODS: A search of PubMed, CINAHL, Embase, and PsycINFO generated 5,005 published articles. Fifteen studies met the inclusion criteria for qualitative syntheses; thirteen studies for quantitative syntheses related to sleep duration and Aß; and nine studies for quantitative syntheses related to sleep efficiency and Aß. RESULTS: Mean ages of the samples ranged from 63 to 76 years. Studies measured Aß using cerebrospinal fluid, serum, and positron emission tomography scans with two tracers: Carbone 11-labeled Pittsburgh compound B or fluorine 18-labeled. Sleep duration was measured subjectively using interviews or questionnaires, or objectively using polysomnography or actigraphy. Study analyses accounted for demographic and lifestyle factors. Based on 13 eligible articles, our synthesis demonstrated that the average association between sleep duration and Aß was not statistically significant (Fisher's Z = -0.055, 95% CI = -0.117 ~ 0.008). We found that longer self-report sleep duration is associated with lower Aß (Fisher's Z = -0.062, 95% CI = -0.119 ~ -0.005), whereas the objectively measured sleep duration was not associated with Aß (Fisher's Z = 0.002, 95% CI = -0.108 ~ 0.113). Based on 9 eligible articles for sleep efficiency, our synthesis also demonstrated that the average association between sleep efficiency and Aß was not statistically significant (Fisher's Z = 0.048, 95% CI = -0.066 ~ 0.161). CONCLUSION: The findings from this review suggest that shorter self-reported sleep duration is associated with higher Aß levels. Given the heterogeneous nature of the sleep measures and outcomes, it is still difficult to determine the exact relationship between sleep and Aß. Future studies with larger sample sizes should focus on comprehensive sleep characteristics and use longitudinal designs to better understand the relationship between sleep and AD.

Sleeping more than 8 h: a silent factor contributing to decreased muscle mass in Chinese community-dwelling older adults.

BACKGROUND: Muscle mass loss is an age-related process that can be exacerbated by lifestyle, environmental and other factors, but can be mitigated by good sleep. The objective of this study was to investigate the correlation between varying time lags of sleep duration and the decline in muscle mass among individuals aged 60 years or older by using real-world health monitoring data obtained from wearable devices and smart home health monitoring devices. METHODS: This study included 86,037 observations from 2,869 participants in the Mobile Support System database. Missing data were supplemented by multiple imputation. The investigation utilized generalized estimating equations and restricted cubic spline curve to examine the relationship between sleep duration and low muscle mass. Various lag structures, including 0, 1, 2, 0-1, 0-2, and 1-2 months, were fitted, and the interaction effect of observation time with sleep duration was estimated for each lag structure. Additionally, subgroup analyses were conducted. The models were adjusted for various covariates, including gender, age, body mass index, footsteps, smoking status, drinking status, marital status, number of chronic diseases, number of medications, diabetes mellitus, hyperlipidemia, coronary artery disease, respiratory disease, and musculoskeletal disease and an interaction term between time and sleep duration. RESULTS: The results of the generalized estimating equation showed a significant correlation (p < 0.001) between sleep duration of 8 h or more and low muscle mass in older adults, using 6-7 h of sleep as a reference. This effect was seen over time and prolonged sleep accumulated over multiple months had a greater effect on muscle mass loss than a single month. The effect of long sleep duration on muscle mass loss was significantly greater in females than in males and greater in the over-75 than in the under-75 age group. Restricted cubic spline plots showed a non-linear relationship between sleep duration and low muscle mass (p < 0.001). CONCLUSIONS: This study found an association between sustained nighttime sleep of more than eight hours and decreased muscle mass in older adults, especially older women.

Bidirectional Associations Between Loneliness, Emotional Support, and Sleep in Daily Life.

OBJECTIVE: Evidence suggests a link between positive social relationship perceptions and improved sleep (e.g., quality, efficiency) across the life span. Less work has probed the directionality of these relationships. Here, we report findings from the first study to examine bidirectional between- and within-person associations between loneliness and emotional support with daily life measures of sleep. METHODS: Participants were 389 healthy adults aged 40 to 64 years (61% female) who completed hourly surveys assessing loneliness and perceptions of emotional support over the course of 4 days. Measures of actigraphy-assessed sleep and nightly sleep quality were also assessed for 7 to 10 days. RESULTS: Individuals with lower average daily loneliness showed higher sleep quality and efficiency than individuals with higher loneliness (r = -0.19, p < .001; r = -0.14, p = .008, respectively), and greater average emotional support was likewise linked with better sleep quality (r = 0.18, p < .001). Controlling for neuroticism attenuated the effects of average loneliness on sleep. Within-person analyses showed unexpected bidirectional effects. Specifically, days in which people felt relatively lonelier were followed by nights with greater sleep efficiency (γ = 1.08, p = .015), and nights when people reported relatively poorer sleep quality were followed by days with greater emotional support (γ = -0.04, p = .013). These unexpected findings are probed in exploratory analyses. CONCLUSIONS: Individuals with higher loneliness and lower emotional support report poorer sleep quality and efficiency, on average. Day-to-day fluctuations in perceptions of social relationships may affect the following night's sleep, and vice versa.

Prospective Bidirectional Relationship Between Sleep Duration and Posttraumatic Stress Disorder Symptoms After Suspected Acute Coronary Syndrome.

OBJECTIVE: Sleep disturbance is a "hallmark" symptom of posttraumatic stress disorder (PTSD). Poor sleep (including short sleep) after combat-related trauma can also predict subsequent PTSD. Less is known about the association between sleep duration and PTSD symptoms when PTSD is induced by acute coronary syndrome (ACS). We examined the bidirectional relationship between sleep duration and PTSD symptoms over the year after hospital evaluation for ACS. METHODS: Participants were enrolled in this observational study after emergency department evaluation for ACS. Sleep duration ("During the past month, how many hours of actual sleep did you get at night?") and cardiac event or hospitalization-induced PTSD symptoms (PTSD Checklist) were assessed at 1, 6, and 12 months after hospital discharge. Cross-lagged path analysis was used to model the effects of sleep duration and PTSD symptoms on each other. Covariates included age, sex, race/ethnicity, cardiac severity, baseline depression symptoms, and early acute stress disorder symptoms. RESULTS: The sample included 1145 participants; 16% screened positive for probable PTSD (PTSD Checklist score ≥33). Mean sleep duration across time points was 6.1 hours. Higher PTSD symptoms predicted shorter sleep duration at the next time point (i.e., 1-6 and 6-12 months; B = -0.14 hours/10-point difference, SE = 0.03, p < .001). Shorter sleep duration was associated with higher PTSD symptoms at the next time point (B = -0.25 points/hour, SE = 0.12, p = .04). CONCLUSIONS: Short sleep duration and PTSD symptoms are mutually reinforcing across the first year after ACS evaluation. Findings suggest that sleep, PTSD symptoms, and their relationship should be considered in the post-ACS period.

The Association of Multidimensional Sleep Health With HbA1c and Depressive Symptoms in African American Adults With Type 2 Diabetes.

OBJECTIVE: Sleep is important for diabetes-related health outcomes. Using a multidimensional sleep health framework, we examined the association of individual sleep health dimensions and a composite sleep health score with hemoglobin A1c (HbA1c) and depressive symptoms among African American adults with type 2 diabetes. METHODS: Participants (N = 257; mean age = 62.5 years) were recruited through local churches. Wrist-worn actigraphy and sleep questionnaire data assessed multidimensional sleep health using the RuSATED framework (regularity, satisfaction, alertness, timing, efficiency, duration). Individual sleep dimensions were dichotomized into poor or good sleep health and summed into a composite score. HbA1c was assessed using the DCA Vantage™ Analyzer or A1CNow® Self Check. Depressive symptoms were assessed using the Patient Health Questionnaire (PHQ-9). Regression models examined the association of individual sleep dimensions and composite sleep health with HbA1c and depressive symptoms. RESULTS: Higher composite sleep health scores were associated with a lower likelihood of having greater than minimal depressive symptoms (PHQ-9 ≥ 5) (odds ratio [OR] = 0.578, 95% confidence interval [CI] = 0.461-0.725). Several individual sleep dimensions, including irregularity (OR = 1.013, CI = 1.005-1.021), poor satisfaction (OR = 3.130, CI = 2.095-4.678), and lower alertness (OR = 1.866, CI = 1.230-2.833) were associated with a greater likelihood of having depressive symptoms. Neither composite sleep health scores nor individual sleep dimensions were associated with HbA1c. CONCLUSIONS: Better multidimensional sleep health is associated with lower depressive symptoms among African American adults with type 2 diabetes. Longitudinal research is needed to determine the causal association between multidimensional sleep health and depressive symptoms in this population. TRIAL REGISTRY: ClinicalTrials.gov identifier NCT04282395.

Shared EEG correlates between non-REM parasomnia experiences and dreams.

Sleepwalking and related parasomnias result from incomplete awakenings out of non-rapid eye movement sleep. Behavioral episodes can occur without consciousness or recollection, or in relation to dream-like experiences. To understand what accounts for these differences in consciousness and recall, here we recorded parasomnia episodes with high-density electroencephalography (EEG) and interviewed participants immediately afterward about their experiences. Compared to reports of no experience (19%), reports of conscious experience (56%) were preceded by high-amplitude EEG slow waves in anterior cortical regions and activation of posterior cortical regions, similar to previously described EEG correlates of dreaming. Recall of the content of the experience (56%), compared to no recall (25%), was associated with higher EEG activation in the right medial temporal region before movement onset. Our work suggests that the EEG correlates of parasomnia experiences are similar to those reported for dreams and may thus reflect core physiological processes involved in sleep consciousness.