Showing papers on "Non-rapid eye movement sleep published in 2020"

An electrophysiological marker of arousal level in humans.

Abstract: Deep non-rapid eye movement sleep (NREM) and general anesthesia with propofol are prominent states of reduced arousal linked to the occurrence of synchronized oscillations in the electroencephalogram (EEG). Although rapid eye movement (REM) sleep is also associated with diminished arousal levels, it is characterized by a desynchronized, 'wake-like' EEG. This observation implies that reduced arousal states are not necessarily only defined by synchronous oscillatory activity. Using intracranial and surface EEG recordings in four independent data sets, we demonstrate that the 1/f spectral slope of the electrophysiological power spectrum, which reflects the non-oscillatory, scale-free component of neural activity, delineates wakefulness from propofol anesthesia, NREM and REM sleep. Critically, the spectral slope discriminates wakefulness from REM sleep solely based on the neurophysiological brain state. Taken together, our findings describe a common electrophysiological marker that tracks states of reduced arousal, including different sleep stages as well as anesthesia in humans.

Sleep and synaptic down-selection

Abstract: Sleep is universal, tightly regulated, and many cognitive functions are impaired if we do not sleep. But why? Why do our brains need to disconnect from the environment for hours every day? We discuss here the synaptic homeostasis hypothesis (SHY), which proposes that sleep is the price the brain pays for plasticity, to consolidate what we already learned, and be ready to learn new things the next day. In brief, new experiments show that the net strength of synapses increases with wake and decreases with sleep. As we discuss, these findings can explain why sleep is necessary for the well-being of neural cells and brain circuits, and how the regulation of synaptic strength may be a universal, essential function of sleep.

Promoting memory consolidation during sleep: A meta-analysis of targeted memory reactivation

Abstract: Targeted memory reactivation (TMR) is a methodology employed to manipulate memory processing during sleep. TMR studies have great potential to advance understanding of sleep-based memory consolidation and corresponding neural mechanisms. Research making use of TMR has developed rapidly, with over 70 articles published in the last decade, yet no quantitative analysis exists to evaluate the overall effects. Here we present the first meta-analysis of sleep TMR, compiled from 91 experiments with 212 effect sizes (N = 2,004). Based on multilevel modeling, overall sleep TMR was highly effective (Hedges' g = 0.29, 95% CI [0.21, 0.38]), with a significant effect for two stages of non-rapid-eye-movement (NREM) sleep (Stage NREM 2: Hedges' g = 0.32, 95% CI [0.04, 0.60]; and slow-wave sleep: Hedges' g = 0.27, 95% CI [0.20, 0.35]). In contrast, TMR was not effective during REM sleep nor during wakefulness in the present analyses. Several analysis strategies were used to address the potential relevance of publication bias. Additional analyses showed that TMR improved memory across multiple domains, including declarative memory and skill acquisition. Given that TMR can reinforce many types of memory, it could be useful for various educational and clinical applications. Overall, the present meta-analysis provides substantial support for the notion that TMR can influence memory storage during NREM sleep, and that this method can be useful for understanding neurocognitive mechanisms of memory consolidation. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Sleep deprivation and stress: a reciprocal relationship.

Abstract: Sleep is highly conserved across evolution, suggesting vital biological functions that are yet to be fully understood. Animals and humans experiencing partial sleep restriction usually exhibit detrimental physiological responses, while total and prolonged sleep loss could lead to death. The perturbation of sleep homeostasis is usually accompanied by an increase in hypothalamic-pituitary-adrenal (HPA) axis activity, leading to a rise in circulating levels of stress hormones (e.g. cortisol in humans, corticosterone in rodents). Such hormones follow a circadian release pattern under undisturbed conditions and participate in the regulation of sleep. The investigation of the consequences of sleep deprivation, from molecular changes to behavioural alterations, has been used to study the fundamental functions of sleep. However, the reciprocal relationship between sleep and the activity of the HPA axis is problematic when investigating sleep using traditional sleep-deprivation protocols that can induce stress per se. This is especially true in studies using rodents in which sleep deprivation is achieved by exogenous, and potentially stressful, sensory-motor stimulations that can undoubtedly confuse their conclusions. While more research is needed to explore the mechanisms underlying sleep loss and health, avoiding stress as a confounding factor in sleep-deprivation studies is therefore crucial. This review examines the evidence of the intricate links between sleep and stress in the context of experimental sleep deprivation, and proposes a more sophisticated research framework for sleep-deprivation procedures that could benefit from recent progress in biotechnological tools for precise neuromodulation, such as chemogenetics and optogenetics, as well as improved automated real-time sleep-scoring algorithms.

Overanxious and underslept.

Abstract: Are you feeling anxious? Did you sleep poorly last night? Sleep disruption is a recognized feature of all anxiety disorders. Here, we investigate the basic brain mechanisms underlying the anxiogenic impact of sleep loss. Additionally, we explore whether subtle, societally common reductions in sleep trigger elevated next-day anxiety. Finally, we examine what it is about sleep, physiologically, that provides such an overnight anxiety-reduction benefit. We demonstrate that the anxiogenic impact of sleep loss is linked to impaired medial prefrontal cortex activity and associated connectivity with extended limbic regions. In contrast, non-rapid eye movement (NREM) slow-wave oscillations offer an ameliorating, anxiolytic benefit on these brain networks following sleep. Of societal relevance, we establish that even modest night-to-night reductions in sleep across the population predict consequential day-to-day increases in anxiety. These findings help contribute to an emerging framework explaining the intimate link between sleep and anxiety and further highlight the prospect of non-rapid eye movement sleep as a therapeutic target for meaningfully reducing anxiety. All anxiety disorders are characterized by sleep disruption. Ben Simon et al. develop a neural framework of sleep-loss-induced anxiety, one that emphasizes NREM sleep as a therapeutic target for anxiety amelioration.

Sex differences in obstructive sleep apnea phenotypes, the multi-ethnic study of atherosclerosis

Abstract: STUDY OBJECTIVES The bases for sex disparities in obstructive sleep apnea (OSA), is poorly understood. We quantified the influences of event definitions, sleep-state, and body position on apnea-hypopnea indices (AHIs) in men and women, and evaluated sex differences in pathophysiological endotypes. METHODS Polysomnography (PSG) data were analyzed from 2057 participants from the multi-ethnic study of atherosclerosis. Alternative AHIs were compared using various desaturation and arousal criteria. Endotypes (loop gain, airway collapsibility, arousal threshold) were derived using breath-by-breath analysis of PSG signals. Regression models estimated the extent to which endotypes explained sex differences in AHI. RESULTS The sample (mean 68.5 ± 9.2 years) included 54% women. OSA (AHI4P ≥15/h, defined by events with ≥4% desaturations) was found in 41.1% men and 21.8% women. Compared to AHI4P, male/female AHI ratios decreased by 5%-10% when using 3%-desaturation and/or arousal criteria; p < 0.05. REM-OSA (REM-AHI ≥15/h) was similar in men and women regardless of event desaturation criteria. REM-AHI4P ≥15/h was observed in 57% of men and women each. In NREM, AHI4P in men was 2.49 (CI95: 2.25, 2.76) of that in women. Women demonstrated lower loop gain, less airway collapsibility, and lower arousal threshold in NREM (ps < 0.0005). Endotypes explained 30% of the relative sex differences in NREM-AHI4P. CONCLUSIONS There are significant sex differences in NREM-AHI levels and in physiological endotypes. Physiological endotypes explained a significant portion of the relative sex differences in NREM-AHI. Definitions that use 4%-desaturation criteria under-estimate AHI in women. Combining NREM and REM events obscures OSA prevalence in REM in women.

Deep learning enables sleep staging from photoplethysmogram for patients with suspected sleep apnea

Abstract: Accurate identification of sleep stages is essential in the diagnosis of sleep disorders (e.g. obstructive sleep apnea, OSA) but relies on labor-intensive EEG-based manual scoring. Furthermore, long-term assessment of sleep relies on actigraphy differentiating only between wake and sleep periods without identifying specific sleep stages and has low reliability in identifying wake periods after sleep onset. To address these issues, we aimed to automatically identify the sleep stages from the photoplethysmogram (PPG) signal obtained with a simple finger pulse oximeter. PPG signals from the diagnostic polysomnographies of patients suspected of OSA (n=894) were utilized to develop a combined convolutional and recurrent neural network. The deep learning model was trained individually for 3-stage (wake/NREM/REM), 4-stage (wake/N1+N2/N3/REM), and 5-stage (wake/N1/N2/N3/REM) classification of sleep. The 3-stage model achieved an epoch-by-epoch accuracy of 80.1% with Cohen's kappa (κ) of 0.65. The 4-stage and 5-stage models achieved 68.5% (κ=0.54), and 64.1% (κ=0.51) accuracies, respectively. With the 5-stage model, the total sleep time was underestimated with mean (standard deviation) error of 7.5 (55.2) min. The PPG-based deep learning model enabled accurate estimation of sleep time and differentiation between sleep stages with a moderate agreement to manual EEG-based scoring. As PPG is already included in ambulatory polygraphic recordings, applying the PPG-based sleep staging could improve their diagnostic value by enabling simple, low-cost, and reliable monitoring of sleep and help assess otherwise overlooked conditions such as REM-related OSA.

Sleep spindles mediate hippocampal-neocortical coupling during long-duration ripples.

Abstract: Sleep is pivotal for memory consolidation. According to two-stage accounts, memory traces are gradually translocated from hippocampus to neocortex during non-rapid-eye-movement (NREM) sleep. Mechanistically, this information transfer is thought to rely on interactions between thalamocortical spindles and hippocampal ripples. To test this hypothesis, we analyzed intracranial and scalp Electroencephalography sleep recordings from pre-surgical epilepsy patients. We first observed a concurrent spindle power increase in hippocampus (HIPP) and neocortex (NC) time-locked to individual hippocampal ripple events. Coherence analysis confirmed elevated levels of hippocampal-neocortical spindle coupling around ripples, with directionality analyses indicating an influence from NC to HIPP. Importantly, these hippocampal-neocortical dynamics were particularly pronounced during long-duration compared to short-duration ripples. Together, our findings reveal a potential mechanism underlying active consolidation, comprising a neocortical-hippocampal-neocortical reactivation loop initiated by the neocortex. This hippocampal-cortical dialogue is mediated by sleep spindles and is enhanced during long-duration hippocampal ripples.

Rapid fast-delta decay following prolonged wakefulness marks a phase of wake-inertia in NREM sleep.

Abstract: Sleep-wake driven changes in non-rapid-eye-movement sleep (NREM) sleep (NREMS) EEG delta (δ-)power are widely used as proxy for a sleep homeostatic process Here, we noted frequency increases in δ-waves in sleep-deprived mice, prompting us to re-evaluate how slow-wave characteristics relate to prior sleep-wake history We identified two classes of δ-waves; one responding to sleep deprivation with high initial power and fast, discontinuous decay during recovery sleep (δ2) and another unrelated to time-spent-awake with slow, linear decay (δ1) Reanalysis of previously published datasets demonstrates that δ-band heterogeneity after sleep deprivation is also present in human subjects Similar to sleep deprivation, silencing of centromedial thalamus neurons boosted subsequent δ2-waves, specifically δ2-dynamics paralleled that of temperature, muscle tone, heart rate, and neuronal ON-/OFF-state lengths, all reverting to characteristic NREMS levels within the first recovery hour Thus, prolonged waking seems to necessitate a physiological recalibration before typical NREMS can be reinstated

Neurovascular coupling and bilateral connectivity during NREM and REM sleep

Abstract: To understand how arousal state impacts cerebral hemodynamics and neurovascular coupling, we monitored neural activity, behavior, and hemodynamic signals in un-anesthetized, head-fixed mice. Mice frequently fell asleep during imaging, and these sleep events were interspersed with periods of wake. During both NREM and REM sleep, mice showed large increases in cerebral blood volume ([HbT]) and arteriole diameter relative to the awake state, two to five times larger than those evoked by sensory stimulation. During NREM, the amplitude of bilateral low-frequency oscillations in [HbT] increased markedly, and coherency between neural activity and hemodynamic signals was higher than the awake resting and REM states. Bilateral correlations in neural activity and [HbT] were highest during NREM, and lowest in the awake state. Hemodynamic signals in the cortex are strongly modulated by arousal state, and changes during sleep are substantially larger than sensory-evoked responses.

Complementary contributions of non-REM and REM sleep to visual learning.

Abstract: Sleep is beneficial for learning. However, it remains unclear whether learning is facilitated by non-rapid eye movement (NREM) sleep or by REM sleep, whether it results from plasticity increases or stabilization, and whether facilitation results from learning-specific processing. Here, we trained volunteers on a visual task and measured the excitatory and inhibitory (E/I) balance in early visual areas during subsequent sleep as an index of plasticity. The E/I balance increased during NREM sleep irrespective of whether pre-sleep learning occurred, but it was associated with post-sleep performance gains relative to pre-sleep performance. In contrast, the E/I balance decreased during REM sleep but only after pre-sleep training, and the decrease was associated with stabilization of pre-sleep learning. These findings indicate that NREM sleep promotes plasticity, leading to performance gains independent of learning, while REM sleep decreases plasticity to stabilize learning in a learning-specific manner.

The Brain-Derived Neurotrophic Factor: Missing Link Between Sleep Deprivation, Insomnia, and Depression.

Abstract: The brain-derived neurotrophic factor (BDNF) mediates the plasticity-related changes that associate with memory processing during sleep. Sleep deprivation and chronic stress are associated with propensity to depression, anxiety, and insomnia. We propose a model by which explain alterations in the CNS and serum expression of BDNF associated with chronic sleep deprivation, depression, and insomnia. Mild sleep deprivation activates the cerebral cortex and brainstem to generate the physiologic drive for non-rapid eye movement (NREM) and rapid eye movement (REM) sleep drive respectively, associated with BDNF upregulation in these regions. This physiological response loses effectiveness with longer episodes or during chronic of total or selective REM sleep loss, which are associated with impaired hippocampal BDNF expression, impaired memory and cognition. Chronic sleep deprivation and insomnia can act as an external stressors and result in depression, characterized by hippocampal BDNF downregulation along with disrupted frontal cortical BDNF expression, as well as reduced levels and impaired diurnal alterations in serum BDNF expression. Acute REM sleep deprivation breaks the cycle by restoration of hippocampal, and possibly restoration of cortical and serum expression of BDNF. The BDNF Val66Met polymorphism alters susceptibility to depression, anxiety, and insomnia by altering availability and expression of BDNF in brain and blood. The proposed model is testable and implies that low levels and low variability in serum BDNF are associated with poor response to anti-depressive medications, electroconvulsive therapy, and REM sleep deprivation, in patients with depression. Our mode is also backed up by the existing clinical evidence but is yet to be investigated.

Slow Wave Sleep Is a Promising Intervention Target for Alzheimer's Disease

Abstract: Alzheimer's disease (AD) is the major cause of dementia, characterized by the presence of amyloid-beta plaques and neurofibrillary tau tangles. Plaques and tangles are associated with sleep-wake cycle disruptions, including the disruptions in non-rapid eye movement (NREM) slow wave sleep (SWS). Alzheimer's patients spend less time in NREM sleep and exhibit decreased slow wave activity (SWA). Consistent with the critical role of SWS in memory consolidation, reduced SWA is associated with impaired memory consolidation in AD patients. The aberrant SWA can be modeled in transgenic mouse models of amyloidosis and tauopathy. Animal models exhibited slow wave impairments early in the disease progression, prior to the deposition of amyloid-beta plaques, however, in the presence of abundant oligomeric amyloid-beta. Optogenetic rescue of SWA successfully halted the amyloid accumulation and restored intraneuronal calcium levels in mice. On the other hand, optogenetic acceleration of slow wave frequency exacerbated amyloid deposition and disrupted neuronal calcium homeostasis. In this review, we summarize the evidence and the mechanisms underlying the existence of a positive feedback loop between amyloid/tau pathology and SWA disruptions that lead to further accumulations of amyloid and tau in AD. Moreover, since SWA disruptions occur prior to the plaque deposition, SWA disruptions may provide an early biomarker for AD. Finally, we propose that therapeutic targeting of SWA in AD might lead to an effective treatment for Alzheimer's patients.

A mechanism for learning with sleep spindles

Abstract: Spindles are ubiquitous oscillations during non-rapid eye movement (NREM) sleep. A growing body of evidence points to a possible link with learning and memory, and the underlying mechanisms are now starting to be unveiled. Specifically, spindles are associated with increased dendritic activity and high intracellular calcium levels, a situation favourable to plasticity, as well as with control of spiking output by feed-forward inhibition. During spindles, thalamocortical networks become unresponsive to inputs, thus potentially preventing interference between memory-related internal information processing and extrinsic signals. At the system level, spindles are co-modulated with other major NREM oscillations, including hippocampal sharp wave-ripples (SWRs) and neocortical slow waves, both previously shown to be associated with learning and memory. The sequential occurrence of reactivation at the time of SWRs followed by neuronal plasticity-promoting spindles is a possible mechanism to explain NREM sleep-dependent consolidation of memories.

Unraveling why we sleep: Quantitative analysis reveals abrupt transition from neural reorganization to repair in early development

Abstract: Sleep serves disparate functions, most notably neural repair, metabolite clearance and circuit reorganization. Yet the relative importance remains hotly debated. Here, we create a novel mechanistic framework for understanding and predicting how sleep changes during ontogeny and across phylogeny. We use this theory to quantitatively distinguish between sleep used for neural reorganization versus repair. Our findings reveal an abrupt transition, between 2 and 3 years of age in humans. Specifically, our results show that differences in sleep across phylogeny and during late ontogeny (after 2 or 3 years in humans) are primarily due to sleep functioning for repair or clearance, while changes in sleep during early ontogeny (before 2 or 3 years) primarily support neural reorganization and learning. Moreover, our analysis shows that neuroplastic reorganization occurs primarily in REM sleep but not in NREM. This developmental transition suggests a complex interplay between developmental and evolutionary constraints on sleep.

Electroencephalographic changes associated with subjective under- and overestimation of sleep duration.

Abstract: Feeling awake although sleep recordings indicate clear-cut sleep sometimes occurs in good sleepers and to an extreme degree in patients with so-called paradoxical insomnia. It is unknown what underlies sleep misperception, as standard polysomnographic (PSG) parameters are often normal in these cases. Here we asked whether regional changes in brain activity could account for the mismatch between objective and subjective total sleep times (TST). To set cutoffs and define the norm, we first evaluated sleep perception in a population-based sample, consisting of 2,092 individuals who underwent a full PSG at home and estimated TST the next day. We then compared participants with a low mismatch (normoestimators, n = 1,147, ±0.5 SD of mean) with those who severely underestimated (n = 52, 97.5th percentile). Compared with normoestimators, underestimators displayed higher electroencephalographic (EEG) activation (beta/delta power ratio) in both rapid eye movement (REM) and non-rapid eye movement (NREM) sleep, while overestimators showed lower EEG activation (significant in REM sleep). To spatially map these changes, we performed a second experiment, in which 24 healthy subjects and 10 insomnia patients underwent high-density sleep EEG recordings. Similarly to underestimators, patients displayed increased EEG activation during NREM sleep, which we localized to central-posterior brain areas. Our results indicate that a relative shift from low- to high-frequency spectral power in central-posterior brain regions, not readily apparent in conventional PSG parameters, is associated with underestimation of sleep duration. This challenges the concept of sleep misperception, and suggests that instead of misperceiving sleep, insomnia patients may correctly perceive subtle shifts toward wake-like brain activity.

Haplotype of the astrocytic water channel AQP4 is associated with slow wave energy regulation in human NREM sleep.

Abstract: 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.

Sleep disorders in anti-NMDAR encephalitis.

Abstract: Objective To describe the sleep disorders in anti–NMDA receptor encephalitis (anti-NMDARe) Methods Patients recovering from anti-NMDARe were invited to participate in a prospective observational single-center study including comprehensive clinical, video-polysomnography (V-PSG) sleep assessment, and neuropsychological evaluation Age- and sex-matched healthy participants served as controls Results Eighteen patients (89% female, median age 26 years, interquartile range [IQR] 21–29 years) and 21 controls (81% female, median age 23 years, IQR 18–26 years) were included In the acute stage, 16 (89%) patients reported insomnia and 2 hypersomnia; nightmares occurred in 7 After the acute stage, 14 (78%) had hypersomnia At study admission (median 183 days after disease onset, IQR 110–242 days), 8 patients still had hypersomnia, 1 had insomnia, and 9 had normal sleep duration Patients had more daytime sleepiness than controls (higher Barcelona Sleepiness Index, p = 002, and Epworth Sleepiness Score, p = 004) On V-PSG, sleep efficiency was similar in both groups, but patients more frequently had multiple and longer confusional arousals in non-REM (NREM) sleep (videos provided) In addition, 13 (72%) patients had cognitive deficits; 12 (67%) had psychological, social, or occupational disability; and 33% had depression or mania Compared with controls, patients had a higher body mass index (median 235 [IQR 223–302] vs 205 [191–211] kg/m2; p = 0007) Between disease onset and last follow-up, 14 (78%) patients developed hyperphagia, and 6 (33%) developed hypersexuality (2 requiring hospitalization), all associated with sleep dysfunction Conclusions Sleep disturbances are frequent in anti-NMDARe They show a temporal pattern (predominantly insomnia at onset; hypersomnia during recovery), are associated with behavioral and cognitive changes, and can occur with confusional arousals during NREM sleep

Automatic Sleep Stage Classification With Single Channel EEG Signal Based on Two-Layer Stacked Ensemble Model

Abstract: Sleep stage classification, including wakefulness (W), rapid eye movement (REM), and non- rapid eye movement (NREM) which includes three sleep stages that describe the depth of sleep, is one of the most critical steps in effective diagnosis and treatment of sleep-related disorders. Clinically, sleep staging is performed by domain experts through visual inspection of polysomnography (PSG) recordings, which is time-consuming, labor-intensive and often subjective in nature. Therefore, this study develops an automatic sleep staging system, which uses single channel electroencephalogram (EEG) signal, for convenience of wearing and less interference in the sleep, to do automatic identification of various sleep stages. To achieve the automatic sleep staging system, this study proposes a two-layer stacked ensemble model, which combines the advantages of random forest (RF) and LightGBM (LGB), where RF focuses on reducing the variance of the proposed model while LGB focuses on reducing the bias of the proposed model. Particularly, the proposed model introduces a class balance strategy to improve the N1 stage recognition rate. In order to evaluate the performance of the proposed model, experiments are performed on two datasets, including Sleep-EDF database (SEDFDB) and Sleep-EDF Expanded database (SEDFEDB). In the SEDFDB, the overall accuracy (ACC), weight F1-score (WF1), Cohen’s Kappa coefficient (Kappa), sensitivity of N1 (SEN-N1) obtained by proposed model are 91.2%, 0.916, 0.864 and 72.52% respectively using subject-non-independent test (SNT). In parallel, the ACC, WF1, Kappa, SEN-N1 obtained by proposed model are 82.4%, 0.751, 0.719 and 27.15% respectively using subject-independent test (SIT). Experimental results show that the performance of the proposed model are competitive with the state-of-the-art methods and results, and the recognition rate of N1 stage is significantly improved. Moreover, in the SEDFEDB, the experimental results indicate the robustness and generality of the proposed model.

Local Sleep and Alzheimer's Disease Pathophysiology.

Abstract: Even prior to the onset of the prodromal stages of Alzheimer's disease (AD), a constellation of sleep disturbances are apparent. A series of epidemiological studies indicate that multiple forms of these sleep disturbances are associated with increased risk for developing mild cognitive impairment (MCI) and AD, even triggering disease onset at an earlier age. Through the combination of causal manipulation studies in humans and rodents, as well as targeted examination of sleep disturbance with respect to AD biomarkers, mechanisms linking sleep disturbance to AD are beginning to emerge. In this review, we explore recent evidence linking local deficits in brain oscillatory function during sleep with local AD pathological burden and circuit-level dysfunction and degeneration. In short, three deficits in the local expression of sleep oscillations have been identified in relation to AD pathophysiology: (1) frequency-specific frontal deficits in slow wave expression during non-rapid eye movement (NREM) sleep, (2) deficits in parietal sleep spindle expression, and (3) deficits in the quality of electroencephalographic (EEG) desynchrony characteristic of REM sleep. These deficits are noteworthy since they differ from that seen in normal aging, indicating the potential presence of an abnormal aging process. How each of these are associated with β-amyloid (Aβ) and tau pathology, as well as neurodegeneration of circuits sensitive to AD pathophysiology, are examined in the present review, with a focus on the role of dysfunction within fronto-hippocampal and subcortical sleep-wake circuits. It is hypothesized that each of these local sleep deficits arise from distinct network-specific dysfunctions driven by regionally-specific accumulation of AD pathologies, as well as their associated neurodegeneration. Overall, the evolution of these local sleep deficits offer unique windows into the circuit-specific progression of distinct AD pathophysiological processes prior to AD onset, as well as their impact on brain function. This includes the potential erosion of sleep-dependent memory mechanisms, which may contribute to memory decline in AD. This review closes with a discussion of the remaining critical knowledge gaps and implications of this work for future mechanistic studies and studies implementing sleep-based treatment interventions.

Sex differences within sleep in gonadally intact rats.

Abstract: Sleep impacts diverse physiological and neural processes and is itself affected by the menstrual cycle; however, few studies have examined the effects of the estrous cycle on sleep in rodents. Studies of disease mechanisms in females therefore lack critical information regarding estrous cycle influences on relevant sleep characteristics. We recorded electroencephalographic (EEG) activity from multiple brain regions to assess sleep states as well as sleep traits such as spectral power and interregional spectral coherence in freely cycling females across the estrous cycle and compared with males. Our findings show that the high hormone phase of proestrus decreases the amount of nonrapid eye movement (NREM) sleep and rapid eye movement (REM) sleep and increases the amount of time spent awake compared with other estrous phases and to males. This spontaneous sleep deprivation of proestrus was followed by a sleep rebound in estrus which increased NREM and REM sleep. In proestrus, spectral power increased in the delta (0.5-4 Hz) and the gamma (30-60 Hz) ranges during NREM sleep, and increased in the theta range (5-9 Hz) during REM sleep during both proestrus and estrus. Slow-wave activity (SWA) and cortical sleep spindle density also increased in NREM sleep during proestrus. Finally, interregional NREM and REM spectral coherence increased during proestrus. This work demonstrates that the estrous cycle affects more facets of sleep than previously thought and reveals both sex differences in features of the sleep-wake cycle related to estrous phase that likely impact the myriad physiological processes influenced by sleep.