In-Home Sleep Recordings in Military Veterans With Posttraumatic Stress Disorder Reveal Less REM and Deep Sleep <1 Hz

Vivid dreams are associated with a high percentage of REM sleep: a prospective study in veterans

STUDY OBJECTIVES

Vivid dreams are dreams that feel real or are associated with dream enactment behavior. They are prevalent in veterans, especially in those with psychiatric disorders such as post-traumatic stress disorders. Such psychiatric disorders have known association with abnormalities in rapid eye movement (REM) sleep. Vivid dreams are also described in neurological conditions, such Lewy body dementias, which are also associated with REM sleep abnormality. Although vivid dreams occur in neuropsychiatric disorders that have REM sleep abnormalities, there are no studies that have directly investigated an association between vivid dreams and REM sleep. We sought to study vivid dreams and REM sleep in veterans.

METHODS

Veterans undergoing polysomnography at our hospital were invited to enroll. Participants completed a dream-related questionnaire the morning after their polysomnography.

RESULTS

We prospectively enrolled 505 veterans. After a night in the sleep laboratory, 196 of 504 (39%) reported experiencing a dream, and, of those, 117 of 190 (62%) described their dream as vivid. Discrepancies in patient totals are secondary to missing questionnaire data. Our novel finding is that participants with a high percentage of REM sleep (above 25%) were more than twice likely to report a vivid dream than participants with a lower percentage of REM sleep (P < .0001). Nonvivid dreams were not associated with a high percentage of REM sleep.

CONCLUSIONS

Vivid dreams are associated with a high percentage of REM sleep. Further research into the role of REM sleep abnormalities in vivid dreams may help to advance understanding of neuropsychiatric disorders.

CITATION

Fattal D, Platti N, Hester S, Wendt L. Vivid dreams are associated with a high percentage of REM sleep: a prospective study in veterans. J Clin Sleep Med. 2023;19(9):1661-1668.

An ecological approach to clinically assess nightmares in military service members with severe PTSD

BACKGROUND

Trauma-related nightmares (TRNs) are distressing events which contribute to insomnia severity, chronicity and treatment resistance of PTSD. Therefore, recording TRNs is a crucial technical challenge in order to understand their physiopathological patterns and their impact on sleep. However, TRNs are difficult to record during a single night in a sleep laboratory, which, moreover, is likely to be considered by patients as a protective sleep environment that is therefore not representative of home sleep conditions.

METHOD

In the present study, we investigate if objective sleep measures acquired at-home using two ambulatory devices is of clinical value by correlating with PTSD patients' complaints about sleep and nightmares. A secondary objective is to relate awakenings associated with TRNs to sleep stages and to provide new insights into the use of electrodermal activity (EDA) as a potential physiological marker of TRNs. Sixty veterans and active-duty service members were assessed by questionnaires and recorded for 5 consecutive nights in their homes.

RESULTS

Our approach firstly identified positive correlations between subjective and objective sleep parameters (total sleep time, sleep-onset latency and TRNs frequency). We also developed a method of synchronization between the two ambulatory devices that allowed us to match 200 TRNs (reported by event marker push button) with sleep stages corresponding to 91 nights and 37 patients. Most awakenings associated with TRNs occurred during NREM sleep (65.5% versus 34.5% during REM sleep). Our results also reveal significant differences in the frequency of EDA peaks 10 min before the reported events, with a lower frequency in REM (13.7 peaks) than in NREM (24.8 peaks) awakenings associated with TRNs. This EDA peaks frequency in REM sleep is not statistically different from that in REM sleep preceding awakenings that are not associated with TRNs.

CONCLUSION

The development of wearable devices to collect physiological parameters is of interest in clinical practice to improve our knowledge of sleep and trauma-related nightmares in patients with PTSD.

The association of polysomnographic sleep on posttraumatic stress disorder symptom clusters in trauma-exposed civilians and veterans

Study Objectives

Self-reported sleep disturbance has been established as a risk factor and predictor for posttraumatic stress disorder (PTSD); however, less is known about the relationship between objective sleep and PTSD symptom clusters, and the specific role of hyperarousal. The present study examined the relationships between sleep continuity and architecture on PTSD symptom clusters.

Methods

Participants underwent two in-laboratory sleep studies to assess sleep continuity and architecture. They also completed the Clinician-Administered PTSD-IV scale and the Structured Clinical Interview for the DSM-IV to assess for PTSD diagnosis and other psychiatric disorders.

Results

Sleep continuity (i.e. total sleep time, sleep efficiency percent, wake after sleep onset, sleep latency) was significantly related to PTSD Cluster B (reexperiencing) symptom severity (R ² = .27, p < .001). Sleep architecture, specifically Stage N1 sleep, was significantly associated with PTSD Cluster B (t = 2.98, p = .004), C (Avoidance; t = 3.11, p = .003), and D (Hyperarosual; t = 3.79, p < .001) symptom severity independently of Stages N2, N3, and REM sleep. REM sleep variables (i.e. REM latency, number of REM periods) significantly predicted Cluster D symptoms (R ² = .17, p = .002).

Conclusions

These data provide evidence for a relationship between objective sleep and PTSD clusters, showing that processes active during Stage N1 sleep may contribute to PTSD symptomatology in civilians and veterans. Further, these data suggest that arousal mechanisms active during REM sleep may also contribute to PTSD hyperarousal symptoms.This paper is part of the War, Trauma, and Sleep Across the Lifespan Collection. This collection is sponsored by the Sleep Research Society.

Post-traumatic stress disorder: clinical and translational neuroscience from cells to circuits

Post-traumatic stress disorder (PTSD) is a maladaptive and debilitating psychiatric disorder, characterized by re-experiencing, avoidance, negative emotions and thoughts, and hyperarousal in the months and years following exposure to severe trauma. PTSD has a prevalence of approximately 6-8% in the general population, although this can increase to 25% among groups who have experienced severe psychological trauma, such as combat veterans, refugees and victims of assault. The risk of developing PTSD in the aftermath of severe trauma is determined by multiple factors, including genetics - at least 30-40% of the risk of PTSD is heritable - and past history, for example, prior adult and childhood trauma. Many of the primary symptoms of PTSD, including hyperarousal and sleep dysregulation, are increasingly understood through translational neuroscience. In addition, a large amount of evidence suggests that PTSD can be viewed, at least in part, as a disorder that involves dysregulation of normal fear processes. The neural circuitry underlying fear and threat-related behaviour and learning in mammals, including the amygdala-hippocampus-medial prefrontal cortex circuit, is among the most well-understood in behavioural neuroscience. Furthermore, the study of threat-responding and its underlying circuitry has led to rapid progress in understanding learning and memory processes. By combining molecular-genetic approaches with a translational, mechanistic knowledge of fear circuitry, transformational advances in the conceptual framework, diagnosis and treatment of PTSD are possible. In this Review, we describe the clinical features and current treatments for PTSD, examine the neurobiology of symptom domains, highlight genomic advances and discuss translational approaches to understanding mechanisms and identifying new treatments and interventions for this devastating syndrome.

Amount of < 1Hz deep sleep correlates with melatonin dose in military veterans with PTSD

Military veterans with posttraumatic stress disorder often complain of non-restful sleep, which further exacerbates their symptoms. Our previous study showed a deficit in Lo Deep sleep, or slow oscillations, in the PTSD population compared to healthy control sleepers. Because Lo Deep sleep is likely a stage when the brain eliminates protein debris, it is critical to find the cause and effective therapeutics to reverse Lo Deep deficiency. The current study aims to replicate and extend this finding by examining several physiological and medication factors that may be responsible for the Lo Deep deficiency. We recorded overnight sleep electroencephalogram (EEG) via a 2-channel headband device on 69 veterans in a residential treatment facility. Dried urine samples were collected at 4 time points during one day to measure melatonin, cortisol, norepinephrine and other factors. EEG data were transformed into frequency power and submitted to an automated sleep scoring algorithm. The scoring corresponds to clear spectral patterns in the overnight spectrogram but does not align exactly with traditional visual scoring stages. As expected, veterans showed decreased Lo Deep (activity < 1 Hz) and more Hi Deep sleep (1-3 Hz activity) than healthy controls, replicating our previous study. Multiple linear regressions showed that melatonin dose and morning urine melatonin correlated with more Lo Deep sleep. Buspirone dose also correlated with more Lo Deep, but only 6 subjects were taking buspirone. Also replicating the findings from our last study were independent reductions of REM sleep with prazosin and sertraline. Other findings included decreased Lo and increased Hi Deep sleep with higher caffeine dose, and less Hi Deep percentage with higher testosterone. Finally, evening cortisol levels correlated with a higher percentage of Wake after sleep onset. These results confirm Lo Deep deficiency in this PTSD population and suggests melatonin as a possible therapeutic to reverse Lo Deep deficiency. This is a critical first step to establishing a systematic sleep assessment and treatment program in this and potentially other populations to prevent future brain pathology.

Sleep and PTSD in the Military Forces: A Reciprocal Relationship and a Psychiatric Approach

Sleep disturbances are well-recognised symptoms of Post-Traumatic Stress Disorder (PTSD). This review updates knowledge regarding the relationship between sleep during deployment, combat-related trauma, and PTSD in military personnel, from which the importance of restorative sleep results. The description of the characteristics of sleep in military forces with the considerable roles of the operational and training contexts highlights the important consequences of degraded sleep. Indeed, a lot of data suggest a dynamic link between sleep and the onset and chronicity of PTSD. We propose a reciprocal relationship model with strategies strongly recommended or already adopted by the military to promote restorative sleep before and after combat exposure. Among the alterations in a variety of sleep architecture and sleep patterns described in PTSD, the physiological hypothesis of REM sleep fragmentation in the development of PTSD symptoms may be important because REM sleep is generally associated with emotional memory. Finally, we address clinical and research perspectives that could be used to detect or restore sleep continuity before and during military deployment to possibly alleviate nightmares and insomnia related to combat exposure and PTSD occurrence and improve our understanding of sleep in PTSD.

Sleep parameters improvement in PTSD soldiers after symptoms remission

Eye movement desensitization and reprocessing (EMDR) is a psychotherapy for the treatment of posttraumatic stress disorder (PTSD). It is still unclear whether symptoms remission through EMDR therapy is associated with a beneficial effect on one of the PTSD symptoms, sleep disturbance. Our objective was therefore to study sleep parameters before and after symptom remission in soldiers with PTSD. The control group consisted of 20 healthy active duty military men who slept in a sleep lab with standard polysomnography (PSG) on two sessions separated by one month. The patient group consisted of 17 active duty military with PTSD who underwent EMDR therapy. PSG-recorded sleep was assessed 1 week before the EMDR therapy began and 1 week after PTSD remission. We found that the increased REMs density after remission was positively correlated with a greater decrease of symptoms. Also, the number of EMDR sessions required to reach remission was correlated with intra-sleep awakenings before treatment. These results confirm the improvement of some sleep parameters in PTSD after symptoms remission in a soldier's population and provide a possible predictor of treatment success. Further experiments will be required to establish whether this effect is specific to the EMDR therapy.

The spectral fingerprint of sleep problems in post-traumatic stress disorder

Study Objectives

Sleep problems are a core feature of post-traumatic stress disorder (PTSD). The aim of this study was to find a robust objective measure for the sleep disturbance in patients having PTSD.

Methods

The current study assessed EEG power across a wide frequency range and multiple scalp locations, in matched trauma-exposed individuals with and without PTSD, during rapid eye movement (REM) and non-REM (NREM) sleep. In addition, a full polysomnographical evaluation was performed, including sleep staging and assessment of respiratory function, limb movements, and heart rate. The occurrence of sleep disorders was also assessed.

Results

In patients having PTSD, NREM sleep shows a substantial loss of slow oscillation power and increased higher frequency activity compared with controls. The change is most pronounced over right-frontal sensors and correlates with insomnia. PTSD REM sleep shows a large power shift in the opposite direction, with increased slow oscillation power over occipital areas, which is strongly related to nightmare activity and to a lesser extent with insomnia. These pronounced spectral changes occur in the context of severe subjective sleep problems, increased occurrence of various sleep disorders and modest changes in sleep macrostructure.

Conclusions

This is the first study to show pronounced changes in EEG spectral topologies during both NREM and REM sleep in PTSD. Importantly, the observed power changes reflect the hallmarks of PTSD sleep problems: insomnia and nightmares and may thus be specific for PTSD. A spectral index derived from these data distinguishes patients from controls with high effect size, bearing promise as a candidate biomarker.

Adaptive latent state modeling of brain network dynamics with real-time learning rate optimization

Objective. Dynamic latent state models are widely used to characterize the dynamics of brain network activity for various neural signal types. To date, dynamic latent state models have largely been developed for stationary brain network dynamics. However, brain network dynamics can be non-stationary for example due to learning, plasticity or recording instability. To enable modeling these non-stationarities, two problems need to be resolved. First, novel methods should be developed that can adaptively update the parameters of latent state models, which is difficult due to the state being latent. Second, new methods are needed to optimize the adaptation learning rate, which specifies how fast new neural observations update the model parameters and can significantly influence adaptation accuracy.Approach. We develop a Rate Optimized-adaptive Linear State-Space Modeling (RO-adaptive LSSM) algorithm that solves these two problems. First, to enable adaptation, we derive a computation- and memory-efficient adaptive LSSM fitting algorithm that updates the LSSM parameters recursively and in real time in the presence of the latent state. Second, we develop a real-time learning rate optimization algorithm. We use comprehensive simulations of a broad range of non-stationary brain network dynamics to validate both algorithms, which together constitute the RO-adaptive LSSM.Main results. We show that the adaptive LSSM fitting algorithm can accurately track the broad simulated non-stationary brain network dynamics. We also find that the learning rate significantly affects the LSSM fitting accuracy. Finally, we show that the real-time learning rate optimization algorithm can run in parallel with the adaptive LSSM fitting algorithm. Doing so, the combined RO-adaptive LSSM algorithm rapidly converges to the optimal learning rate and accurately tracks non-stationarities.Significance. These algorithms can be used to study time-varying neural dynamics underlying various brain functions and enhance future neurotechnologies such as brain-machine interfaces and closed-loop brain stimulation systems.

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.

Sleep quality prediction in caregivers using physiological signals

Most caregivers of people with dementia (CPWD) experience a high degree of stress due to the demands of providing care, especially when addressing unpredictable behavioral and psychological symptoms of dementia. Such challenging responsibilities make caregivers susceptible to poor sleep quality with detrimental effects on their overall health. Hence, monitoring caregivers' sleep quality can provide important CPWD stress assessment. Most current sleep studies are based on polysomnography, which is expensive and potentially disrupts the caregiving routine. To address these issues, we propose a clinical decision support system to predict sleep quality based on trends of physiological signals in the deep sleep stage. This system utilizes four raw physiological signals using a wearable device (E4 wristband): heart rate variability, electrodermal activity, body movement, and skin temperature. To evaluate the performance of the proposed method, analyses were conducted on a two-week period of sleep monitored on eight CPWD. The best performance is achieved using the random forest classifier with an accuracy of 75% for sleep quality, and 73% for restfulness, respectively. We found that the most important features to detect these measures are sleep efficiency (ratio of amount of time asleep to the amount of time in bed) and skin temperature. The results from our sleep analysis system demonstrate the capability of using wearable sensors to measure sleep quality and restfulness in CPWD.

Catecholamines in Post-traumatic Stress Disorder: A Systematic Review and Meta-Analysis

Studies on the association between post-traumatic stress disorder (PTSD) and levels of catecholamines have yielded inconsistent results. The aim of this study was to conduct a systematic review and meta-analysis to assess whether concentrations of the catecholamines dopamine, norepinephrine, and epinephrine are associated with PTSD. This study searched relevant articles in the following databases: PubMed, Embase, Web of Science, and Psyc-ARTICLES. Each database was searched from its inception to September, 2018. Data related to catecholamine concentrations were extracted for patients with PTSD and the controls to calculate standardized mean differences and to evaluate effect sizes. A meta-analysis was then performed to compare the concentration of each catecholamine between the two groups in blood and/or urine samples. Heterogeneity was quantified using I² and its significance was tested using the Q statistics. Subgroup analyses of the types of controls, PTSD assessment tools, and assayed methods used in the studies were performed to explore sources of heterogeneity among studies. Random-effects models were used to combine results from selected studies. A total of 1,388 articles were identified, of which 27 were included in the final analysis. Heterogeneity was high; hence random-effects models were used to combine results of selected studies. Results revealed significantly higher norepinephrine levels in people with PTSD than in the controls [standardized mean difference (SMD) = 0.35, 95% confidence interval (CI): 0.13 to 0.57, p = 0.002]. No difference was found in dopamine and epinephrine concentrations between the two groups. Elevated norepinephrine levels may be an important indicator for PTSD.