REM Sleep Research Articles

Clinically probable RBD is an early predictor of malignant non-motor Parkinson’s disease phenotypes

Non-motor symptoms (NMS) in Parkinson’s disease (PD) significantly impact quality of life, especially in later stages. REM sleep behavior disorder (RBD) affects approximately 42% of all PD patients and frequently precedes motor PD symptoms. RBD is linked to increased rates of depression and cognitive decline. This study explores how early RBD can predict the development of NMS profiles in patients, comparing those with and without early RBD. We identified a unique NMS profile associated with early RBD. These patients had a higher rate of cognitive impairment (M2 = 326.84, p < 0.001), apathy (M2 = 332.93, p < 0.001), hallucinations (M2 = 480.05, p < 0.001), depression (M2 = 480.05, p < 0.0001), anxiety (corrected p < 0.01), impulse control disorders (M2 = 77.577, p < 0.001), and autonomic dysfunction (F = 251.8, p < 0001). A survival analysis revealed an association between early RBD and faster progression to cognitive impairment. These NMS profiles may play a critical role in stratifying patients for targeted interventions.

Altered Intra- and Inter-Network Resting-State Functional Connectivity is Associated with Neuropsychological Functioning and Clinical Symptoms in Patients with Isolated Rapid Eye Movement Sleep Behavior Disorder.

Isolated rapid-eye movement (REM) sleep behavior disorder (iRBD) is characterized by abnormal behaviors in REM sleep and is considered as a prodromal symptom of alpha-synucleinopathies. Resting-state functional magnetic resonance imaging (rsfMRI) studies have unveiled altered functional connectivity (rsFC) in patients with iRBD. However, the associations between intra- and inter-network rsFC with clinical symptoms and neuropsychological functioning in iRBD remain unclear. To characterize intra- and inter-network rsFC in iRBD patients using a data-driven approach and to assess its associations with clinical features and cognitive functioning. Forty-two patients with iRBD and 45 healthy controls (HC) underwent rsfMRI and comprehensive neuropsychological testing. Resting-state networks were characterized using independent component analyses. Group differences in intra- and inter-network rsFC and their associations with clinical and neuropsychological data were studied. A threshold of corrected P < 0.05 was used in all the analyses. iRBD patients displayed lower intra-network rsFC within basal ganglia, visual, sensorimotor, and cerebellar networks, relative to HC. Mean rsFC strength within the basal ganglia network positively correlated with processing speed and negatively with the non-motor symptoms in iRBD patients. Reduced inter-network rsFC between sensorimotor and visual medial networks was observed in iRBD patients, which was associated with global cognitive status. iRBD is characterized by both reductions in intra-network rsFC in cortical and subcortical networks and inter-network dysconnectivity between sensorimotor and visual networks. Abnormalities in intra- and inter-network rsFC are associated with cognitive performance and non-motor symptoms, suggesting the utility of both rsFC measures as imaging markers in prodromal alpha-synucleinopathies. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Association of rapid eye movement sleep latency with multimodal biomarkers of Alzheimer's disease.

Sleep disturbances are associated with Alzheimer's disease (AD)and Alzheimer's disease and related dementias (ADRD), but the relationship between sleep architecture, particularly rapid eye movement (REM) sleep, and AD/ADRD biomarkers remains unclear. We enrolled 128 adults (64 with Alzheimer's disease, 41 with mild cognitive impairment [MCI], and 23 with normal cognition [NC]), mean age 70.8±9.6 years, 56.9% female, from a tertiary hospital in China. Participants underwent overnight polysomnography (PSG), amyloid β (Aβ) positron emission tomography (PET), and plasma biomarker analysis: phosphorylated tau at threonine 181 (p-tau181), neurofilament light (NfL), and brain-derived neurotrophic factor (BDNF). After adjusting for demographics, apolipoprotein E (APOE) ε4 status, cognition, and comorbidities, the highest tertile of REM latency was associated with higher Aβ burden (β=0.08, 95% confidence interval [CI]: 0.03 to 0.13, p=0.002), elevated p-tau181 (β=0.19, 95% CI: 0.02 to 0.13, p=0.002), and reduced BDNF levels (β=-0.47, 95% CI: -0.68 to -0.13, p=0.013), compared to the lowest tertile. Prolonged REM latency may serve as a novel marker or risk factor for AD/ADRD pathogenesis. Rapid eye movement latency (REML) may be a potential marker for Alzheimer's disease and Alzheimer's disease and related dementias (AD/ADRD) pathogenesis. Prolonged REML was associated with higher amyloid beta (Aβ) burden, phosphorylated tau-181 (p-tau181), and lower brain-derived neurotrophic factor (BDNF) levels. Intervention trial is needed to determine if targeting REML can modify AD/ADRD risk. Slow-wave sleep was not associated with AD/ADRD biomarkers.

RADAR-AD: assessment of multiple remote monitoring technologies for early detection of Alzheimer’s disease

BackgroundAlzheimer’s disease (AD) is a progressive neurodegenerative disorder affecting millions worldwide, leading to cognitive and functional decline. Early detection and intervention are crucial for enhancing the quality of life of patients and their families. Remote Monitoring Technologies (RMTs) offer a promising solution for early detection by tracking changes in behavioral and cognitive functions, such as memory, language, and problem-solving skills. Timely detection of these symptoms can facilitate early intervention, potentially slowing disease progression and enabling appropriate treatment and care.MethodsThe RADAR-AD study was designed to evaluate the accuracy and validity of multiple RMTs in detecting functional decline across various stages of AD in a real-world setting, compared to standard clinical rating scales. Our approach involved a univariate analysis using Analysis of Covariance (ANCOVA) to analyze individual features of six RMTs while adjusting for variables such as age, sex, years of education, clinical site, BMI and season. Additionally, we employed four machine learning classifiers – Logistic Regression, Decision Tree, Random Forest, and XGBoost – using a nested cross-validation approach to assess the discriminatory capabilities of the RMTs.ResultsThe ANCOVA results indicated significant differences between healthy and AD subjects regarding reduced physical activity, less REM sleep, altered gait patterns, and decreased cognitive functioning. The machine-learning-based analysis demonstrated that RMT-based models could identify subjects in the prodromal stage with an Area Under the ROC Curve of 73.0 %. In addition, our findings show that the Amsterdam iADL questionnaire has high discriminatory abilities.ConclusionsRMTs show promise in AD detection already in the prodromal stage. Using them could allow for earlier detection and intervention, thereby improving patients’ quality of life. Furthermore, the Amsterdam iADL questionnaire holds high potential when employed remotely.

Exploring the Psychological and Physiological Insights Through Digital Phenotyping by Analyzing the Discrepancies Between Subjective Insomnia Severity and Activity-Based Objective Sleep Measures: Observational Cohort Study.

Insomnia is a prevalent sleep disorder affecting millions worldwide, with significant impacts on daily functioning and quality of life. While traditionally assessed through subjective measures such as the Insomnia Severity Index (ISI), the advent of wearable technology has enabled continuous, objective sleep monitoring in natural environments. However, the relationship between subjective insomnia severity and objective sleep parameters remains unclear. This study aims to (1) explore the relationship between subjective insomnia severity, as measured by ISI scores, and activity-based objective sleep parameters obtained through wearable devices; (2) determine whether subjective perceptions of insomnia align with objective measures of sleep; and (3) identify key psychological and physiological factors contributing to the severity of subjective insomnia complaints. A total of 250 participants, including both individuals with and without insomnia aged 19-70 years, were recruited from March 2023 to November 2023. Participants were grouped based on ISI scores: no insomnia, mild, moderate, and severe insomnia. Data collection involved subjective assessments through self-reported questionnaires and objective measurements using wearable devices (Fitbit Inspire 3) that monitored sleep parameters, physical activity, and heart rate. The participants also used a smartphone app for ecological momentary assessment, recording daily alcohol consumption, caffeine intake, exercise, and stress. Statistical analyses were used to compare groups on subjective and objective measures. Results indicated no significant differences in general sleep structure (eg, total sleep time, rapid eye movement sleep time, and light sleep time) among the insomnia groups (mild, moderate, and severe) as classified by ISI scores (all P>.05). Interestingly, the no insomnia group had longer total awake times and lower sleep quality compared with the insomnia groups. Among the insomnia groups, no significant differences were observed regarding sleep structure (all P>.05), suggesting similar sleep patterns regardless of subjective insomnia severity. There were significant differences among the insomnia groups in stress levels, dysfunctional beliefs about sleep, and symptoms of restless leg syndrome (all P≤.001), with higher severity associated with higher scores in these factors. Contrary to expectations, no significant differences were observed in caffeine intake (P=.42) and alcohol consumption (P=.07) between the groups. The findings demonstrate a discrepancy between subjective perceptions of insomnia severity and activity-based objective sleep parameters, suggesting that factors beyond sleep duration and quality may contribute to subjective sleep complaints. Psychological factors, such as stress, dysfunctional sleep beliefs, and symptoms of restless legs syndrome, appear to play significant roles in the perception of insomnia severity. These results highlight the importance of considering both subjective and objective assessments in the evaluation and treatment of insomnia and suggest potential avenues for personalized treatment strategies that address both psychological and physiological aspects of sleep disturbances. Clinical Research Information Service KCT0009175; https://cris.nih.go.kr/cris/search/detailSearch.do?seq=26133.

Calcineurin governs baseline and homeostatic regulations of non–rapid eye movement sleep in mice

Sleep need accumulates during waking and dissipates during sleep to maintain sleep homeostasis (process S). Besides the regulation of daily (baseline) sleep amount, homeostatic sleep regulation commonly refers to the universal phenomenon that sleep deprivation (SD) causes an increase of sleep need, hence, the amount and intensity of subsequent recovery sleep. The central regulators and signaling pathways that govern the baseline and homeostatic sleep regulations in mammals remain unclear. Here, we report that enhanced activity of calcineurin Aα (CNAα)-a catalytic subunit of calcineurin-in the mouse brain neurons sharply increases the amount (to ~17-h/d) and delta power-a measure of intensity-of non-rapid eye movement sleep (NREMS). Knockout of the regulatory (CnB1) or catalytic (CnAα and CnAβ) subunits of calcineurin diminishes the amount (to ~4-h/d) and delta power of baseline NREMS, but also nearly abrogates the homeostatic recovery NREMS following SD. Accordingly, mathematical modeling of process S reveals an inability to accumulate sleep need during spontaneous or forced wakefulness in calcineurin deficient mice. Moreover, calcineurin promotes baseline NREMS by antagonizing wake-promoting protein kinase A and, in part, by activating sleep-promoting kinase SIK3. Together, these results indicate that calcineurin is an important regulator of sleep need and governs both baseline and homeostatic regulations of NREMS in mice.

REM Refines and Rescues Memory Representations: A New Theory

Abstract Despite extensive evidence on the roles of non-rapid eye movement (NREM) and REM sleep in memory processing, a comprehensive model that integrates their complementary functions remains elusive due to a lack of mechanistic understanding of REM’s role in offline memory processing. We present the REM Refining and Rescuing (RnR) Hypothesis, which posits that the principal function of REM sleep is to increase the signal-to-noise ratio within and across memory representations. As such, REM sleep selectively enhances essential nodes within a memory representation while inhibiting the majority (Refine). Additionally, REM sleep modulates weak and strong memory representations so they fall within a similar range of recallability (Rescue). Across multiple NREM-REM cycles, tuning functions of individual memory traces get sharpened, allowing for integration of shared features across representations. We hypothesize that REM sleep’s unique cellular, neuromodulatory, and electrophysiological milieu, marked by greater inhibition and a mixed autonomic state of both sympathetic and parasympathetic activity, underpins these processes. The RnR Hypothesis offers a unified framework that explains diverse behavioral and neural outcomes associated with REM sleep, paving the way for future research and a more comprehensive model of sleep-dependent cognitive functions.

Breathtaking dreams: reduced REM phenotype in REM-related sleep apnea

PurposeThe expression of the respiratory events in OSA is influenced by different mechanisms. In particular, REM sleep can highly increase the occurrence of events in a subset of OSA patients, a condition dubbed REM-OSA (often defined as an AHI 2 times higher in REM than NREM sleep). However, a proper characterization of REM-OSA and its pathological sequelae is still inadequate, partly because of limitations in the current definitions.MethodsWe propose a new interpretation of the REM-OSA definition, extending it from a AHI-ratio to a two-dimensional space, considering both time and events ratios in REM over NREM separately. Within this space, we analyzed current definitions of REM-OSA in three large clinical dataset and identified the underlying sources of heterogeneity.ResultsWe observed that REM-OSA and REM-independent-OSA subgroups exist. Some subgroups exhibited abnormal REM characteristics (e.g., REM-OSA with reduced time in REM). Others had OSA features that are intermediate between REM-independent-OSA participants and those with a clear disproportion of REM events.ConclusionWe found that a time and events’ ratio of REM and NREM allow a more precise characterization of REM-OSA subgroups. Our new interpretation can be used to bolster new research into REM-OSA pathophysiological mechanisms.

Comprehensive assessment reveals numerous clinical and neurophysiological differences between MECP2-allelic disorders.

Rett syndrome (RTT) and MECP2 duplication syndrome (MDS) result from under- and overexpression of MECP2, respectively. Preclinical studies using genetic-based treatment showed robust phenotype recovery for both MDS and RTT. However, there is a risk of converting MDS to RTT, or vice versa, if accurate MeCP2 levels are not achieved. The aim of this study was to identify biomarkers distinguishing RTT from MDS. We prospectively enrolled 11 MDS and 6 male RTT like (MRL) individuals for a panel of clinical and neurophysiological assessments over two visits, 8-10 months apart. We identified numerous clinical and physiological features as promising biomarkers. MRL individuals exhibited large amplitude whole body tremor, midline stereotypies (vs. hand flapping at sides in MDS), earlier neuromotor regression, and earlier onset but less commonly refractory epilepsy. In the neurophysiological domain, we observed several marked differences in sleep physiology between MDS/MRL and typically developing (TD) individuals including reduced sleeping time, increased delta power during rapid eye movement (REM) sleep, decreased occipital alpha and increased brain-wide delta power during wakefulness, and reduced spindle density and duration. MRL individuals also had much lower delta power during NREM 2 and 3 stages than the TD group. We found differences in spindle duration in the temporal lobes and spindle amplitude in the frontal lobes between MDS and MRL. Our study revealed distinct clinical features of MDS and MRL that can be monitored during a clinical trial and may serve as target engagement, disease progression, or safety biomarkers for interventional studies.

Sleep-related drugs utilization and suicide behaviors: a population-based study in China

BackgroundPrevious studies have yielded conflicting findings regarding the relationship between the use of sleep-related drugs (SRDU) and suicidal behaviors. This population-based study aimed to analyze the associations between SRDU and suicidal behaviors. Additionally, we examined the associations between SRDU and specific conditional suicidal behaviors, providing insights into the impact of SRDU on the progression of suicidal behaviors.MethodsThe study was conducted among community residents aged 18 and older using a cross-sectional design, analyzing 21,376 participants. Data on SRDU, suicidal ideation, plans, and attempts were collected. Participants were categorized into general individuals without suicidal behaviors (GNS), suicidal ideators without a plan or attempt (SINPA), suicidal ideators with a plan but no attempt (SIP), and individuals who attempted suicide (SA). Insomnia, sleep apnea, rapid eye movement sleep behavior disorder (RBD), and narcolepsy were assessed using the Athens Insomnia Scale, Berlin Questionnaire, Rapid Eye Movement Sleep Behavior Disorder Questionnaire, and Ullanlinna Narcolepsy Scale, respectively.ResultsAfter adjusting for sociodemographic variables, insomnia, sleep apnea, RBD, and narcolepsy, SRDU showed a positive association with suicidal ideation (OR = 3.02), plans (OR = 4.78), and attempts (OR = 6.40; all p < 0.001). Compared to GNS, and after controlling for the same variables, SRDU was associated with SINPA (OR = 2.46), SIP (OR = 5.11), and SA (OR = 6.93; all p < 0.001) respectively. However, no significant differences in SRDU were found between SINPA, SIP, and SA (all p > 0.05).ConclusionsThis population-based study confirms that SRDU is positively associated with suicidal ideation, plans, and attempts, even after accounting for the risk factors of insomnia, sleep apnea, RBD, and narcolepsy. Nonetheless, SRDU does not appear to influence the progression from suicidal ideation to attempt.

Self-Similarity Analysis of Heartbeat Fluctuations in Sleep Among Female Shift Workers

Cardiovascular signals exhibit self-similarity characteristics, which are influenced by changes in autonomic nervous system (ANS) regulation caused by shift work. This study aims to assess the self-similarity properties of inter-beat interval (IBI) in healthy female shift workers and non-shift workers in different sleep stages to detect alterations in heartbeat fluctuations due to shift work. Short- and long-term self-similarity properties of the IBI signal ([Formula: see text] and [Formula: see text] scaling exponents, respectively) were analyzed using Detrended Fluctuation Analysis. Time and frequency indices were also calculated. In addition, Principal Component Analysis (PCA) was employed to reduce dimensionality and evaluate group separability based on the obtained features. Most indices showed similar values in the different sleep stages for both groups, but [Formula: see text] during light sleep and sympathovagal balance during REM sleep showed a significant decrease in shift workers compared to non-shift workers ([Formula: see text]). In addition, PCA was able to separate shift workers from non-shift workers and differentiate between nighttime and daytime sleep of workers. This analysis aids in identifying cardiovascular impairment associated with shift work and suggests a loss of ANS self-similarity in shift workers, indicating reduced adaptive capacity. Such alterations in ANS behavior could lead to serious health consequences related to cardiovascular disease.

Statistical Complexity Analysis of Sleep Stages.

Studying sleep stages is crucial for understanding sleep architecture, which can help identify various health conditions, including insomnia, sleep apnea, and neurodegenerative diseases, allowing for better diagnosis and treatment interventions. In this paper, we explore the effectiveness of generalized weighted permutation entropy (GWPE) in distinguishing between different sleep stages from EEG signals. Using classification algorithms, we evaluate feature sets derived from both standard permutation entropy (PE) and GWPE to determine which set performs better in classifying sleep stages, demonstrating that GWPE significantly enhances sleep stage differentiation, particularly in identifying the transition between N1 and REM sleep. The results highlight the potential of GWPE as a valuable tool for understanding sleep neurophysiology and improving the diagnosis of sleep disorders.

Audiovisual analysis of the diagnostic video polysomnography in patients with isolated REM sleep behavior disorder.

The diagnosis of isolated REM sleep behavior disorder (IRBD) requires video polysomnography (V-PSG) showing increased muscle activity and abnormal behaviors in REM sleep. To describe in IRBD the behavioral manifestations occurring during REM sleep in the diagnostic V-PSG. This is a systematic audiovisual V-PSG analysis of consecutive IRBD patients. According to the International RBD Study Group recommendations, REM sleep movements and vocalizations were classified into categories and severity. We analyzed the V-PSG of 62 IRBD patients with a mean age of 67.6 ± 8.1years. Of 6,330 30-s epochs of REM sleep, 55.1% epochs exhibited motor events, 5.5% contained vocalizations and 39.4% were silent. Among the epochs with motor manifestations, 66.1% contained simple minor movements, 25.0% simple major and 8.9% complex movements. Motor severity of the epochs was mild in 82.2%, moderate in 13.2% and severe in 4.6%. Most movements were bilateral (62.4%) and located in the upper limbs (42.5%). Of the epochs with vocalizations, 61.5% were simple minor, 20.7% complex and 17.8% simple major of mild (72.7%), moderate (23.0%) and severe (4.3%) severity. Complex movements occurred in 87.1% of the patients and complex vocalizations in 38.7%. In IRBD, the most common manifestations in REM sleep are simple minor movements and vocalizations of mild intensity. Complex movements are observed during REM sleep in most patients but are much less frequent than simple minor and major motor events. These findings should be considered for the routine diagnosis of IRBD when reviewing the V-PSG studies.

Role of REM Sleep in Dealing with Low Intensity Trauma as Natural/biological &amp; Informal Therapy

Role of REM Sleep in Dealing with Low Intensity Trauma as Natural/biological &amp; Informal Therapy

Sleep-wake patterns of fencing athletes: a long-term wearable device study.

Sleep is the most efficient means of recovery for athletes, guaranteeing optimal athletic performance. However, many athletes frequently experience sleep problems. Our study aims to describe the sleep-wake patterns of fencing athletes and determine whether factors, such as sex, competitive level and training schedules, could affect the sleep-wake rhythm. Sleep data from 23 fencing athletes were collected using the Huawei Band 6, monitoring key sleep parameters such as bedtime, wake time, duration of deep and light sleep, wake periods, REM sleep duration, and nap duration. During this period, athletes were required to wear the band continuously for 24 hours daily, except bathing, charging, and competition times. Athletes averaged 7.97 hours of sleep per night, with significant differences observed in wake time (p=0.015) and midpoint of sleep (p=0.048) between high-level and low-level athletes, as well as a higher frequency of naps among high-level (χ2=11.97, p=0.001) and female (χ2=3.88, p=0.049) athletes. Nap duration was negatively correlated with night sleep duration (r=-0.270, p<0.001). Athletes were observed for changes in sleep-wake patterns from Monday to Sunday. On Mondays, Wednesdays, and Fridays, when there was no morning training, the athletes' wake-up time and the midpoint of sleep were shifted significantly backward, and there were significant differences in sleep parameters between training days and rest days. The sleep patterns of athletes differ according to level and gender. The sleep-wake patterns of athletes are influenced by training schedules, indicating the presence of sleep rhythm disruption.

REM obstructive sleep apnea: prevalence and clinical associations in a high-altitude population.

REM-associated OSA (REM OSA) has a prevalence of 17-74% of all OSA cases. At high altitude and in Latin America, there are no data on REM OSA and its relationship to daytime sleepiness and comorbidities. This study aimed to determine the prevalence of REM OSA and the differences in clinical and polysomnographic characteristics between OSA and REM OSA in a population living at 2640 m. A retrospective cross-sectional study was conducted on adults in Bogotá, Colombia between January and December 2022. Patients were considered to have REM- OSA if they had a REM sleep duration of at least 30 minutes and the ratio of REM-AHI to NREM-AHI was > 2, and NREM-AHI < 15. For comparing the OSA and OSA REM groups, the X2 or Fisher's exact test was used for the qualitative variables and Student's t-test or its non-parametric counterpart for the quantitative variables. Patients with REM OSA and mild OSA had more severe nocturnal desaturation indices compared to mild NREM OSA. Patients with OSA had a higher prevalence of arterial hypertension and ischemic heart disease. REM OSA prevalence in a population living at high altitude was low compared with other studies. The patients with REM OSA and mild OSA had more severe nocturnal desaturation indexes compared to REM OSA at sea level. This study suggests a possible subgroup of patients with mild OSA at high altitude who may benefit from a discussion about initiating CPAP therapy.

Phasic dopamine release in the nucleus accumbens influences REM sleep timing.

Based on the activity of dopamine (DA) neurons during behavioral states, the DA system has long been thought to be foundational in regulating sleep-wake behavior; over the past decade advances in circuit manipulation and recording techniques have strengthened this perspective. Recently, several studies have demonstrated that DA release in regions of the limbic system is important in the promotion of REM sleep. Yet how DA dynamics change within bouts of sleep, how these changes are regulated, and whether they influence future state changes remains unclear. To address these questions, in mice of both sexes we used in vivo fiber photometry and inhibitory optogenetics to identify a specific role of DA transients in the nucleus accumbens (NAcc) in state transitions from NREM sleep. We found that DA transients increase their frequency and amplitude over the duration of NREM sleep and that this increase is more pronounced during NREM bouts that transition into REM sleep. Next, we found that DA transients in NREM sleep are influenced by changes in REM sleep pressure. Finally, we show that transient DA release in the NAcc plays a functional role in regulating the timing of REM sleep entrances, as inhibition of midbrain DA neuron terminals in the NAcc prolonged bouts of NREM sleep and decreased the frequency of bouts of REM sleep. These findings demonstrate that DA release in the NAcc is dynamically regulated by sleep pressure and has a functional role in transitions from NREM sleep, particularly those into REM sleep.Significance Statement Sleep is a central component of daily life and is heavily influenced by midbrain dopamine neurons. Dopamine release in limbic regions, such as the nucleus accumbens, has been implicated in the promotion of REM sleep. However, dopamine release dynamics during sleep and how these influence future changes in state remain unclear. We used a fluorescence-based dopamine biosensor to elucidate the pattern of dopamine release during sleep and inhibitory optogenetics to disrupt dopamine release. Dopamine release increases across the duration of NREM sleep bouts and is sensitive to REM sleep need. Inhibition of dopamine terminals in the nucleus accumbens decreases the frequency of REM sleep. This suggests that phasic dopamine release during NREM sleep functionally influences REM sleep timing.

Automated Detection of Isolated REM Sleep Behavior Disorder Using Computer Vision.

Isolated rapid eye movement (REM) sleep behavior disorder (iRBD) is, in most cases, an early stage of Parkinson's disease or related disorders. Diagnosis requires an overnight video-polysomnogram (vPSG), however, even for sleep experts, interpreting vPSG data is challenging. Using a 3D camera, automated analysis of movements has yielded high accuracy. We aimed to replicate and extend prior work using a conventional 2D camera. The dataset included 172 vPSG recordings from a clinical sleep center, 81 patients with iRBD and 91 non-RBD healthy controls (63 with a range of other sleep disorders and 28 healthy sleepers). An optical flow computer vision algorithm automatically detected movements during rapid eye movement (REM) sleep, from which features of rate, ratio, magnitude and velocity of movements, and ratio of immobility were extracted. Patients with iRBD exhibited an increased number of shorter movements and immobility periods. Accuracies for detecting iRBD ranged from 84.9% (with 2 features) to 87.2% (with 5 features). Combining all 5 features but only analyzing short (0.1-2 second duration) movements achieved the highest accuracy at 91.9%. Of the 11 patients with iRBD without noticeable movements during vPSG, 7 were correctly identified. This work improves prior art by using a 2D camera routinely used in sleep laboratories and improving performance by adding only 3 features. This approach could be implemented in clinical sleep laboratories to facilitate and improve the diagnosis of iRBD. Coupled with automated detection of REM sleep, it should also be tested in the home environment using conventional infrared cameras to detect and/or monitor RBD. ANN NEUROL 2025.

Fractal cycles of sleep, a new aperiodic activity-based definition of sleep cycles.

Sleep cycles are defined as episodes of non-rapid eye movement (non-REM) sleep followed by an episode of REM sleep. Fractal or aperiodic neural activity is a well-established marker of arousal and sleep stages measured using electroencephalography. We introduce a new concept of 'fractal cycles' of sleep, defined as a time interval during which time series of fractal activity descend to their local minimum and ascend to the next local maximum. We assess correlations between fractal and classical (i.e. non-REM - REM) sleep cycle durations and study cycles with skipped REM sleep. The sample comprised 205 healthy adults, 21 children and adolescents and 111 patients with depression. We found that fractal and classical cycle durations (89±34 vs 90±25 min) correlated positively (r=0.5, p<0.001). Children and adolescents had shorter fractal cycles than young adults (76±34 vs 94±32 min). The fractal cycle algorithm detected cycles with skipped REM sleep in 91-98% of cases. Medicated patients with depression showed longer fractal cycles compared to their unmedicated state (107±51 vs 92±38 min) and age-matched controls (104±49 vs 88±31 min). In conclusion, fractal cycles are an objective, quantifiable, continuous and biologically plausible way to display sleep neural activity and its cycles.

A predictive model for longitudinal cognitive subtypes in Parkinson's disease.

Longitudinal cognitive changes in Parkinson's disease (PD) exhibit considerable heterogeneity.Predicting cognitive trajectories in early PD patients can improve prognostic counseling and guide clinical trials. This study included 337 early PD patients with 6-year follow-up in the Parkinson's Progression Markers Initiative (PPMI) database.Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA) to identify subtypes of longitudinal cognitive trajectories, and a nomogram predictive model was constructed using baseline clinical variables. The 337 PD patientshad a mean age of 61.0years, mean disease duration of 0.55years,and mean MoCA score of 27.1 points. Latent class mixed models (LCMM) identified two longitudinal cognitive subtypes: cognitive stable (276 cases, 81.9%) and cognitivel deteriorating (61 cases, 18.1%). The cognitively deteriorating subtype presented poorer baseline cognition, older age, and more severe motor and non-motor symptoms. On biomarkers, the cognitively deteriorating subtype revealed higher serum NFL levels and lower mean striatum DAT uptake. Six baseline clinical variables (age, Letter Number Sequencing score, Symbol Digit Modalities Test score, Benton Judgment of Line Orientation Test score, Hopkins Verbal Learning Test-Revised score, and REM Sleep Behavior Disorder) were selected to construct the nomogram predictive model which achieved an AUC of 0.92.The calibration curve demonstrated high consistency between predicted and observed probabilities.The predictive model has potential utility in disease-modifying clinical trials by pre-screening patients at high risk for cognitive deterioration. This study identified two longitudinal cognitive subtypes: cognitive stable and cognitive deterioration within 6-year follow-up, and eighteen percent of early PD patients shared the cognitive deterioration subtype The predictive model, incorporating six baseline variables could estimate the risk of longitudinal cognitive deterioration in PD.