Adaptation effects to sleep studies in participants with and without chronic posttraumatic stress disorder

InsightSleepNet: the interpretable and uncertainty-aware deep learning network for sleep staging using continuous Photoplethysmography

BACKGROUND

This study was conducted to address the existing drawbacks of inconvenience and high costs associated with sleep monitoring. In this research, we performed sleep staging using continuous photoplethysmography (PPG) signals for sleep monitoring with wearable devices. Furthermore, our aim was to develop a more efficient sleep monitoring method by considering both the interpretability and uncertainty of the model's prediction results, with the goal of providing support to medical professionals in their decision-making process.

METHOD

The developed 4-class sleep staging model based on continuous PPG data incorporates several key components: a local attention module, an InceptionTime module, a time-distributed dense layer, a temporal convolutional network (TCN), and a 1D convolutional network (CNN). This model prioritizes both interpretability and uncertainty estimation in its prediction results. The local attention module is introduced to provide insights into the impact of each epoch within the continuous PPG data. It achieves this by leveraging the TCN structure. To quantify the uncertainty of prediction results and facilitate selective predictions, an energy score estimation is employed. By enhancing both the performance and interpretability of the model and taking into consideration the reliability of its predictions, we developed the InsightSleepNet for accurate sleep staging.

RESULT

InsightSleepNet was evaluated using three distinct datasets: MESA, CFS, and CAP. Initially, we assessed the model's classification performance both before and after applying an energy score threshold. We observed a significant improvement in the model's performance with the implementation of the energy score threshold. On the MESA dataset, prior to applying the energy score threshold, the accuracy was 84.2% with a Cohen's kappa of 0.742 and weighted F1 score of 0.842. After implementing the energy score threshold, the accuracy increased to a range of 84.8-86.1%, Cohen's kappa values ranged from 0.75 to 0.78 and weighted F1 scores ranged from 0.848 to 0.861. In the case of the CFS dataset, we also noted enhanced performance. Before the application of the energy score threshold, the accuracy stood at 80.6% with a Cohen's kappa of 0.72 and weighted F1 score of 0.808. After thresholding, the accuracy improved to a range of 81.9-85.6%, Cohen's kappa values ranged from 0.74 to 0.79 and weighted F1 scores ranged from 0.821 to 0.857. Similarly, on the CAP dataset, the initial accuracy was 80.6%, accompanied by a Cohen's kappa of 0.73 and weighted F1 score was 0.805. Following the application of the threshold, the accuracy increased to a range of 81.4-84.3%, Cohen's kappa values ranged from 0.74 to 0.79 and weighted F1 scores ranged from 0.813 to 0.842. Additionally, by interpreting the model's predictions, we obtained results indicating a correlation between the peak of the PPG signal and sleep stage classification.

CONCLUSION

InsightSleepNet is a 4-class sleep staging model that utilizes continuous PPG data, serves the purpose of continuous sleep monitoring with wearable devices. Beyond its primary function, it might facilitate in-depth sleep analysis by medical professionals and empower them with interpretability for intervention-based predictions. This capability can also support well-informed clinical decision-making, providing valuable insights and serving as a reliable second opinion in medical settings.

First-night effect in insomnia disorder: a systematic review and meta-analysis of polysomnographic findings

Polysomnographic studies have been performed to investigate the first-night effect in insomnia disorder. However, these studies have revealed discrepant findings. This meta-analysis aimed to summarise and quantify the characteristics of the first-night effect in insomnia disorder. We performed a systematic search of the PubMed, Medline, EMBASE, Web of Science and PsycINFO databases to identify studies published through October 2019. A total of 11,862 articles were identified, and seven studies with eight independent populations were included in the meta-analysis. A total of 639 patients with insomnia disorder and 171 healthy controls underwent more than 2 consecutive nights of in-laboratory polysomnography. Pooled results demonstrated that both variables of sleep continuity and sleep architecture, other than slow-wave sleep were significantly altered in the first-night effect in insomnia disorder. Furthermore, the results indicated that patients with insomnia disorder had a disruption of sleep continuity in the first-night effect, including increased sleep onset latency and reduced total sleep time, compared to healthy controls. Overall, the findings show that patients with insomnia disorder experience the first-night effect, rather than reverse first-night effect, and the profiles of the first-night effect in patients with insomnia are different from healthy controls. These indicate that an adaptation night is necessary when sleep continuity and sleep architecture is to be studied in patients with insomnia disorder. More well-designed studies with large samples are needed to confirm the results.

Polysomnographic characteristics of sleep in adults with and without physician-diagnosed atopic dermatitis: results from the Study of Health in Pomerania

PURPOSE

To analyze sleep characteristics as measured with polysomnography (PSG) in adults from the general population with and without physician-diagnosed atopic dermatitis (AD).

METHODS

We analyzed data from participants from the German population-based Study of Health in Pomerania (SHIP) TREND-0. AD was diagnosed in a standardized skin examination. The following polysomnographic parameters were measured: total sleep duration (min), sleep latency (min), wake after sleep onset (WASO; min), rapid eye movement (REM) latency (min), sleep efficiency (%), total number of wakefulness and movement episodes, stages of sleep (%), and apnea-hypopnea index (AHI). Additionally, the subjective sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). We compared sleep characteristics of participants with and without AD.

RESULTS

Among 1187 participants, 47 (4.0%) had AD. We found no differences between participants with and without AD in any of the analyzed PSG parameters except for the total number of wakefulness and movement episodes and the percentage of REM sleep. Participants with AD had a higher number of wakefulness and movement episodes, and a lower proportion of REM sleep compared to those without AD. Regarding subjective sleep parameters, no significant differences were found between participants with and without AD.

CONCLUSION

Our data do not provide evidence for poor sleep quality in individuals with AD. Major limitations of the study include the unavailability of data on AD severity and the small number of participants with AD. Larger-scaled longitudinal studies considering disease severity and specific AD symptoms with an effect on sleep are required.

Effects of sleep fragmentation and partial sleep restriction on heart rate variability during night

We developed a cross-over study design with two interventions in randomized order to compare the effects of sleep fragmentation and partial sleep restriction on cardiac autonomic tone. Twenty male subjects (40.6 ± 7.5 years old) underwent overnight polysomnography during 2 weeks, each week containing one undisturbed baseline night, one intervention night (either sleep restriction with 5 h of sleep or sleep fragmentation with awakening every hour) and two undisturbed recovery nights. Parameters of heart rate variability (HRV) were used to assess cardiac autonomic modulation during the nights. Sleep restriction showed significant higher heart rate (p = 0.018) and lower HRV-pNN50 (p = 0.012) during sleep stage N1 and lower HRV-SDNN (p = 0.009) during wakefulness compared to the respective baseline. For HR and SDNN there were recovery effects. There was no significant difference comparing fragmentation night and its baseline. Comparing both intervention nights, sleep restriction had lower HRV high frequency (HF) components in stage N1 (p = 0.018) and stage N2 (p = 0.012), lower HRV low frequency (LF) (p = 0.007) regarding the entire night and lower SDNN (p = 0.033) during WASO during sleep. Sleep restriction increases sympathetic tone and decreases vagal tone during night causing increased autonomic stress, while fragmented sleep does not affect cardiac autonomic parameters in our sample.

Sleep spindles in people with schizophrenia, schizoaffective disorders or bipolar disorders: a pilot study in a general population-based cohort

BACKGROUND

Sleep spindles have been involved in sleep stabilization and sleep-related memory mechanisms and their deficit emerged as possible biomarker in schizophrenia. However, whether this sleep phenotype is also present in other disorders that share psychotic symptoms remains unclear. To address this gap, we assessed sleep spindles in participants of a prospective population-based cohort who underwent psychiatric assessment (CoLaus|PsyCoLaus) and polysomnographic recording (HypnoLaus).

METHODS

Sleep was recorded using ambulatory polysomnography in participants (N = 1037) to the PsyCoLaus study. Sleep spindle parameters were measured in people with a lifelong diagnosis of schizophrenia (SZ), schizoaffective depressive (SAD), schizoaffective manic (SAM), bipolar disorder type I (BP-I) and type II (BP-II). The associations between lifetime diagnostic status (independent variables, SZ, SAD, SAM, BPD-I, BPD-II, controls) and spindle parameters (dependent variables) including density, duration, frequency and maximum amplitude, for all (slow and fast), slow- and fast-spindle were assessed using linear mixed models. Pairwise comparisons of the different spindle parameters between the SZ group and each of the other psychiatric groups was performed using a contrast testing framework from our multiple linear mixed models.

RESULTS

Our results showed a deficit in the density and duration of sleep spindles in people with SZ. They also indicated that participants with a diagnosis of SAD, SAM, BP-I and BP-II exhibited different sleep spindle phenotypes. Interestingly, spindle densities and frequencies were different in people with a history of manic symptoms (SAM, BP-I, and BP-II) from those without (SZ, SAD).

CONCLUSIONS

Although carried out on a very small number of participants due to the low prevalence of these disorders in general population, this pilot study brought new elements that argued in favor of a deficit of sleep spindles density and duration in people with schizophrenia. In addition, while we could expect a gradual change in intensity of the same sleep spindle parameters through psychotic diagnoses, our results seem to indicate a more complex situation in which the frequency of sleep spindles might be more impacted by diagnoses including a history of mania or hypomania. Further studies with a larger number of participants are required to confirm these effects.

Subjective and objective sleep quality in young women with posttraumatic stress disorder following sexual assault: a prospective study

Background: Most posttraumatic stress disorder (PTSD) sleep disturbances reports have been conducted in male combat veteran populations, usually decades after the disorder's onset. Given the increase in the prevalence of violence against women and the fact that women are at greater risk for developing PTSD, it is critical to examine sleep abnormalities in this population. Objectives: To examine subjective and objective sleep quality in young women with PTSD following sexual assault compared with a control group at baseline and after one year of treatment. Methods: Seventy-four women with PTSD following sexual assault and 64 healthy controls with no history of sexual assault were assessed using the Clinician-Administered PTSD Scale (CAPS-5), the Beck Depression Inventory, the Beck Anxiety Inventory, the Pittsburgh Sleep Quality Index (PSQI), the Modified Fatigue Impact Scale, and the Insomnia Severity Index. Subjects also underwent full in-lab polysomnography. PTSD participants received pharmacological and/or psychological therapy between baseline and one-year follow-up. Results: The PTSD group had significantly higher scores in the clinical and sleep measurements than the control group. Although the PTSD group reported poorer subjective sleep quality than healthy controls, there were few between-group differences in objective sleep. Analysis of the PTSD group at baseline and one-year follow-up showed that the PSQI global score was a significant predictor of PTSD improvement. Conclusions: Sleep quality is impaired in young women with PTSD and may impact long-term treatment responses. Better sleep quality is significantly associated with PTSD improvement, independent of depression and anxiety.

Subjective cognitive impairment in patients with transformed migraine and the associated psychological and sleep disturbances

PURPOSE

Migraines are associated with multiple comorbidities like depression, anxiety, poor sleep quality, and subjective cognitive impairment (SCI). This study aimed to evaluate the association of SCI with depression, anxiety, and modalities of sleep in those who have transformed migraines (TM).

SUBJECTS AND METHODS

The study was conducted on 120 participants with TM and 41 control group participants. The subjective cognitive decline questionnaire classified the participants as SCI and non-SCI. The Headache Impact Test-6, Migraine Disability Assessment, Montreal Cognitive Assessment, Mini-Mental State Examination, Patient Health Questionnaire-9, Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale, Full Polysomnography, and Beck's Anxiety and the Depression Inventories were used and analyzed between patients with SCI and non-SCI.

RESULTS

Patients with TM who had SCI represented 34% with severe headache effects, disability, pain severity, increased depression, and increased anxiety. They showed shorter sleep duration during weekdays, lower sleep quality, less sleep time, lower efficiency, and less REM sleep along with greater sleep latency, periodic limb movements, a higher arousal index, snore index, and percent of NREM3. There was a positive correlation between certain polysomnography parameters like percent NREM3, sleep period, sleep index, sleep latency, sleep arousal index, and periodic limb movements, and an inverse correlation with the percent of REM sleep, total sleep time, and sleep efficiency.

CONCLUSION

Subjective cognitive complaints are common in patients with transformed migraine affecting about 34% of cases. TM patients with SCI had more sleep and psychological disturbances.

TRIAL REGISTRATION

Clinicaltrials.gov is NCT04413110.

Effect of an Inflatable Air Mattress with Variable Rigidity on Sleep Quality

Several studies, wherein the structure or rigidity of a mattress was varied, have been conducted to improve sleep quality. These studies investigated the effect of variation in the surface characteristics of mattresses on sleep quality. The present study developed a mattress whose rigidity can be varied by controlling the amount of air in its air cells. To investigate the effect of the variable rigidity of the air mattress on sleep quality, participants (Male, Age: 23.9 ± 2.74, BMI: 23.3 ± 1.60) were instructed to sleep on the air mattress under different conditions, and their sleep quality was subjectively and objectively investigated. Subjectively, sleep quality is assessed based on the participants’ evaluations of the depth and length of their sleep. Objectively, sleep is estimated using the sleep stage information obtained by analysing the movements and brain waves of the participants during their sleep. A subjective assessment of the sleep quality demonstrates that the participants’ sleep was worse with the adjustment of the air mattress than that without; however, the objective sleep quality results demonstrates an improvement in the sleep quality when the rigidity of the air mattress is varied based on the participant’s preference. This paper proposes a design for mattresses that can result in more efficient sleep than that provided by traditional mattresses.

Objective Characterization of Activity, Sleep, and Circadian Rhythm Patterns Using a Wrist-Worn Actigraphy Sensor: Insights Into Posttraumatic Stress Disorder

BACKGROUND

Wearables have been gaining increasing momentum and have enormous potential to provide insights into daily life behaviors and longitudinal health monitoring. However, to date, there is still a lack of principled algorithmic framework to facilitate the analysis of actigraphy and objectively characterize day-by-day data patterns, particularly in cohorts with sleep problems.

OBJECTIVE

This study aimed to propose a principled algorithmic framework for the assessment of activity, sleep, and circadian rhythm patterns in people with posttraumatic stress disorder (PTSD), a mental disorder with long-lasting distressing symptoms such as intrusive memories, avoidance behaviors, and sleep disturbance. In clinical practice, these symptoms are typically assessed using retrospective self-reports that are prone to recall bias. The aim of this study was to develop objective measures from patients' everyday lives, which could potentially considerably enhance the understanding of symptoms, behaviors, and treatment effects.

METHODS

Using a wrist-worn sensor, we recorded actigraphy, light, and temperature data over 7 consecutive days from three groups: 42 people diagnosed with PTSD, 43 traumatized controls, and 30 nontraumatized controls. The participants also completed a daily sleep diary over 7 days and the standardized Pittsburgh Sleep Quality Index questionnaire. We developed a novel approach to automatically determine sleep onset and offset, which can also capture awakenings that are crucial for assessing sleep quality. Moreover, we introduced a new intuitive methodology facilitating actigraphy exploration and characterize day-by-day data across 49 activity, sleep, and circadian rhythm patterns.

RESULTS

We demonstrate that the new sleep detection algorithm closely matches the sleep onset and offset against the participants' sleep diaries consistently outperforming an existing open-access widely used approach. Participants with PTSD exhibited considerably more fragmented sleep patterns (as indicated by greater nocturnal activity, including awakenings) and greater intraday variability compared with traumatized and nontraumatized control groups, showing statistically significant (P<.05) and strong associations (|R|>0.3).

CONCLUSIONS

This study lays the foundation for objective assessment of activity, sleep, and circadian rhythm patterns using passively collected data from a wrist-worn sensor, facilitating large community studies to monitor longitudinally healthy and pathological cohorts under free-living conditions. These findings may be useful in clinical PTSD assessment and could inform therapy and monitoring of treatment effects.

Deep learning in the cross-time frequency domain for sleep staging from a single-lead electrocardiogram

OBJECTIVE

This study classifies sleep stages from a single lead electrocardiogram (ECG) using beat detection, cardiorespiratory coupling in the time-frequency domain and a deep convolutional neural network (CNN).

APPROACH

An ECG-derived respiration (EDR) signal and synchronous beat-to-beat heart rate variability (HRV) time series were derived from the ECG using previously described robust algorithms. A measure of cardiorespiratory coupling (CRC) was extracted by calculating the coherence and cross-spectrogram of the EDR and HRV signal in 5 min windows. A CNN was then trained to classify the sleep stages (wake, rapid-eye-movement (REM) sleep, non-REM (NREM) light sleep and NREM deep sleep) from the corresponding CRC spectrograms. A support vector machine was then used to combine the output of CNN with the other features derived from the ECG, including phase-rectified signal averaging (PRSA), sample entropy, as well as standard spectral and temporal HRV measures. The MIT-BIH Polysomnographic Database (SLPDB), the PhysioNet/Computing in Cardiology Challenge 2018 database (CinC2018) and the Sleep Heart Health Study (SHHS) database, all expert-annotated for sleep stages, were used to train and validate the algorithm.

MAIN RESULTS

Ten-fold cross validation results showed that the proposed algorithm achieved an accuracy (Acc) of 75.4% and a Cohen's kappa coefficient of [Formula: see text]  =  0.54 on the out of sample validation data in the classification of Wake, REM, NREM light and deep sleep in SLPDB. This rose to Acc  =  81.6% and [Formula: see text]  =  0.63 for the classification of Wake, REM sleep and NREM sleep and Acc  =  85.1% and [Formula: see text]  =  0.68 for the classification of NREM sleep versus REM/wakefulness in SLPDB.

SIGNIFICANCE

The proposed ECG-based sleep stage classification approach that represents the highest reported results on non-electroencephalographic data and uses datasets over ten times larger than those in previous studies. By using a state-of-the-art QRS detector and deep learning model, the system does not require human annotation and can therefore be scaled for mass analysis.

Home Polysomnography Reveals a First-Night Effect in Patients With Low Sleep Bruxism Activity

STUDY OBJECTIVES

To examine the presence of a first-night effect (FNE) and the level of internight variability in sleep bruxism (SB) activity when a self-applicable electrode set is used in home polysomnography (PSG) in a sample of subjects with possible SB.

METHODS

Fourteen females and two males aged 38.3 ± 9.1 years (mean ± standard deviation) with self-reported SB underwent home-PSG on three consecutive nights. The subjects applied PSG sensors themselves, including self-applicable electrode sets used to record sleep and masseter muscle activity. Repeated-measures analysis of variance was used to compare SB and sleep variables between the nights.

RESULTS

Surprisingly, there were statistically significant elevations in the rhythmic masticatory muscle activity (RMMA) episode index (P = .009), burst index (P = .016), and bruxism time index (P = .049) throughout the course of 3 nights. More bruxers were diagnosed on the second (6 bruxers, ≥ 2 episodes/h) and third night (7 bruxers) compared to the first night (2 bruxers). Most subjects (14/16) had their highest RMMA index on the second or third night. The mean coefficient of variation for RMMA episode index was 50.7%. No statistically significant differences were detected in other sleep variables.

CONCLUSIONS

The results indicate that a FNE may be present in SB activity, possibly lasting several nights in some subjects. Furthermore, FNE appears to be combined with high internight variability of SB activity without indications of internight changes in sleep macrostructure. To confirm the level of ongoing SB activity, several nights of PSG may be required, especially in subjects with low first-night SB activity.

COMMENTARY

A commentary on this article appears in this issue on page 1281.

Better Sleep in a Strange Bed? Sleep Quality in South African Women with Posttraumatic Stress Disorder

Although individuals diagnosed with posttraumatic stress disorder (PTSD) regularly report subjective sleep disruption, many studies using objective measures (e.g., polysomnography) report no PTSD-related sleep disruption. To account for these inconsistencies, some authors hypothesize that PTSD-diagnosed individuals have sleep-state misperception; that is, they self-report experiencing poor sleep quality, but objectively sleep relatively normally. We tested this sleep-state misperception hypothesis, collecting data on subjectively-reported sleep quality (in the home, and in the laboratory) and on objectively-measured, laboratory-based, sleep quality in PTSD-diagnosed participants from low socioeconomic status South African communities. Women with PTSD (n = 21), with trauma exposure but no PTSD (TE; n = 19), and healthy controls (HC; n = 20) completed questionnaires on their average sleep quality in the past 30 days, and on their sleep quality after a night (8 h) of polysomnographic-monitored sleep in the laboratory. PTSD-diagnosed individuals reported poorer everyday subjective sleep quality than TE and HC individuals. In the laboratory, however, there were no between-group differences in subjective sleep quality, and few between-group differences in objective sleep quality (PTSD-diagnosed individuals only had decreased sleep depth). Furthermore, whereas measures of laboratory-based objective and subjective sleep quality correlated significantly, especially in PTSD-diagnosed individuals, there were few significant associations between objective sleep measures and everyday subjective sleep quality. Taken together, these findings suggest that PTSD-diagnosed individuals likely experienced better sleep quality in the laboratory than at home. Descriptive observations corroborated this interpretation, with almost half the sample rating their laboratory sleep (which they described as “safe” and “quiet”) as better than their home sleep (which was experienced in an atmosphere marked by high levels of violence and nighttime noise). These findings disconfirm the sleep-state misperception hypothesis as related to PTSD, and suggest that the laboratory environment may influence sleep quality positively in these individuals. Many investigations of sleep in PTSD do not consider the influence of the laboratory environment. Our findings suggest that future studies in this field should consider that sleep-state misperception may be an artifact of the laboratory setting, especially when samples are drawn from communities where violence and crime are an everyday reality.

Sleep and mental disorders: A meta-analysis of polysomnographic research

Investigating sleep in mental disorders has the potential to reveal both disorder-specific and transdiagnostic psychophysiological mechanisms. This meta-analysis aimed at determining the polysomnographic (PSG) characteristics of several mental disorders. Relevant studies were searched through standard strategies. Controlled PSG studies evaluating sleep in affective, anxiety, eating, pervasive developmental, borderline and antisocial personality disorders, attention-deficit-hyperactivity disorder (ADHD), and schizophrenia were included. PSG variables of sleep continuity, depth, and architecture, as well as rapid-eye movement (REM) sleep were considered. Calculations were performed with the "Comprehensive Meta-Analysis" and "R" software. Using random effects modeling, for each disorder and each variable, a separate meta-analysis was conducted if at least 3 studies were available for calculation of effect sizes as standardized means (Hedges' g). Sources of variability, that is, sex, age, and mental disorders comorbidity, were evaluated in subgroup analyses. Sleep alterations were evidenced in all disorders, with the exception of ADHD and seasonal affective disorders. Sleep continuity problems were observed in most mental disorders. Sleep depth and REM pressure alterations were associated with affective, anxiety, autism and schizophrenia disorders. Comorbidity was associated with enhanced REM sleep pressure and more inhibition of sleep depth. No sleep parameter was exclusively altered in 1 condition; however, no 2 conditions shared the same PSG profile. Sleep continuity disturbances imply a transdiagnostic imbalance in the arousal system likely representing a basic dimension of mental health. Sleep depth and REM variables might play a key role in psychiatric comorbidity processes. Constellations of sleep alterations may define distinct disorders better than alterations in 1 single variable. (PsycINFO Database Record

The impact of posttraumatic stress disorder versus resilience on nocturnal autonomic nervous system activity as functions of sleep stage and time of sleep

Posttraumatic stress disorder (PTSD) has been associated with sleep disturbances including alterations in sleep stages and recently, elevated nocturnal autonomic nervous system (ANS) arousal (i.e., dominance of the sympathetic nervous system over the parasympathetic nervous system). Data suggest that sleep contributes to the regulation of ANS activity. In our previous ambulatory heart rate variability (HRV) monitoring study, strong relationships between sleep and nocturnal ANS activity in resilient participants (i.e., individuals who had never had PTSD despite exposure to high-impact trauma) were not seen with PTSD. In this study, we examined the impact of PTSD vs. resilience on ANS activity as a function of sleep stage and time of sleep. Participants (age 18-35) with current PTSD (n=38) and resilience (n=33) completed two overnight polysomnography recordings in a lab setting. The second night electrocardiogram was analyzed for frequency domain HRV parameters and heart rate within rapid-eye-movement (REM) and non-REM (NREM) sleep periods. Results indicated that ANS arousal indexed by HRV was greater during REM compared with NREM sleep and that the REM-NREM difference was greater in the PTSD than in the resilient participants. This effect of PTSD was reduced to non-significance when analyses controlled for REM sleep percentage, which was lower with PTSD. Exploratory analyses revealed that the REM-NREM difference in HRV was correlated with REM sleep percentage in resilient participants, but not with PTSD. In contrast with our data from home settings, the present study did not find increased overall nocturnal ANS arousal with PTSD. Analyses did reveal higher heart rate during initial NREM sleep with more rapid decline over the course of NREM sleep with PTSD compared with resilience. Findings suggest that elevated ANS arousal indexed by heart rate with PTSD is specific to the early part of sleep and possible impairment in regulating ANS activity with PTSD related to REM sleep.

Has adult sleep duration declined over the last 50+ years?

The common assumption that population sleep duration has declined in the past few decades has not been supported by recent reviews, which have been limited to self-reported data. The aim of this review was to assess whether there has been a reduction in objectively recorded sleep duration over the last 50+ years. The literature was searched for studies published from 1960 to 2013, which assessed objective sleep duration (total sleep time (TST)) in healthy normal-sleeping adults. The search found 168 studies that met inclusion criteria, with 257 data points representing 6052 individuals ages 18-88 y. Data were assessed by comparing the regression lines of age vs. TST in studies conducted between 1960 and 1989 vs. 1990-2013. Weighted regression analyses assessed the association of year of study with age-adjusted TST across all data points. Regression analyses also assessed the association of year of study with TST separately for 10-y age categories (e.g., ages 18-27 y), and separately for polysomnographic and actigraphic data, and for studies involving a fixed sleep schedule and participants' customary sleep schedules. Analyses revealed no significant association of sleep duration with study year. The results are consistent with recent reviews of subjective data, which have challenged the notion of a modern epidemic of insufficient sleep.

Sleep pattern in Charcot-Marie-Tooth disease type 2: report of family case series

OBJECTIVES

Charcot-Marie-Tooth (CMT) disease is the most prevalent hereditary motor and sensory polyneuropathy, and a condition in which sleep has rarely been studied, particularly in relation to the type 2 (CMT2). Thus, we aimed to characterize the sleep patterns of a family affected by CMT2 disease.

METHODS

Sixteen volunteers with CMT2 from the same multigenerational family agreed to participate in the study (refusal rate = 31%). All participants answered sleep questionnaires and came to the sleep laboratory to perform a diagnostic polysomnography (PSG). Clinical manifestation and severity of the disease were also evaluated.

RESULTS

56% of the sample were male and 44% female, with a mean age of 32 ± 17 years, of normal weight (body mass index 21 ± 3 kg/m(2)); 64% presented moderate to severe CMT2. Regarding subjective sleep, 31% had excessive daytime sleepiness and 75% reported poor sleep quality. The PSG results revealed that CMT2 patients had an increase in stage N3 and a reduction in REM sleep, in addition to a high arousal index. Although 81% of the sample were snorers, only 13% had an apnea-hypopnea index (AHI) > 5. However, a positive correlation was found between the severity of disease and the AHI.

CONCLUSIONS

Taken together, these data show that CMT2 disease is characterized by important changes in sleep architecture, probably due to sleep fragmentation. Although these alterations may worsen with disease severity, it seems that they are not related to sleep breathing or movement disorders.

The first-night effect suppresses the strength of slow-wave activity originating in the visual areas during sleep

Our visual system is plastic and adaptive in response to the stimuli and environments we experience. Although visual adaptation and plasticity have been extensively studied while participants are awake, little is known about what happens while they are asleep. It has been documented that sleep structure as measured by sleep stages using polysomnography is altered specifically in the first sleep session due to exposure to a new sleep environment, known as the first-night effect (FNE). However, the impact of the FNE on spontaneous oscillations in the visual system is poorly understood. How does the FNE affect the visual system during sleep? To address this question, the present study examined whether the FNE modifies the strength of slow-wave activity (SWA, 1-4Hz)-the dominant spontaneous brain oscillation in slow-wave sleep-in the visual areas. We measured the strength of SWA originating in the visual areas during the first and the second sleep sessions. Magnetoencephalography, polysomnography, and magnetic resonance imaging were used to localize the source of SWA to the visual areas. The visual areas were objectively defined using retinotopic mapping and an automated anatomical parcellation technique. The results showed that the strength of SWA was reduced in the first sleep session in comparison to the second sleep session, especially during slow-wave sleep, in the ventral part of the visual areas. These results suggest that environmental novelty may affect the visual system through suppression of SWA. The impact of the FNE may not be negligible in vision research.