Prior studies have discussed rapid eye movement (REM) sleep disturbance as a potential endophenotype of major depressive disorder (MDD). However, the neural substrates underlying the percentage of REM sleep duration (REM%) and its association with disease progression in MDD remain unclear.
One hundred and fourteen MDD patients and 74 healthy controls (HCs) underwent resting-state functional and perfusion magnetic resonance imaging (MRI) scans as well as overnight polysomnography examination to assess brain function and REM%, with 48 patients completing follow-up visits. Correlation and mediation analyses were conducted to investigate the associations among baseline REM%, multimodal brain imaging measures, and the improvement of depressive symptoms at follow-up in MDD.
We found voxel-wise correlations between baseline REM% and multimodal brain imaging metrics in many brain regions involved in sensorimotor, visual processing, emotion, and cognition in patients with MDD. Moreover, the baseline REM% was correlated with the improvement of depressive symptoms from acute to remitted status in patients through regulating brain activity in the left inferior temporal gyrus and cerebral blood flow in the bilateral paracentral lobule.
Our findings help to identify the neural underpinnings of REM% in depression and highlight REM% as a potential prognostic biomarker to predict disease progression. These may inform future novel interventions of MDD from the perspective of regulating REM sleep.

Rapid eye movement sleep fragmentation is hypothesised to be a reliable feature of insomnia, which may contribute to emotion dysregulation. Sleep restriction therapy, an effective intervention for insomnia, has the potential to reduce rapid eye movement sleep fragmentation through its manipulation of basic sleep-wake processes. We performed secondary data analysis of a randomised controlled trial to examine whether sleep restriction therapy reduces rapid eye movement sleep fragmentation in comparison to a matched control arm. Participants (n = 56; 39 female, mean age = 40.78 ± 9.08 years) were randomly allocated to 4 weeks of sleep restriction therapy or 4 weeks of time in bed regularisation. Ambulatory polysomnographic recordings were performed at baseline, week 1 and week 4. Arousals during rapid eye movement and non-rapid eye movement sleep were scored blind to group allocation. The following rapid eye movement sleep fragmentation index was the primary outcome: index 1 = (rapid eye movement arousals + rapid eye movement awakenings + non-rapid eye movement intrusions)/rapid eye movement duration in hours. Secondary outcomes were two further indices of rapid eye movement sleep fragmentation: index 2 = (rapid eye movement arousals + rapid eye movement awakenings)/rapid eye movement duration in hours; and index 3 = rapid eye movement arousals/rapid eye movement duration in hours. A non-rapid eye movement fragmentation index was also calculated (non-rapid eye movement arousals/non-rapid eye movement duration in hours). Linear-mixed models were fitted to assess between-group differences. There was no significant group difference for the primary rapid eye movement fragmentation index at week 1 (p = 0.097, d = -0.31) or week 4 (p = 0.741, d = -0.06). There was some indication that secondary indices of rapid eye movement fragmentation decreased more in the sleep restriction therapy group relative to control at week 1 (index 2: p = 0.023, d = -0.46; index 3: p = 0.051, d = -0.39), but not at week 4 (d ≤ 0.13). No group effects were found for arousals during non-rapid eye movement sleep. We did not find clear evidence that sleep restriction therapy modifies rapid eye movement sleep fragmentation. Small-to-medium effect sizes in the hypothesised direction, across several indices of rapid eye movement fragmentation during early treatment, demand further investigation in future studies.

Sleep disorders are common in Parkinson\'s disease (PD) and include alterations in sleep-related EEG oscillations.
This case-control study tested the hypothesis that patients with PD would have a lower density of Scalp-Slow Wave (SW) oscillations and higher slow-to-fast frequencies ratio in rapid eye movement (REM) sleep than non-PD controls. Other sleep-related quantitative EEG (qEEG) features were also examined, including SW morphology, sleep spindles, and Scalp-SW spindle phase-amplitude coupling.
Polysomnography (PSG)-derived sleep EEG was compared between PD participants (n = 56) and non-PD controls (n = 30). Following artifact rejection, sleep qEEG analysis was performed in frontal and central leads. Measures included SW density and morphological features of SW and sleep spindles, SW-spindle phase-amplitude coupling, and spectral power analysis in Non-REM (NREM) and REM. Differences in qEEG features between PD and non-PD controls were compared using two-tailed Welch\'s t-tests, and correction for multiple comparisons was performed per the Benjamini-Hochberg method.
SW density was lower in PD than in non-PD controls (F = 13.5, p\' = 0.003). The PD group also exhibited higher ratio of slow REM EEG frequencies (F = 4.23, p\' = 0.013), higher slow spindle peak frequency (F = 24.7, p\' < 0.002), and greater SW-spindle coupling angle distribution non-uniformity (strength) (F = 7.30, p\' = 0.034).
This study comprehensively evaluates sleep qEEG including SW-spindle phase amplitude coupling in PD compared to non-PD controls. These findings provide novel insights into how neurodegenerative disease disrupts electrophysiological sleep rhythms. Considering the role of sleep oscillatory activity on neural plasticity, future studies should investigate the influence of these qEEG markers on cognition in PD.

In our large-scale study, the correlation between obstructive sleep apnea (OSA) related to rapid eye movement (REM) sleep and cardiac autonomic dysfunction was assessed by standard polysomnography (PSG). Cardiac autonomic dysfunction was evaluated by the measurement of heart rate variability (HRV). The cardiovascular disease (CVD) risk was determined using the cross-sectional prevalence of CVD and its overall 10 year risk according to the Framingham risk score (FRS). 4152 individuals were included in the study. A higher apnea-hypopnea index during REM sleep (AHIREM ) was correlated with increased CVD risk. The adjusted odds ratios (95% CIs) for CVD prevalence and its high 10 year risk in participants having severe OSA during REM sleep (AHIREM  ≥30 events/h) were 1.452 (1.012-2.084) and 1.904 (1.470-2.466) in the demographic adjusted model and 1.175 (0.810-1.704) and 1.716 (1.213-2.427) in the multivariate adjusted model, respectively, compared with the group with a AHIREM of <5 events/h. Fully adjusted multivariate linear regression models showed the independent association between AHIREM and a more elevated ratio of low-frequency and high-frequency (LF/HF) and LF in normalised units [LF (n.u.)] (P = 0.042, P = 0.027 in all participants and P = 0.033, P = 0.029 in participants with AHI during non-REM sleep <5 events/h, respectively). Mediation analysis demonstrated that OSA during REM sleep and CVD risk was significantly mediated by LF/HF and LF (n.u.). OSA during REM sleep may be a marker behind CVD risk because it promotes cardiac autonomic dysfunction.

UNASSIGNED: To explore the effectiveness of using deep learning network combined Vision Transformer (ViT) and Transformer to identify patients with depressive disorder on the basis of their sleep electroencephalogram (EEG) signals.
UNASSIGNED: The sleep EEG signals of 28 patients with depressive disorder and 37 normal controls were preprocessed. Then, the signals were converted into image format and the feature information on frequency domain and spatial domain was retained. After that, the images were transmitted to the ViT-Transformer coding network for deep learning of the EEG signal characteristics of the rapid eye movement (REM) sleep and non-rapid eye movement (NREM) sleep in patients with depressive disorder and those in normal controls, respectively, and to identify patients with depressive disorder.
UNASSIGNED: Based on the ViT-Transformer network, after examining different EEG frequencies, we found that the combination of delta, theta, and beta waves produced better results in identifying depressive disorder. Among the different EEG frequencies, EEG signal features of delta-theta-beta combination waves in REM sleep achieved 92.8% accuracy and 93.8% precision for identifying depression, with the recall rate of patients with depression being 84.7%, and the F0.5 value being 0.917±0.074. When using the delta-theta-beta combination EEG signal features in NREM sleep to identify depressive disorder, the accuracy was 91.7%, the precision was 90.8%, the recall rate was 85.2%, and the F0.5 value was 0.914±0.062. In addition, through visualization of the sleep EEG of different sleep stages for the whole night, it was found that classification errors usually occurred during transition to a different sleep stage.
UNASSIGNED: Using the deep learning ViT-Transformer network, we found that the EEG signal features in REM sleep based on delta-theta-beta combination waves showed better effect in identifying depressive disorder.

Chronic insomnia disorder (CID) is a common sleep disorder, with a prevalence ranging from 6%-10% worldwide. Individuals with CID experience more fragmented sleep than healthy control patients do. They awaken frequently during the night and have a higher risk of injury from falling. Awakening from different sleep stages may have different effects on postural stability and waking performance. However, limited research has been conducted on this topic.
This prospective randomized crossover study was conducted between January 2015 and January 2017. We included 20 adults aged 20-65 years who fulfilled the diagnosis criteria for CID. Participants underwent 2 overnight polysomnography studies with an interval of at least 7 days. They were awakened during either rapid eye movement (REM) sleep or stage N1/N2 sleep alternatively. We compared measurements of static postural stability, vigilance scores, and neuropsychological tests between REM sleep and stage N1/N2 sleep awakening.
Polysomnography parameters between the 2 nights were comparable. Participants who were awakened from REM sleep had worse static postural stability than those with stage N1/N2 sleep awakening. Compared with stage N1/N2 sleep awakening, larger mean sway areas of center of pressure (P = .0413) and longer center-of-pressure mean distances (P = .0139) were found in REM sleep awakening. There were no statistically significant differences in vigilance scores or neuropsychological tests between the 2 nights.
REM sleep awakening was associated with worse static postural stability than was stage N1/N2 sleep awakening. No statistically significant differences were found in waking performance in alertness or in neuropsychological tests between stage N1/N2 and REM sleep awakening.
Yeh W-C, Chuang Y-C, Yen C-W, et al. Static postural stability and neuropsychological performance after awakening from REM and NREM sleep in patients with chronic insomnia: a randomized, crossover, overnight polysomnography study. J Clin Sleep Med. 2022;18(8):1983-1992.

BACKGROUND: Although recent studies have indicated an association between obstructive sleep apnea (OSA) and air pollution, they have reported inconsistent results. Moreover, few studies investigated the effects of short-term air pollution exposure.
OBJECTIVE: To estimate the health effects of short- and long-term exposure to traffic air pollution on mild OSA in Taipei.
METHODS: We collected participants\' data from Taipei Sleep Center and air pollution data from Taiwan Environmental Protection Administration. A spatiotemporal model was used to estimate the individual exposure level. Generalized linear models were used to assess the percent change of overall apnea-hypopnea index (AHI), AHI in rapid eye movement period (AHI-REM), AHI in non-REM (AHI-NREM), and oxygen desaturation index (ODI) associated with an interquartile (IQR) increase in personal pollution exposure. A generalized logistic model was used to estimate the ORs of different severities of OSA compared with the reference group.
RESULTS: In the patients with AHI of <15, both short- and long-term exposure to NO2 were significantly associated with AHI and ODI increases: an IQR increase in 2-year mean NO2 increased 7.3% of AHI and 8.4% of ODI; these values were the highest among all exposure windows. The effects of NO2 on AHI increase were stronger in the men and younger patients. Moreover, the association between AHI and NO2 in the patients with AHI of <15 was mediated by the REM stage. NO2 exposure was associated with an increased risk of mild OSA that reached up to 24.8% per IQR increase in NO2 averaged over 2 years. PM2.5 exerted no effects on AHI, but an IQR increase in 1-year and 2-year mean PM2.5 was associated with 6.8% and 8.8% increases in ODI, respectively.
CONCLUSIONS: Both short- and long-term exposure to traffic air pollution were associated with the risk of mild OSA, which was modified by REM stage.

The central nucleus of the amygdala (CNA) projects to brainstem regions that generate and regulate rapid eye movement sleep (REM). We used optogenetics to assess the influence of CNA inputs into reticularis pontis oralis (RPO), pedunculopontine tegmentum (PPT) and nucleus subcoeruleus (SubC) on dark period sleep. We compared these results to effects of microinjections into CNA of the GABAA agonist, muscimol (MUS, inhibition of cell bodies) and tetrodotoxin (TTX, inhibition of cell bodies and fibers of passage). For optogenetics, male Wistar rats received excitatory (AAV5-EF1a-DIO -hChR2(H134R)-EYFP) or inhibitory (AAV-EF1a-DIO-eNpHR3.0-EYFP; DIO-eNpHR3.0) opsins into CNA and AAV5-EF1a-mCherry-IRES-WGA-Cre into RPO, PPT, or SubC. This enabled only CNA neurons synaptically connected to each region to express opsin. Optic cannulae for light delivery into CNA and electrodes for determining sleep were implanted. Sleep was recorded with and without blue or amber light stimulation of CNA. Separate rats received MUS or TTX into CNA prior to recording sleep. Optogenetic activation of CNA neurons projecting to RPO enhanced REM and did not alter non-REM (NREM) whereas activation of CNA neurons projecting to PPT or SubC did not significantly affect sleep. Inhibition of CNA neurons projecting to any region did not significantly alter sleep. TTX inactivation of CNA decreased REM and increased NREM whereas muscimol inactivation did not significantly alter sleep. Thus, the amygdala can regulate decreases and increases in REM, and RPO is important for CNA promotion of REM. Fibers passing through CNA, likely from the basolateral nucleus of the amygdala, also play a role in regulating sleep.

Various lines of evidence suggest that a bidirectional relationship exists between poor sleep quality and chronic pain, with each condition tending to promote and exacerbate the other. This has led to the hypothesis that the two conditions may be linked by common underlying mechanisms. It has thus been suggested that inadequate sleep and chronic pain may share neurophysiological and molecular pathways that are similar or overlapping. Some studies based on self-report measures have tended to support the inference that chronic neck pain may promote sleep disturbance, but this association has not, until now, been investigated with quantitative measures. The present study is the first to evaluate the sleep quality of patients with chronic neck pain through the use of polysomnography. The study sought to identify the sleep characteristics of patients with chronic neck pain and then to determine whether these characteristics were associated with the severity of their neck pain. Laboratory testing with polysomnography was carried out on 32 males who had complaints of chronic neck pain and on 12 healthy participants who served as controls. Compared to the control subjects, patients with chronic neck pain were found to have significantly shorter times spent in sleep (p = 0.015), longer latencies to sleep onset (p = 0.015) and rapid eye movement (REM) sleep (p < 0.05), longer durations spent in Stage 1 (p < 0.05), and shorter durations spent in both Stage 2 (p = 0.001) and REM sleep (p = 0.00). The severity of discomfort was related negatively to the amount of time spent in REM sleep. The present study\'s quantitative measures corroborate the view that patients with chronic neck pain have poor sleep quality. These findings confirm long-held clinical observations that the sleep quality of patients with chronic neck pain is compromised, and that, in this clinical group, poor sleep is at least a correlate of and may be an amplifier of perceived pain.

OBJECTIVE: Obstructive sleep apnea (OSA) during rapid eye movement (REM) stage of sleep is gaining importance in recent years. This study was done to determine the proportion of REM-related OSA and its associated polysomnographic features.
METHODS: One hundred forty-two patients were included in the study. REM-related OSA was defined based on previously established broad and strict criteria (REM apnea-hypopnea index [AHI]/non-REM [NREM] AHI ratio ≥2 and REM AHI >5 with NREM AHI <5, respectively), and its association with polysomnographic features was studied using appropriate statistical tools.
RESULTS: The proportion of REM-related OSA in the study was 56.3% and 25.3% as per broad and strict criterion, respectively. The REM-related OSA group had a mean younger age (47.4 ± 13.2 years) as compared to NREM-related OSA group (52.6 ± 15.8 years). Females (34 out of 45; 75.6%) were more likely to have REM-related OSA as compared to males (46 out of 107; 47.4%). Supine AHI, arousal index, oxygen desaturation index, length of the longest event, and the lowest oxygen saturation recorded during sleep had a significant association with REM-related OSA. 74% of patients with overall AHI <5 and 87% patients with overall AHI 5 to 15 satisfied the criteria for REM-related OSA as per broad criterion.
CONCLUSIONS: REM-related OSA was quite prevalent in the study population (56.3%) and was more common in the mild and moderate severity subgroups of OSA.