Rapid eye movement sleep (REMs) is characterized by activated electroencephalogram (EEG) and muscle atonia, accompanied by vivid dreams. REMs is homeostatically regulated, ensuring that any loss of REMs is compensated by a subsequent increase in its amount. However, the neural mechanisms underlying the homeostatic control of REMs are largely unknown. Here, we show that GABAergic neurons in the preoptic area of the hypothalamus projecting to the tuberomammillary nucleus (POAGAD2→TMN neurons) are crucial for the homeostatic regulation of REMs in mice. POAGAD2→TMN neurons are most active during REMs, and inhibiting them specifically decreases REMs. REMs restriction leads to an increased number and amplitude of calcium transients in POAGAD2→TMN neurons, reflecting the accumulation of REMs pressure. Inhibiting POAGAD2→TMN neurons during REMs restriction blocked the subsequent rebound of REMs. Our findings reveal a hypothalamic circuit whose activity mirrors the buildup of homeostatic REMs pressure during restriction and that is required for the ensuing rebound in REMs.

Sleep-related painful erection (SRPE) is a parasomnia defined by the repetition of painful erections during rapid eye movement (REM) sleep. Hypnic headache (HH) is a primary headache occurring exclusively at night, often during REM sleep. We report the observation of a 33-year-old man with simultaneous SRPE and HH. Physical examination was normal. Comprehensive urological and endocrine explorations excluded other organic differential diagnoses. Polysomnography revealed several awakenings in REM, due to SRPE and concurrent HH. Medication by baclofen at bedtime seemed to have resulted in a decrease in SRPE episodes, confirmed by polysomnography, but at the cost of excessive daytime sleepiness, and was discontinued by the patient. Caffeine intake at bedtime was proposed, but the patient was reluctant because he was concerned about worsening insomnia. At 9-month follow-up, the patient had accepted his medical condition and was coping with both SRPE and HH. He felt reassured and wished no \"overmedicalization.\" To our knowledge, the coexistence of both conditions has not yet been reported, yet their frequencies might be underestimated. We hypothesize a common underlying pathophysiology with a possible dysfunction of the vascular control and/or the autonomic nervous system and that could involve the hypothalamus. Somnologists should be aware of SRPE, potentially overlapping with HHs. SRPE should be considered in case of sleep-maintenance insomnia. Patient reassurance seems to be central in the care process of SRPE.
BACKGROUND: Moreau A, Monnier L, Medde A, Bourgin P, Ruppert E. Images: sleep-related painful erection with concomitant hypnic headache. J Clin Sleep Med. 2024;20(5):837-839.

Rapid eye movement (REM) sleep is the main sleep correlate of dreaming. Ponto-geniculo-occipital (PGO) waves are a signature of REM sleep. They represent the physiological mechanism of REM sleep that specifically limits the processing of external information. PGO waves look just like a message sent from the pons to the lateral geniculate nucleus of the visual thalamus, the occipital cortex, and other areas of the brain. The dedicated visual pathway of PGO waves can be interpreted by the brain as visual information, leading to the visual hallucinosis of dreams. PGO waves are considered to be both a reflection of REM sleep brain activity and causal to dreams due to their stimulation of the cortex. In this review, we summarize the role of PGO waves in potential neural circuits of two major theories, i.e., (1) dreams are generated by the activation of neural activity in the brainstem; (2) PGO waves signaling to the cortex. In addition, the potential physiological functions during REM sleep dreams, such as memory consolidation, unlearning, and brain development and plasticity and mood regulation, are discussed. It is hoped that our review will support and encourage research into the phenomenon of human PGO waves and their possible functions in dreaming.

Patients with neurocognitive disorders often battle sleep disturbances. Kynurenic acid is a tryptophan metabolite of the kynurenine pathway implicated in the pathology of these illnesses. Modest increases in kynurenic acid, an antagonist at glutamatergic and cholinergic receptors, result in cognitive impairments and sleep dysfunction. We explored the hypothesis that inhibition of the kynurenic acid synthesising enzyme, kynurenine aminotransferase II, may alleviate sleep disturbances. At the start of the light phase, adult male and female Wistar rats received systemic injections of either: (i) vehicle; (ii) kynurenine (100 mg kg-1; i.p.); (iii) the kynurenine aminotransferase II inhibitor, PF-04859989 (30 mg kg-1; s.c.); or (iv) PF-04859989 and kynurenine in combination. Kynurenine and kynurenic acid levels were evaluated in the plasma and brain. Separate animals were implanted with electroencephalogram and electromyogram telemetry devices to record polysomnography, and evaluate the vigilance states wake, rapid eye movement sleep and non-rapid eye movement sleep following each treatment. Kynurenine challenge increased brain kynurenic acid and resulted in reduced rapid eye movement sleep duration, non-rapid eye movement sleep delta power and sleep spindles. PF-04859989 reduced brain kynurenic acid formation when given prior to kynurenine, prevented disturbances in rapid eye movement sleep and sleep spindles, and enhanced non-rapid eye movement sleep. Our findings suggest that reducing kynurenic acid in conditions where the kynurenine pathway is activated may serve as a potential strategy for improving sleep dynamics.

UNASSIGNED: The objectives of this study were to determine the prevalence of sleep paralysis (SP) in medical students from the University of Buenos Aires (UBA).
UNASSIGNED: An ad hoc questionnaire based on the diagnosis of SP and a demographic survey was electronically presented to students of Internal Medicine at the School of Medicine of the UBA. The respondents answered both questionnaires using Google Forms®.
UNASSIGNED: The prevalence of SP was 40.7% (95% CI 33.5-47.8). A higher percentage of the respondents (76%) reported experiencing SP-related anxiety. An association between self-perceived quality of sleep and the incidence of SP was found (χ2: 12.712, P = 0.002). The highest frequency was hypnopompic SP (55.55%), and the highest percentage (55.4%) suffered from SP less than once every 6 months. Most respondents (59.5%) reported having started with SP symptoms after 18 years of age, and the highest percentage (66.2%) had exacerbated their symptoms at college. The frequency of the Incubus phenomenon was 14.5% (95% CI 6.2-23). Most respondents (70.8%) denied the association of SP with religious or paranormal beliefs.
UNASSIGNED: SP is highly prevalent in medical students and is associated with poor sleep habits and perceived poor sleep quality. Clinicians should be aware of this parasomnia to avoid a misdiagnosis of psychosis and inform sufferers of the nature of SP.

It has long been thought that links between affect and sleep are bidirectional. However, few studies have directly assessed the relationships between: (1) pre-sleep affect and sleep electroencephalogram (EEG) activity; and (2) sleep EEG activity and post-sleep affect. This study aims to systematically explore the correlations between pre-/post-sleep affect and EEG activity during sleep. In a community sample of adults (n = 51), we measured participants\' positive and negative affect in the evening before sleep and in the next morning after sleep. Participants slept at their residence for 1 night of EEG recording. Using Fourier transforms, the EEG power at each channel was estimated during rapid eye movement sleep and non-rapid eye movement sleep for the full range of sleep EEG frequencies. We first present heatmaps of the raw correlations between pre-/post-sleep affect and EEG power during rapid eye movement and non-rapid eye movement sleep. We then thresholded the raw correlations with a medium effect size |r| ≥ 0.3. Using a cluster-based permutation test, we identified a significant cluster indicating a negative correlation between pre-sleep positive affect and EEG power in the alpha frequency range during rapid eye movement sleep. This result suggests that more positive affect during the daytime may be associated with less fragmented rapid eye movement sleep that night. Overall, our exploratory results lay the foundation for confirmatory research on the relationship between daytime affect and sleep EEG activity.

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.

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.

Sleep and stress have complex interactions that are implicated in both physical diseases and psychiatric disorders. These interactions can be modulated by learning and memory, and involve additional interactions with the neuroimmune system. In this paper, we propose that stressful challenges induce integrated responses across multiple systems that can vary depending on situational variables in which the initial stress was experienced, and with the ability of the individual to cope with stress- and fear-inducing challenges. Differences in coping may involve differences in resilience and vulnerability and/or whether the stressful context allows adaptive learning and responses. We provide data demonstrating both common (corticosterone, SIH and fear behaviors) and distinguishing (sleep and neuroimmune) responses that are associated with an individual\'s ability to respond and relative resilience and vulnerability. We discuss neurocircuitry regulating integrated stress, sleep, neuroimmune and fear responses, and show that responses can be modulated at the neural level. Finally, we discuss factors that need to be considered in models of integrated stress responses and their relevance for understanding stress-related disorders in humans.

Rationale: A growing body of evidence suggests that sleep is critical for the adaptive processing and consolidation of emotional information into long-term memory. Previous research has indicated that emotional components of scenes particularly benefit from sleep in healthy groups, yet sleep-dependent emotional memory processes remain unexplored in clinical cohorts, including those with obstructive sleep apnea (OSA). This line of research is important as it will add to the understanding of how disrupted sleep in OSA contributes to both impaired cognition and emotion dysregulation. Objectives: To test the hypothesis that individuals with OSA will have impaired sleep-dependent memory consolidation, with the greatest impact being on memory for emotional content. Methods: In this study, a group of newly diagnosed patients with OSA (n = 26; 10 female; average age, 42.5 years) and a matched group of healthy control subjects (n = 24; 13 female; average age, 37 years) were enrolled in the study at Beth Israel Deaconess Medical Center. Participants encoded scenes with negative or neutral foreground objects placed on neutral backgrounds before a night of polysomnographically recorded sleep. In the morning, they completed a recognition test in which old and new scene objects and backgrounds, presented separately and one at a time, were judged as old, new, or similar compared with what had been previously viewed. Results: Patients with OSA had a deficit in recognition memory for the scenes. Overall recognition (the ability to recognize old items as either old or similar) was impaired across all scene elements, both negative and neutral objects and backgrounds, whereas specific recognition (correctly identifying old items as old) was impaired only for negative objects. Across all participants, successful overall recognition correlated positively with sleep efficiency and rapid eye movement (REM) sleep, whereas successful specific memory recognition correlated only with REM sleep. Conclusions: Our findings indicate that fragmented sleep and reduced REM sleep, both hallmarks of OSA, are associated with disruptions in general memory impairment and veridical memory for emotional content, which could alter emotional regulation and contribute to comorbid emotional distress in OSA.