Search Results (611)

In addition to characteristic and easily identifiable behavioural signs—namely epileptic seizures—electroencephalography (EEG) has long been a standard component of epilepsy diagnosis protocols. In veterinary practice, EEG is typically performed in a semi-invasive manner, using subcutaneous electrodes and sedation. Here, we propose that the non-invasive polysomnography protocol, originally developed for basic research, can serve as a more welfare-friendly yet informative alternative for assessing epileptic brain activity in dogs. In this study, N = 11 family dogs diagnosed with epilepsy underwent a single non-invasive polysomnography session. EEG-based evidence for epileptic activity was detected in two cases. Polysomnography data from these 11 epileptic dogs were further analysed to evaluate sleep structure parameters. Compared to a matched control group of N = 11 clinically healthy dogs, the epileptic group exhibited reduced sleep efficiency, increased sleep latency, more wakings after sleep onset, and less time spent in drowsiness and non-REM sleep. These findings support the potential utility of non-invasive brain monitoring techniques, such as polysomnography, in the diagnosis and management of epilepsy in veterinary medicine. Full article

The automatic classification of sleep stages and Cyclic Alternating Pattern (CAP) subtypes from electroencephalogram (EEG) recordings remains a significant challenge in computational sleep research because of the short duration of CAP events and the inherent class imbalance in clinical datasets. Background/Objectives: The research introduces a domain-specific deep learning system that employs an LSTM network optimized through a PSO-Hyperband hybrid hyperparameter tuning method. Methods: The research enhances EEG-based sleep analysis through the implementation of hybrid optimization methods within an LSTM architecture that addresses CAP sequence classification requirements without requiring architectural changes. Results: The developed model demonstrates strong performance on the CAP Sleep Database by achieving 97% accuracy for REM and 96% accuracy for stage S0 and ROC AUC scores exceeding 0.92 across challenging CAP subtypes (A1–A3). The model transparency is improved through the application of SHAP-based interpretability techniques, which highlight the role of spectral and morphological EEG features in classification outcomes. Conclusions: The proposed framework demonstrates resistance to class imbalance and better discrimination between visually similar CAP subtypes. The results demonstrate how hybrid optimization methods improve the performance, generalizability, and interpretability of deep learning models for EEG-based sleep microstructure analysis. Full article

Background/Objectives: Rapid eye movements (REMs) during sleep were initially associated with dreaming, suggesting a relationship between REMs and dream content; however, this hypothesis was questioned by their differences with the REMs during wakefulness and the evidence that REMs are also present in blind individuals with no visual dreaming. Successive studies have focused on the phenomenology and physiological significance of REMs during sleep. REMs are categorized as expressions of the phasic REM component, which is characterized by bursts of eye movements, whereas the tonic REM component is characterized by quiescent periods without eye movements. Methods: The study is a retrospective analysis of 105 sleep records from 15 subjects. We analyzed the two components, tonic and phasic REM, across the sleep period, the REM activity in the first 5 min and in the last 5 min of each REM period were also assessed. Results: Phasic epochs were more represented than tonic epochs across the whole night period. REM activity in the first and last five minutes of an REM period presented different, although non-significant, patterns across the night. REM activity in the first 5 min showed a curvilinear profile, whereas REM activity in the last 5 min showed a linear increasing trend. A significant correlation was found between the REM activity in the first 5 min of the REM period and the total duration of the REM period. Conclusions: According to our results, the analysis of REM activity and the focus on segments of an REM period could provide more information both on the temporal evolution of REM activity within an REM period and on the possible role of REMs in REM sleep regulation and its significance in psychiatric and neurological disorders. Full article

Sleep is a vital physiological process for recovery and health. In people with knee osteoarthritis (OA), disrupted sleep is common and linked to worse clinical outcomes. Commercial sleep trackers provide an accessible option to monitor sleep in this population, but their accuracy for detecting sleep, wake, and sleep stages remains uncertain. This study compared nighttime sleep data from polysomnography (PSG) and Fitbit Sense in individuals with knee OA and insomnia. Data were collected from 53 participants (60.4% women, mean age 51 ± 8.2 years) over 62 nights using simultaneous PSG and Fitbit recording. Fitbit Sense showed high accuracy (85.76%) and sensitivity (95.95%) for detecting sleep but lower specificity (50.96%), indicating difficulty separating quiet wakefulness from sleep. Agreement with PSG was higher on nights with longer total sleep time, higher sleep efficiency, shorter sleep onset, and fewer awakenings, suggesting better performance when sleep is less fragmented. The device showed limited precision in classifying sleep stages, often misclassifying deep and REM sleep as light sleep. Despite these issues, Fitbit Sense may serve as a useful complementary tool for monitoring sleep duration, timing, and regularity in this population. However, sleep stage and fragmentation data should be interpreted cautiously in both clinical and research settings. Full article

The organization of consciousness is described through increasingly rich theoretical models. We review evidence that working memory capacity—essential to generating consciousness in the cerebral cortex—is supported by dual limbic memory systems. These dorsal (Papez) and ventral (Yakovlev) limbic networks provide the basis for mnemonic processing and prediction in the dorsal and ventral divisions of the human neocortex. Empirical evidence suggests that the dorsal limbic division is (i) regulated preferentially by excitatory feedforward control, (ii) consolidated by REM sleep, and (iii) controlled in waking by phasic arousal through lemnothalamic projections from the pontine brainstem reticular activating system. The ventral limbic division and striatum, (i) organizes the inhibitory neurophysiology of NREM to (ii) consolidate explicit memory in sleep, (iii) operating in waking cognition under the same inhibitory feedback control supported by collothalamic tonic activation from the midbrain. We propose that (i) these dual (excitatory and inhibitory) systems alternate in the stages of sleep, and (ii) in waking they must be balanced—at criticality—to optimize the active inference that generates conscious experiences. Optimal Bayesian belief updating rests on balanced feedforward (excitatory predictive) and feedback (inhibitory corrective) control biases that play the role of prior and likelihood (i.e., sensory) precision. Because the excitatory (E) phasic arousal and inhibitory (I) tonic activation systems that regulate these dual limbic divisions have distinct affective properties, varying levels of elation for phasic arousal (E) and anxiety for tonic activation (I), the dual control systems regulate sleep and consciousness in ways that are adaptively balanced—around the entropic nadir of E–I criticality—for optimal self-regulation of consciousness and psychological health. Because they are emotive as well as motive control systems, these dual systems have unique qualities of feeling that may be registered as subjective experience. Full article

Sleep paralysis (SP), an REM parasomnia, can be characterized as one of the symptoms of narcolepsy. The SP phenomenon involves regaining meta-consciousness by the dreamer during REM, when the physiological atonia of skeletal muscles is accompanied by visual and auditory hallucinations that are perceived as vivid and distressing nightmares. Sensory impressions include personification of an unknown presence, strong chest pressure sensation, and intense fear resulting from subjective interaction with the unfolding nightmare. While the mechanism underlying skeletal muscle atonia is known, the physiology of hallucinations remains unclear. Their complex etiology involves interactions among various membrane receptor systems and neurotransmitters, which leads to altered neuronal functionality and disruptions in sensory perception. According to current knowledge, serotonergic activation of 5-hydroxytryptamine-receptor-2A (5-HT2A)-associated pathways plays a critical role in promoting hallucinogenesis during SP. Furthermore, they share similarities with psychedelic-substance-induced ones (i.e., LSD, psilocybin, and 2,5-dimethoxy-4-iodoamphetamine). These compounds also target the 5-HT2A receptor; however, their molecular mechanism varies from serotonin-induced ones. The current review discusses the intracellular signaling pathways responsible for promoting hallucinations in SP, highlighting the critical role of β-arrestin-2. We propose that the β-arrestin-2 signaling pathway does not directly induce hallucinations but creates a state of network susceptibility that facilitates their abrupt emergence in sensory areas. Understanding the molecular basis of serotonergic hallucinations and gaining better insight into 5-HT2A-receptor-dependent pathways may prove crucial in the treatment of multifactorial neuropsychiatric disorders associated with the dysfunctional activity of serotonin receptors. Full article

Background: More than merely determining our sleep pattern, our body’s internal clock also improves the quality of our sleep, alleviates the symptoms of depression, and maintains the balance of our gut flora. Methods: We carried out a 12-week randomized controlled trial with 99 adults from Kolkata, New Delhi, and Pune who reported sleep problems and symptoms of depression or anxiety. Participants received either a probiotic formulated to improve sleep quality and reduce depressive symptoms or a placebo. We tracked sleep using overnight studies and wearable devices, assessed depressive symptoms with standardized questionnaires, and analyzed stool samples to profile gut bacteria and their metabolites using gene sequencing and metabolomics. Advanced statistics and machine learning helped us pinpoint the key microbial and metabolic factors tied to sleep and mental health. Results: At the start, participants with disrupted sleep and depressive symptoms had fewer beneficial gut bacteria like Bifidobacterium and Lactobacillus, more inflammation-related microbes, and lower levels of helpful short-chain fatty acids. These imbalances were linked to poorer sleep efficiency, less REM sleep, and higher depression and anxiety scores. After 12 weeks, those taking the circadian-supporting probiotic saw a statistically significant increase in beneficial gut bacteria, improved sleep efficiency (+7.4%, p = 0.02), and greater reductions in depression and anxiety compared to the placebo. Increases in SCFA-producing bacteria most strongly predicted improvements. Conclusions: Our results show that taking a probiotic supplement can help bring your gut back into balance, support better sleep, and lift symptoms of depression and anxiety. This offers a hopeful and practical option for people looking for real relief from these deeply connected challenges. Full article

In the United States, the Clozapine Risk Evaluation and Mitigation Strategy (REMS) program was implemented to ensure safe prescription and monitoring; however, its administrative complexity has often resulted in unintended barriers to access. Clozapine remains the most effective antipsychotic for treatment-resistant schizophrenia (TRS), yet its use continues to be constrained by outdated regulatory frameworks, cultural inertia, and clinical hesitancy. This perspective article revisits the pharmacokinetic foundations of clozapine, re-examines its association with fatal outcomes, and critiques the persistence of obsolete monitoring systems such as the U.S. REMS program. Drawing on recent consensus publications endorsed by over 120 international clozapine experts, this article outlines the proposed changes to the U.S. prescription information and contextualizes them within broader global practices. This article argues that many barriers to clozapine use stem not from evidence, but from regulatory conservatism and the perpetuation of clinical myths. The dismantling of the REMS program in early 2025 represents a pivotal moment, yet further reforms are urgently needed to align regulatory guidance with contemporary science. Ultimately, this article is a call to rediscover the clinical value of clozapine and to translate decades of knowledge into regulatory and clinical action. Full article

Sub-Saharan Africa’s (SSA) corporate environment, like many emerging markets, is marked by institutional voids, weak oversight structures, and patriarchal leadership norms, which heighten the risk of real earnings management (REM). This study examines how CEO characteristics and audit committee gender diversity influence REM among listed manufacturing firms in 12 SSA countries from 2012 to 2023. Anchored in agency theory and Upper Echelon Theory, this study draws on 1189 firm-year observations and employs Pooled OLS, Random Effects, Fixed Effects, Feasible Generalised Least Squares (FGLS), and System GMM estimators. Findings show that female CEOs are consistently associated with lower REM, underscoring the ethical conservatism linked to gender-inclusive leadership. CEO ownership shows a positive and significant association with REM in System GMM, though findings vary across models, indicating potential institutional effects. The firm size is negatively and significantly related to REM in Pooled, RE, and FGLS models, but becomes nonsignificant in FE and System GMM, suggesting the role of external scrutiny may be sensitive to model dynamics. Leverage exhibits a positive and significant relationship with REM in most models, but turns negative and nonsignificant under System GMM, pointing to endogeneity concerns. Interaction effects and country-specific regressions affirm that governance impacts differ across contexts. Policy reforms should prioritise gender-diverse leadership and tailored oversight mechanisms. Full article

Rare earth metals (REMs) are vital for high-tech industries, but their extraction from secondary sources is challenging due to environmental and technical constraints. This study investigates the ion-exchange extraction of light REMs (neodymium, praseodymium, and samarium) from sulfuric and phosphoric acid solutions, modeling industrial leachates from apatite concentrates and phosphogypsum. The study considers the use of anion- and cation-exchange resins with different functional groups for efficient and environmentally safe REM separation. Experimental sorption isotherms were obtained under static conditions at 298 K and analyzed using a thermodynamic model based on the linearization of the mass action equation. Equilibrium constants and Gibbs energy were calculated, which reveals the spontaneity of the processes. Cation-exchange resins demonstrated high selectivity towards individual REMs, while anion-exchange resins were suitable for group extraction. Infrared spectral analysis confirmed the presence of sulfate and phosphate complexes in the resin matrix, clarifying the ion-exchange mechanisms. Thermal effect measurements indicated exothermic sorption on anion-exchange resins with negative entropy and endothermic sorption on cation-exchange resins with positive entropy. The findings highlight the potential of ion-exchange resins for selective and sustainable REM recovery, offering a safer alternative to liquid extraction and enabling the valorization of industrial wastes like phosphogypsum for resource recovery. Full article

Background/Objectives: There is limited data on well-documented comorbidities with polysomnography (PSG)/multiple sleep latency test (MSLT) findings in idiopathic hypersomnia (IH). We aimed to characterize the clinical, PSG/MSLT characteristics of IH patients in our health network. Methods: We reviewed charts of all IH cases between 2000 and 2023, extracting clinical features, comorbidities, and PSG/MSLT findings. Results: One hundred forty-two patients (83.80% female) with IH were included. Compared to those without mood disorders, both major depressive disorder (MDD) and anxiety patients were older at onset (27.10 ± 8.32 and 26.76 ± 8.40 versus 23.23 ± 6.94 and 24.05 ± 7.31 years; p = 0.003 and p = 0.042) and had lower ESS (15 versus 19; 15.67 versus 17.75; p < 0.0001), more disrupted sleep (28 (36.36%) versus 8 (12.31%); p = 0.001; 24 (35.82%) versus 12 (16%); p = 0.007), and less sleep inertia (30 (38.96%) versus 38 (58.46%); p = 0.021; 26 (38.81%) versus 42 (56%); p = 0.04). Fifteen patients with dysautonomia disorders presented at an earlier age (21.80 ± 6.60 versus 25.75 ± 8, p = 0.0682). On MSLT, MDD, anxiety, and dysautonomia patients had longer sleep latencies than the non-affected counterparts (6.40 (5.40–7.60) minutes versus 3.60 (2.60–5.40) min., <0.0001; 6.20 (5.20–7.40) versus 4 (2.60–6.40) minutes; p < 0.0001; 7.40 (6–7.80) versus 5.40 (3–7); p = 0.008). MDD and anxiety cases had fewer sleep onset REM periods (7 (9.09%) versus 16 (24.62%), p = 0.0124 and 6 (8.96%) versus 17 (22.67%), p = 0.0388) compared to those not affected by these disorders. Conclusions: Our study highlights the importance of recognizing mood disorders and dysautonomia in patients diagnosed with IH. Further research may elucidate management strategies for these patients. Full article

Background/Objectives: We present a novel approach for detecting generalized sleep pathologies through the fractal analysis of single-channel electroencephalographic (EEG) signals. We propose that the fractal scaling exponent of permutation entropy time series serves as a robust biomarker of pathological sleep patterns, capturing alterations in brain dynamics across multiple disorders. Methods: Using two public datasets (Sleep-EDF and CAP Sleep Database) comprising 200 subjects (112 healthy controls and 88 patients with various sleep pathologies), we computed the fractal scaling of the permutation entropy of these signals. Results: The results demonstrate significantly reduced scaling exponents in pathological sleep compared to healthy controls (mean = 1.24 vs. 1.06, $p<0.001$), indicating disrupted long-range temporal correlations in neural activity. The method achieved 90% classification accuracy for rapid-eye-movement (REM) sleep behavior disorder (F1-score: 0.89) and maintained 74% accuracy when aggregating all pathologies (insomnia, narcolepsy, sleep-disordered breathing, etc.). Conclusions: The advantages of this approach, including compatibility with single-channel EEG (enabling potential wearable applications), independence from sleep-stage annotations, and generalizability across recording montages and sampling rates, stablish a framework for non-specific sleep pathology detection. This is a computationally efficient method that could transform screening protocols and enable earlier intervention. The robustness of this biomarker could enable straightforward clinical applications for common sleep pathologies as well as diseases associated with neurodegenerative conditions. Full article

Background/Objectives: This study aimed to investigate the effect of age at symptom onset on rapid eye movement (REM) sleep latency and sleep-onset REM period (SOREMP) distribution in multiple sleep latency tests (MSLTs) in patients with narcolepsy. Methods: This was a retrospective multicenter chart review of 135 newly diagnosed drug-naïve patients with narcolepsy who underwent MSLT and fulfilled the diagnostic criteria for narcolepsy. The age at onset was defined as the first occurrence of excessive daytime sleepiness or cataplexy. We investigated sleep onset latency, REM sleep latency, and the presence of SORMEP in each nap trial of the MSLT. The clinical, polysomnography, and MSLT findings were compared between the early- and late-onset groups. Correlation and linear regression analyses were used to assess the effect of age at onset as a continuous variable, and survival analyses confirmed its impact on the MSLT parameters. Results: The mean age at onset was 18.3 ± 8.8 years. Patients with early onset had a higher rate of SOREMPs than late-onset patients in the first MSLT nap (81.9% vs. 63.3%, p = 0.031). However, the severity of the narcolepsy symptoms did not differ between the groups. In linear regression analysis, age at onset was significantly associated with MSLT REM sleep latency (β = 0.049, p = 0.033) after adjusting for confounders. Survival analysis confirmed that an early onset of narcolepsy was associated with a higher probability of SOREMPs in the first MSLT nap (hazard ratio 0.955, p = 0.001). Conclusions: A younger age at narcolepsy onset was associated with shorter REM sleep latency and higher SOREMP probability in MSLT. These findings indicate that the early onset of narcolepsy may be linked to greater disease severity in terms of REM sleep dysregulation. Full article

Introduction: The monitoring of autonomic nervous balance during childhood remains underexplored. However, heart rate variability (HRV) is widely recognized as a biomarker of health risk across the lifespan. Juvenile idiopathic arthritis (JIA), a group of chronic inflammatory joint disorders, is associated with persistent inflammation and pain, both of which contribute to increased cardiovascular risk, commonly linked to reduced HRV. Among HRV parameters, very-low frequency (VLF) components have been associated with physiological recovery processes. This study aimed to assess HRV during sleep in patients with JIA. Methods: We studied 10 patients with JIA and 10 age-, gender-, and Tanner stage-matched healthy controls. All participants underwent polysomnographic monitoring following an adaptation night in the sleep laboratory. HRV was analyzed using standard time and frequency domain measures over 5 min epochs across all sleep stages. Frequency components were classified into low- and high-frequency bands, and time domain measures included the standard deviation of the beat-to-beat intervals. Group differences in HRV parameters were assessed using nonparametric tests for independent samples, with a significance level set at p < 0.05. Results: JIA exhibited greater sleep disruption than controls, including reduced NREM sleep, longer total sleep time, and increased wake time after sleep onset. HRV analyses in both time and frequency domains revealed significant differences between groups across all stages of sleep. In JIA patients, the standard deviation of the normal-to-normal interval during slow wave sleep (SWS) and total power across all sleep stages (p < 0.05) was reduced. In JIA patients, the standard deviation of the normal-to-normal interval during slow wave sleep and total power across all sleep stages were significantly reduced (p < 0.05). VLF power was also significantly lower in JIA patients across all sleep stages (p = 0.002), with pronounced reductions during N2 and SWS (p = 0.03 and p = 0.02, respectively). A group effect was observed for total power across all stages, mirroring the VLF findings. Additionally, group differences were detected in LF/HF ratio analyses, although values during N2, SWS, and REM sleep did not differ significantly between groups. Notably, the number of affected joints showed a moderate positive correlation with the parasympathetic HRV parameter. Conclusions: Patients with JIA exhibited sleep disruption and alterations in cardiovascular autonomic functioning during sleep. Reduced HRV across all sleep stages in these patients suggests underlying autonomic nervous dysfunction. Addressing sleep disturbances in patients with chronic pain may serve as an effective strategy for managing their cardiovascular risk. Full article

This study investigated the effects of lemon verbena extract (LVE) on sleep regulation using both a pentobarbital-induced sleep model and an EEG-based sleep assessment model in mice. To elucidate its potential mechanisms, mice were randomly assigned to five groups: control, positive control (diazepam, 2 mg/kg b.w.), and three LVE-treated groups receiving 40, 80, or 160 mg/kg b.w. via oral administration. In the pentobarbital-induced sleep model, mice underwent a two-week oral administration of LVE, followed by intraperitoneal pentobarbital injections. The results demonstrated that LVE significantly shortened sleep latency and prolonged sleep duration compared to the control group. Notably, adenosine A1 receptor expression, both at the mRNA and protein levels, was markedly upregulated in the brains of LVE-treated mice. Furthermore, LVE’s administration led to a significant increase in the mRNA expression of gamma-aminobutyric acid type A (GABA_A) receptor subunits (α2 and β2) in brain tissue. In the electroencephalography (EEG)/electromyogram (EMG)-based sleep model, mice underwent surgical implantation of EEG and EMG electrodes, followed by one week of LVE administration. Quantitative EEG analysis revealed that LVE treatment reduced wakefulness while significantly enhancing REM and NREM sleep’s duration, indicating its potential sleep-promoting effects. These findings suggest that LVE may serve as a promising natural sleep aid, improving both the quality and duration of sleep through the modulation of adenosine and GABAergic signaling pathways. Full article