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Our research aims to assess the performance of a new generation of consumer activity trackers (Fitbit Charge 4 TM : FBC) to measure sleep variables and sleep stage classifications in patients with chronic insomnia, compared to polysomnography (PSG) and a widely used actigraph (Actiwatch Spectrum Pro: AWS). We recruited 37 participants, all diagnosed with chronic insomnia disorder, for one night of sleep monitoring in a sleep laboratory using PSG, AWS, and FBC. Epoch-by-epoch analysis along with Bland–Altman plots was used to evaluate FBC and AWS against PSG for sleep-wake detection and sleep variables: total sleep time (TST), sleep efficiency (SE), waking after sleep onset (WASO), and sleep onset latency (SOL). FBC sleep stage classification of light sleep (LS), deep sleep (DS), and rapid eye movement (REM) was also compared to that of PSG. When compared with PSG, FBC notably underestimated DS (-41.4, p < 0.0001) and SE (-4.9%, p = 0.0016), while remarkably overestimating LS (37.7, p = 0.0012). However, the TST, WASO, and SOL assessed by FBC presented no significant difference from that assessed by PSG. Compared with PSG, AWS and FBC showed great accuracy (86.9% vs. 86.5%) and sensitivity (detecting sleep; 92.6% vs. 89.9%), but comparatively poor specificity (detecting wake; 35.7% vs. 62.2%). Both devices showed better accuracy in assessing sleep than wakefulness, with the same sensitivity but statistically different specificity. FBC supplied equivalent parameters estimation as AWS in detecting sleep variables except for SE. This research shows that FBC cannot replace PSG thoroughly in the quantification of sleep variables and classification of sleep stages in Chinese patients with chronic insomnia; however, the user-friendly and low-cost wearables do show some comparable functions. Whether FBC can serve as a substitute for actigraphy and PSG in patients with chronic insomnia needs further investigation.

Sleep, specifically non-rapid eye movement (NREM) sleep, is thought to play a critical role in the consolidation of recent memories. Two main oscillatory activities observed during NREM, cortical slow oscillations (SO, 0.5-1.0 Hz) and thalamic spindles (12-15 Hz), have been shown to independently correlate with memory improvement. Yet, it is not known how these thalamocortical events interact, or the significance of this interaction, during the consolidation process. Here, we found that systemic administration of the GABAergic drug (zolpidem) increased both the phase-amplitude coupling between SO and spindles, and verbal memory improvement in humans. These results suggest that thalamic spindles that occur during transitions to the cortical SO Up state are optimal for memory consolidation. Our study predicts that the timely interactions between cortical and thalamic events during consolidation, contribute to memory improvement and is mediated by the level of inhibitory neurotransmission.

Cerebrospinal fluid (CSF) flow through the brain parenchyma is facilitated by the astrocytic water channel aquaporin 4 (AQP4). Homeostatically regulated electroencephalographic (EEG) slow waves are a hallmark of deep non-rapid eye movement (NREM) sleep and have been implicated in the regulation of parenchymal CSF flow and brain clearance. The human AQP4 gene harbors several single nucleotide polymorphisms (SNPs) associated with AQP4 expression, brain-water homeostasis, and neurodegenerative diseases. To date, their role in sleep-wake regulation is unknown. To investigate whether functional variants in AQP4 modulate human sleep, nocturnal EEG recordings and cognitive performance were investigated in 123 healthy participants genotyped for a common eight-SNP AQP4-haplotype. We show that this AQP4-haplotype is associated with distinct modulations of NREM slow wave energy, strongest in early sleep and mirrored by changes in sleepiness and reaction times during extended wakefulness. The study provides the first human evidence for a link between AQP4, deep NREM sleep, and cognitive consequences of prolonged wakefulness.

It is crucial to determine whether rapid eye movement (REM) sleep and slow-wave sleep (SWS) (or non-REM sleep), identified in most mammals and birds, also exist in lizards, as they share a common ancestor with these groups. Recently, a study in the bearded dragon (P. vitticeps) reported states analogous to REM and SWS alternating in a surprisingly regular 80-s period, suggesting a common origin of the two sleep states across amniotes. We first confirmed these results in the bearded dragon with deep brain recordings and electro-oculogram (EOG) recordings. Then, to confirm a common origin and more finely characterize sleep in lizards, we developed a multiparametric approach in the tegu lizard, a species never recorded to date. We recorded EOG, electromyogram (EMG), heart rate, and local field potentials (LFPs) and included data on arousal thresholds, sleep deprivation, and pharmacological treatments with fluoxetine, a serotonin reuptake blocker that suppresses REM sleep in mammals. As in the bearded dragon, we demonstrate the existence of two sleep states in tegu lizards. However, no clear periodicity is apparent. The first sleep state (S1 sleep) showed high-amplitude isolated sharp waves, and the second sleep state (S2 sleep) displayed 15-Hz oscillations, isolated ocular movements, and a decrease in heart rate variability and muscle tone compared to S1. Fluoxetine treatment induced a significant decrease in S2 quantities and in the number of sharp waves in S1. Because S2 sleep is characterized by the presence of ocular movements and is inhibited by a serotonin reuptake inhibitor, as is REM sleep in birds and mammals, it might be analogous to this state. However, S2 displays a type of oscillation never previously reported and does not display a desynchronized electroencephalogram (EEG) as is observed in the bearded dragons, mammals, and birds. This suggests that the phenotype of sleep states and possibly their role can differ even between closely related species. Finally, our results suggest a common origin of two sleep states in amniotes. Yet, they also highlight a diversity of sleep phenotypes across lizards, demonstrating that the evolution of sleep states is more complex than previously thought.

Sleep and wakefulness are greatly influenced by various physiological and psychological factors, but the neuronal elements responsible for organizing sleep-wake behavior in response to these factors are largely unknown. In this study, we report that a subset of neurons in the lateral hypothalamic area (LH) expressing the neuropeptide neurotensin (Nts) is critical for orchestrating sleep-wake responses to acute psychological and physiological challenges or stressors. We show that selective activation of NtsLH neurons with chemogenetic or optogenetic methods elicits rapid transitions from non-rapid eye movement (NREM) sleep to wakefulness and produces sustained arousal, higher locomotor activity (LMA), and hyperthermia, which are commonly observed after acute stress exposure. On the other hand, selective chemogenetic inhibition of NtsLH neurons attenuates the arousal, LMA, and body temperature (Tb) responses to a psychological stress (a novel environment) and augments the responses to a physiological stress (fasting).

The rostromedial tegmental nucleus (RMTg), also called the GABAergic tail of the ventral tegmental area, projects to the midbrain dopaminergic system, dorsal raphe nucleus, locus coeruleus, and other regions. Whether the RMTg is involved in sleep-wake regulation is unknown. In the present study, pharmacogenetic activation of rat RMTg neurons promoted non-rapid eye movement (NREM) sleep with increased slow-wave activity (SWA). Conversely, rats after neurotoxic lesions of 8 or 16 days showed decreased NREM sleep with reduced SWA at lights on. The reduced SWA persisted at least 25 days after lesions. Similarly, pharmacological and pharmacogenetic inactivation of rat RMTg neurons decreased NREM sleep. Electrophysiological experiments combined with optogenetics showed a direct inhibitory connection between the terminals of RMTg neurons and midbrain dopaminergic neurons. The bidirectional effects of the RMTg on the sleep-wake cycle were mimicked by the modulation of ventral tegmental area (VTA)/substantia nigra compacta (SNc) dopaminergic neuronal activity using a pharmacogenetic approach. Furthermore, during the 2-hour recovery period following 6-hour sleep deprivation, the amount of NREM sleep in both the lesion and control rats was significantly increased compared with baseline levels; however, only the control rats showed a significant increase in SWA compared with baseline levels. Collectively, our findings reveal an essential role of the RMTg in the promotion of NREM sleep and homeostatic regulation.

Sleep disorders related to Parkinson's disease (PD) have recently attracted increasing attention, but there are few clinical reports on the correlation of Parkinson's disease patients with rapid eye movement (REM) sleep behavior disorder (RBD). Therefore, this study conducted a cognitive function examination for Parkinson's disease patients and discussed the application effect of three algorithms in the screening of influencing factors and risk prediction effects. Three algorithms (logistic regression, machine learning-based regression trees and random forest) were used to establish a prediction model for PD-RBD patients, and the application effects of the three algorithms in the screening of influencing factors and the risk prediction of PD-RBD were discussed. The subjects included 169 patients with Parkinson's disease (Parkinson's disease with RBD [PD-RBD] = 69 subjects; Parkinson's disease without RBD [PD-nRBD] = 100 subjects). This study compared the predictive performance of RF, decision tree and logistic regression, selected a final model with the best model performance and proposed the importance of variables in the final model. After the analysis, the accuracy of RF (83.05%) was better than that of the other models (decision tree = 75.10%, logistic regression = 71.62%). PQSI, Scopa-AUT score, MoCA score, MMSE score, AGE, LEDD, PD-course, UPDRS total score, ESS score, NMSQ, disease type, RLSRS, HAMD, UPDRS III and PDOnsetage are the main variables for predicting RBD, along with increased weight. Among them, PQSI is the most important factor. The prediction model of Parkinson's disease RBD that was established in this study will help in screening out predictive factors and in providing a reference for the prognosis and preventive treatment of PD-RBD patients. The random forest model had good performance in the prediction and evaluation of PD-RBD influencing factors and was superior to decision tree and traditional logistic regression models in many aspects, which can provide a reference for the prognosis and preventive treatment of PD-RBD patients.

Motor sequence learning is known to rely on more than a single process. As the skill develops with practice, two different representations of the sequence are formed: a goal representation built under spatial allocentric coordinates and a movement representation mediated through egocentric motor coordinates. This study aimed to explore the influence of daytime sleep (nap) on consolidation of these two representations. Through the manipulation of an explicit finger sequence learning task and a transfer protocol, we show that both allocentric (spatial) and egocentric (motor) representations of the sequence can be isolated after initial training. Our results also demonstrate that nap favors the emergence of offline gains in performance for the allocentric, but not the egocentric representation, even after accounting for fatigue effects. Furthermore, sleep-dependent gains in performance observed for the allocentric representation are correlated with spindle density during non-rapid eye movement (NREM) sleep of the post-training nap. In contrast, performance on the egocentric representation is only maintained, but not improved, regardless of the sleep/wake condition. These results suggest that motor sequence memory acquisition and consolidation involve distinct mechanisms that rely on sleep (and specifically, spindle) or simple passage of time, depending respectively on whether the sequence is performed under allocentric or egocentric coordinates.

Patients with Parkinson’s disease (PD) often suffer from sleep disturbances, including excessive daytime sleepiness (EDS) and rapid eye movement sleep behavior disorder (RBD). These symptoms are also experienced by patients with narcolepsy, which is characterized by orexin neuronal loss. In PD, a decrease in orexin neurons is observed pathologically, but the association between sleep disturbance in PD and cerebrospinal fluid (CSF) orexin levels is still unclear. This study aimed to clarify the role of orexin as a biomarker in patients with PD. CSF samples were obtained from a previous cohort study conducted between 2015 and 2020. We cross-sectionally and longitudinally examined the association between CSF orexin levels, sleep, and clinical characteristics. We analyzed 78 CSF samples from 58 patients with PD and 21 samples from controls. CSF orexin levels in patients with PD (median = 272.0 [interquartile range = 221.7–334.5] pg/mL) were lower than those in controls (352.2 [296.2–399.5] pg/mL, p = 0.007). There were no significant differences in CSF orexin levels according to EDS, RBD, or the use of dopamine agonists. Moreover, no significant correlation was observed between CSF orexin levels and clinical characteristics by multiple linear regression analysis. Furthermore, the longitudinal changes in orexin levels were also not correlated with clinical characteristics. This study showed decreased CSF orexin levels in patients with PD, but these levels did not show any correlation with any clinical characteristics. Our results suggest the limited efficacy of CSF orexin levels as a biomarker for PD, and that sleep disturbances may also be affected by dysfunction of the nervous system other than orexin, or by dopaminergic treatments in PD. Understanding the reciprocal role of orexin among other neurotransmitters may provide a better treatment strategy for sleep disturbance in patients with PD.

Birds and mammals share specialized forms of sleep including slow wave sleep (SWS) and rapid eye movement sleep (REM), raising the question of why and how specialized sleep evolved. Extensive prior studies concluded that avian sleep lacked many features characteristic of mammalian sleep, and therefore that specialized sleep must have evolved independently in birds and mammals. This has been challenged by evidence of more complex sleep in multiple songbird species. To extend this analysis beyond songbirds, we examined a species of parrot, the sister taxon to songbirds. We implanted adult budgerigars ( Melopsittacus undulatus) with electroencephalogram (EEG) and electrooculogram (EOG) electrodes to evaluate sleep architecture, and video monitored birds during sleep. Sleep was scored with manual and automated techniques, including automated detection of slow waves and eye movements. This can help define a new standard for how to score sleep in birds. Budgerigars exhibited consolidated sleep, a pattern also observed in songbirds, and many mammalian species, including humans. We found that REM constituted 26.5% of total sleep, comparable to humans and an order of magnitude greater than previously reported. Although we observed no spindles, we found a clear state of intermediate sleep (IS) similar to non-REM (NREM) stage 2. Across the night, SWS decreased and REM increased, as observed in mammals and songbirds. Slow wave activity (SWA) fluctuated with a 29-min ultradian rhythm, indicating a tendency to move systematically through sleep states as observed in other species with consolidated sleep. These results are at variance with numerous older sleep studies, including for budgerigars. Here, we demonstrated that lighting conditions used in the prior budgerigar study—and commonly used in older bird studies—dramatically disrupted budgerigar sleep structure, explaining the prior results. Thus, it is likely that more complex sleep has been overlooked in a broad range of bird species. The similarities in sleep architecture observed in mammals, songbirds, and now budgerigars, alongside recent work in reptiles and basal birds, provide support for the hypothesis that a common amniote ancestor possessed the precursors that gave rise to REM and SWS at one or more loci in the parallel evolution of sleep in higher vertebrates. We discuss this hypothesis in terms of the common plan of forebrain organization shared by reptiles, birds, and mammals.