Sleep Mechanisms Research Articles

Impact of Web-Based Cognitive Behavioral Therapy for Insomnia on Stress, Health, Mood, Cognitive, Inflammatory, and Neurodegenerative Outcomes in Rural Dementia Caregivers: Protocol for the NiteCAPP CARES and NiteCAPP SHARES Randomized Controlled Trial.

BackgroundChronic insomnia affects up to 63% of family dementia caregivers. Research suggests that chronic insomnia prompts changes in central stress processing that have downstream negative effects on health and mood, as well as on cognitive, inflammatory, and neurodegenerative functioning. We hypothesize that cognitive behavioral therapy for insomnia (CBT-I) will reverse those downstream effects by improving insomnia and restoring healthy central stress processing. Rural caregivers are particularly vulnerable, but they have limited access to CBT-I; therefore, we developed an accessible digital version using community input (NiteCAPP CARES).ObjectiveThis trial will evaluate the acceptability, feasibility, and short-term and long-term effects of NiteCAPP CARES on the sleep and stress mechanisms underlying poor caregiver health and functioning.MethodsDyads (n=100) consisting of caregivers with chronic insomnia and their coresiding persons with dementia will be recruited from Columbia and surrounding areas in Missouri, United States. Participant dyads will be randomized to 4 weeks (plus 4 bimonthly booster sessions) of NiteCAPP CARES or a web-based sleep hygiene control (NiteCAPP SHARES). Participants will be assessed at baseline, after treatment, and 6- and 12-month follow-ups. The following assessments will be completed by caregivers: 1 week of actigraphy and daily diaries measuring sleep, Insomnia Severity Index, arousal (heart rate variability), inflammation (blood-derived biomarkers: interleukin-6 and C-reactive protein), neurodegeneration (blood-derived biomarkers: plasma amyloid beta [Aβ40 and Aβ42], total tau, and phosphorylated tau [p-tau181 and p-tau217]), cognition (Joggle battery, NIH Toolbox for Assessment of Neurological and Behavioral Function, and Cognitive Failures Questionnaire), stress and burden, health, and mood (depression and anxiety). Persons with dementia will complete 1 week of actigraphy at each time point.ResultsRecruitment procedures started in February 2022. All data are expected to be collected by 2026. Full trial results are planned to be published by 2027. Secondary analyses of baseline data will be subsequently published.ConclusionsThis randomized controlled trial tests NiteCAPP CARES, a web-based CBT-I for rural caregivers. The knowledge obtained will address not only what outcomes improve but also how and why they improve and for how long, which will help us to modify NiteCAPP CARES to optimize treatment potency and support future pragmatic testing and dissemination.Trial RegistrationClinicalTrials.gov NCT04896775; https://clinicaltrials.gov/ct2/show/NCT04896775International Registered Report Identifier (IRRID)PRR1-10.2196/37874

Determination of optimized sleep interval for 10 gigabit-passive optical network using learning intelligence

<span>The overall aim of this project is to investigate the application of a machine learning method in finding the optimized length of asleep time interval (T<sub>AS</sub>) in a cyclic sleep mechanism (CSM). Since past decade, the implementations of CSM in the optical network unit (ONU) to reduce the energy consumption in 10 gigabit-passive optical network (XG-PON) were extensively researched. However, the newest era sees the emergence of various network traffic with stringent demands that require further improvements on the T<sub>AS</sub> selection. Since conventional methods utilize complex algorithm, this paper presents the employment of an artificial neural network (ANN) to facilitate ONU to determine the optimized T<sub>AS</sub> values using learning from past experiences. Prior to simulation, theoretical analysis was done using the M/G/1 queueing system. The ANN was than trained and tested for the XG-PON network for optimal T<sub>AS</sub> decisions. Results have shown that towards higher network load, a decreasing T<sub>AS</sub> trend was observed from both methods. A wider T<sub>AS</sub> range was recorded from the ANN network as compared to the theoretical values. Therefore, these findings will benefit the network operators to have a flexibility measure in determining the optimal T<sub>AS</sub> values at current network conditions.</span>

EEG Activation Does Not Differ in Simple and Complex Episodes of Disorders of Arousal: A Spectral Analysis Study.

PurposeDisorders of arousal (DoA) are characterized by incomplete awakening from NREM sleep, with the admixture of both deep sleep and wake EEG activity. Previous observations suggested that changes in EEG activity could be detected in the seconds preceding DoA episodes. The aims of this work were to characterize the topography of EEG spectral changes prior to DoA episodes and to investigate whether or not behavioral complexity could be predicted by changes in EEG immediately preceding behavioral onsets.Patients and MethodsWe collected 103 consecutive video-polysomnographic recordings of 53 DoA adult patients and classified all episodes as simple, rising and complex arousal movements. For each episode, a 5-second window preceding its motor onset (“pre-event”) and a 60-second window from 2 to 3 minutes before the episodes (“baseline”) were compared. Subsequently, a between-group comparison was performed for the pre-event of simpler versus the more complex episodes.ResultsSpectral analysis over 325 DoA episodes showed an absolute significant increase prior to DoA episodes in all frequency bands excluding sigma, which displayed the opposite effect. In normalized maps, the increase was relatively higher over the central/anterior areas for both slow and fast frequency bands. No significant differences emerged from the comparison between simpler and more complex episodes.ConclusionTaken together, these results show that deep sleep and wake-like EEG rhythms coexist over overlapping areas before DoA episodes, suggesting an alteration of local sleep mechanisms. Episodes of different complexity are preceded by a similar EEG activation, implying that they possibly share a similar pathophysiology.

0304 Characterizing age and sex-related changes in sleep EEG K-complex morphology in 3,909 individuals

Abstract Introduction K-complexes are hallmarks of sleep stage N2 and are thought to be associated with two distinct roles that serve as either or both, a sleep protective mechanism or a cortical arousal response. K-complexes and their morphological features (number, delta surrounding K complexes, etc.) have been implicated in sustained attention as well as in Alzheimer’s disease wherein a decline in the number of K-complexes appeared to discriminate diseased individuals from healthy controls. Yet, age and sex-related changes in K-complex morphology are not well-known. Methods We analyzed data from the Sleep Heart Health Study (SHHS) to understand age- and sex-related changes in K-complex morphology. The SHHS is a cohort study comprised of 5,804 men and women aged 40 and older aimed at investigating the cardiovascular consequences of sleep-disordered breathing. K-complex (on C3/A2) features were quantified using previously published and validated open-source algorithm (DETOKS; Parekh et. al. J. Neurosci Meth. 2015). Three features of K-complexes were studied: number of K-complexes (density), delta (∆SWAK) and alpha (∆alphaK) surrounding K-complexes. Results Of the 5,804 studies available, 3,909 that had at least 6h of usable EEG were analyzed (mean = 62±11 yrs., range [40-90 yrs.], 53%female). With aging, K-complex density and (rho=-0.1, p<0.0001), ∆SWAK (rho=-0.2, p<0.0001) were inversely associated with age, while ∆alphaK (rho=0.1, p<0.01) was significantly positively associated with age. The inverse association of K-complex density with age was greater in men compared to women (rhomen=-0.3, p<0.0001, rhowomen=-0.1, p<0.01). Women had greater K-complex density compared to men (1.8[1.3-2.4] vs. 1.3[0.9-1.8], median[IQR]; std. mean diff =0.4). The changes in K-complex morphology with age remained significant after controlling for OSA severity. Conclusion Age is associated with decline in K-complex morphology such that K-complex density and delta activity surrounding K-complexes declines whereas alpha activity surrounding K-complexes increases. An age-related decline in delta activity surrounding K-complexes and an increase in alpha activity surrounding K-complexes is consistent with the potential role for these features in either sleep-state maintenance or arousal responsiveness. Whether the decline in K-complex morphology seen here with aging, and its interaction with sex-related differences, is accelerated in neurodegenerative disorders such as AD remains to be tested. Support (If Any) Support: NIH K25HL151912, AASMFoundation BS-233-20

0009 Interindividual variation and extended wakefulness in sleepiness after acute and chronic sleep deprivation

Abstract Introduction Sleepiness is a behavioural consequence of sleep pressure and is associated with negative outcomes with interindividual variation, possibly related to central sleep mechanisms. However, there is a lack of evidence linking progressive sleep need and sleepiness with factors of individual variability, which could be tested by total acute and chronic sleep deprivation. Thus, the objective of the study was to investigate the development of sleepiness in sleep deprived mice. Methods Male C57BL/6J mice were distributed in sleep deprivation, sleep rebound and control groups. Animals underwent acute sleep deprivation for 3, 6, 9 or 12 hours or chronic sleep deprivation for 6 hours for 5 consecutive days. Sleep rebound groups had a sleep opportunity for 1, 2, 3, or 4 hours after acute sleep deprivation or 24 hours after chronic sleep deprivation. During the protocols, sleep attempts were counted to calculate a sleepiness index. After euthanasia, blood was collected for corticosterone assessment. Results Using the average of group sleep attempts, it was possible to differentiate between sleepy (mean>group average) and resistant animals (mean<group average). Resistant mice were more frequent in all settings. Individual variation accounted for 52% of sleepiness variance during chronic sleep deprivation and extended wakefulness explained 68% of sleepiness variance during acute sleep deprivation. A normal corticosterone peak was observed at the start of the dark phase, independent of sleep deprivation. Conclusion Different profiles of sleepiness emerged in sleep deprived mice. Sleep deprivation was the main factor for sleepiness during acute sleep deprivation whereas in chronic deprivation individual variation was more relevant. Support (If Any) Our studies are supported by the following funding agencies: AFIP (Associação Fundo de Incentivo à Pesquisa), São Paulo Research Foundation (FAPESP #2017/18455-5 to GLF), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES - Finance Code 001 to GLF), and CNPq (fellowships to MLA and ST; #169040/2017-8, and #141445/2021-1 to GLF). This study received indirect funding from AFIP and CNPq, which support the department in which the project was conducted.

Nine-day continuous recording of EEG and 2-hour of high-density EEG under chronic sleep restriction in mice

This work provides an EEG dataset collected from nine mice during the sleep deprivation (SD) paradigm for the sleep science community. It includes 9-day of continuous recording of the frontal and parietal EEG, accelerometer, and 2-hour of high-density EEG (HD-EEG) under SD and SD-free conditions. Eighteen hours of SD were conducted on 5 consecutive days. The HD-EEG data were saved in the EEGLAB format and stored as the brain imaging data structure (BIDS). These datasets can be used to (i) compare mouse HD-EEG to human HD-EEG, (ii) track oscillatory activities of the sleep EEG (e.g., slow waves, spindles) across the cortical regions under different conditions of sleep pressure, and (iii) investigate the cortical traveling waves in the mouse brain. We also provided Python code for basic analyses of this dataset, including the detection of slow waves and sleep spindles. We hope that our dataset will reveal hidden activities during sleep and lead to a better understanding of the functions and mechanisms of sleep.

Sleepiness profiles in mice submitted to acute and chronic sleep deprivation

SummarySleepiness is a behavioural consequence of sleep pressure, which shows interindividual variation, a characteristic possibly related to central sleep mechanisms. However, there is a lack of evidence linking progressive sleep need and sleepiness with factors of individual variability, which could be tested by total acute and chronic sleep deprivation. Thus, the objective of the study was to investigate the development of sleepiness in sleep deprived mice. Male C57BL/6J mice were distributed in sleep deprivation, sleep rebound and control groups. Animals underwent acute sleep deprivation for 3, 6, 9 or 12 h or chronic sleep deprivation for 6 h for 5 consecutive days. Sleep rebound groups had a sleep opportunity for 1, 2, 3, or 4 h after acute sleep deprivation or 24 h after chronic sleep deprivation. During the protocols, sleep attempts were counted to calculate a sleepiness index. After euthanasia, blood was collected for corticosterone assessment. Using the average of group sleep attempts, it was possible to differentiate between sleepy (mean>group average) and resistant animals (mean<group average). Resistant mice were more frequent in all protocols. Individual variation accounted for 52% of sleepiness variance during chronic sleep deprivation and extended wakefulness explained 68% of sleepiness variance during acute sleep deprivation. A normal corticosterone peak was observed at the start of the dark phase, independent of sleep deprivation. Different profiles of sleepiness emerged in sleep deprived mice. Sleep deprivation was the main factor for sleepiness during acute sleep deprivation whereas in chronic deprivation individual variation was more relevant.

Adenosine, caffeine, and sleep-wake regulation: state of the science and perspectives.

SummaryFor hundreds of years, mankind has been influencing its sleep and waking state through the adenosinergic system. For ~100 years now, systematic research has been performed, first started by testing the effects of different dosages of caffeine on sleep and waking behaviour. About 70 years ago, adenosine itself entered the picture as a possible ligand of the receptors where caffeine hooks on as an antagonist to reduce sleepiness. Since the scientific demonstration that this is indeed the case, progress has been fast. Today, adenosine is widely accepted as an endogenous sleep‐regulatory substance. In this review, we discuss the current state of the science in model organisms and humans on the working mechanisms of adenosine and caffeine on sleep. We critically investigate the evidence for a direct involvement in sleep homeostatic mechanisms and whether the effects of caffeine on sleep differ between acute intake and chronic consumption. In addition, we review the more recent evidence that adenosine levels may also influence the functioning of the circadian clock and address the question of whether sleep homeostasis and the circadian clock may interact through adenosinergic signalling. In the final section, we discuss the perspectives of possible clinical applications of the accumulated knowledge over the last century that may improve sleep‐related disorders. We conclude our review by highlighting some open questions that need to be answered, to better understand how adenosine and caffeine exactly regulate and influence sleep.

Impairment of sleep homeostasis in cervical dystonia patients

Alterations in brain plasticity seem to play a role in the pathophysiology of cervical dystonia (CD). Since evidences indicate that sleep regulates brain plasticity, we hypothesized that an alteration in sleep homeostatic mechanisms may be involved in the pathogenesis of CD. We explored sleep in control subjects (CTL) and CD patients before (Tpre-BoNT) and after (Tpost-BoNT) botulinum toxin (BoNT) treatment. A physiological slow wave activity (SWA) power decrease throughout the night was observed in CTL but not in CD at Tpre-BoNT. BoNT restored the physiological SWA decrease in CD at Tpost-BoNT. Furthermore, in the first part of the night, CD at Tpost-BNT showed a frontal increase and parietal decrease in SWA power compared to CD at Tpre-BoNT, with a SWA distribution comparable to that observed in CTL. Our data highlighted a pathophysiological relationship between SWA during sleep and CD and provided novel insight into the transient central plastic effect of BoNT.

Sleep restriction alters cortical inhibition in migraine: A transcranial magnetic stimulation study

ObjectiveMigraine is a primary headache disorder with a well-known association with insufficient sleep. However, both the underlying pathophysiology of the disease and the relationship with sleep is still unexplained. In this study, we apply transcranial magnetic stimulation to investigate possible mechanisms of insufficient sleep in migraine. MethodsWe used a randomised, blinded crossover design to examine 46 subjects with migraine during the interictal period and 29 healthy controls. Each subject underwent recordings of cortical silent period, short- and long-interval intracortical inhibition, intracortical facilitation and short-latency afferent inhibition after both two nights of habitual eight-hour sleep and two nights of restricted four-hour sleep. ResultsWe found reduced cortical silent period duration after sleep restriction in interictal migraineurs compared to controls (p = 0.046). This effect was more pronounced for non-sleep related migraine (p = 0.002) and migraine with aura (p = 0.017). The sleep restriction effect was associated with ictal symptoms of hypersensitivity such as photophobia (p = 0.017) and overall silent period was associated with premonitory dopaminergic symptoms such as yawning (p = 0.034). ConclusionsSleep restriction reduces GABAergic cortical inhibition during the interictal period in individuals with migraine. SignificanceSleep related mechanisms appear to affect the pathophysiology of migraine and may differentiate between migraine subgroups.

Review study on epileptiform discharge during sleep and circadian rhythm modulation during seizures

Epilepsy is a neurological condition that affects approximately more than 50 million people around the globe, out of which the prevalence of this disease is also seen in developed countries. Epilepsy can be clinical defined by two or more non triggered seizures. A seizure can be characterized as a paroxysmal event which is caused due to hyper–synchronization in the neurons that many have various reasons of manifestation. The neuronal discharge maybe focal spreading in specific brain cortex or widespread throughout the cortex. An Electroencephalogram (EEG) is used to in diagnosis and management of epilepsy and can be used for routine examinations, it also considered to be the golden standard investigation of epileptic syndrome. While using EEG the distribution, presence and frequency of interictal epileptiform discharges IEDs are suggestive diagnosis of epilepsy. In other words the presence of IEDs in an individual’s EEG is a diagnosis of epilepsy. IEDs are predominantly found in EEG that is performed during sleep which can give basic diagnosis and prognosis of sleep related epilepsies in patients. During sleep latent interictal discharge are activated. Sleep IEDs are said to greatly affect the epilepsy management. These interaction mechanisms of sleep and epilepsies tends to bring about changes in behaviour of the seizure.

Resting-state functional connectivity of the sensory/somatomotor network associated with sleep quality: evidence from 202 young male samples.

Previous neuroimaging studies have demonstrated that sleep is associated with brain functional changes in some specific brain regions. However, few studies have examined the relationship between all possible functional connectivities (FCs) within the sensory/somatomotor network (SSN) and the sleep quality of young male samples. The SSN consists of two motor cortices and is known to play a critical role in sleep. Poor sleep quality may be associated with increased sensory/somatomotor functional connectivity during rest. Hence, 202 young male participants underwent a resting-state functional magnetic resonance imaging (fMRI) scan and completed the Pittsburgh Sleep Quality Index (PSQI). Results indicated that increased functional connectivity within the SSN was associated with poor sleep quality. Specifically, the total PSQI score was positively correlated with the increased functional connectivity of the left paracentral lobule (PCL), bilateral precentral gyrus (PreCG), supplementary motor area (SMA) and bilateral postcentral gyrus (PoCG). Additionally, our findings also exhibited that (a) the subjective sleep quality factor of PSQI was positively correlated with FC between the bilateral PoCG and the bilateral PCL as well as between the left PreCG and the right SMA; (b) the sleep latency factor of PSQI was positively correlated with FC between the left PoCG and the right precuneus (PCUN); (c) the sleep disturbances factor of PSQI was positively correlated with FC between the left PCL and the right PoCG, and (d) the daytime dysfunction factor of PSQI was positively correlated with FC between the bilateral PoCG and the left PCL as well as between the bilateral PreCG and the SMA. In short, our findings can be comprehensively understood as neural mechanisms of intrinsic SSN connectivity are associated with sleep quality of man. Meanwhile, it may expand our knowledge and provide new insight into a deeper understanding of the neurobiological mechanisms of sleep or sleep problems.

Integrative Proteome and Ubiquitinome Analyses Reveal the Substrates of BTBD9 and Its Underlying Mechanism in Sleep Regulation.

Ubiquitination is a major posttranslational modification of proteins that affects their stability, and E3 ligases play a key role in ubiquitination by specifically recognizing their substrates. BTBD9, an adaptor of the Cullin-RING ligase complex, is responsible for substrate recognition and is associated with sleep homeostasis. However, the substrates of BTBD9-mediated ubiquitination remain unknown. Here, we generated an SH-SY5Y cell line stably expressing BTBD9 and performed proteomic analysis combined with ubiquitinome analysis to identify the downstream targets of BTBD9. Through this approach, we identified four potential BTBD9-mediated ubiquitination substrates that are targeted for degradation. Among these candidate substrates, inosine monophosphate dehydrogenase (IMPDH2), a novel target of BTBD9-mediated degradation, is a potential risk gene for sleep dysregulation. In conclusion, these findings not only demonstrate that proteomic analysis can be a useful general approach for the systematic identification of E3 ligase substrates but also identify novel substrates of BTBD9, providing a resource for future studies of sleep regulation mechanisms.

Goodnight, astrocyte: waking up to astroglial mechanisms in sleep.

Astrocytes mediate many important aspects of neural homeostasis, but until recently, their role in sleep was largely unknown. The situation has dramatically changed in the last decade. The use of transgenic animals, optogenetics, chemogenetics, brain imaging and sophisticated molecular assays has led to exciting discoveries. Astrocytes dynamically change their activity across the sleep-wake cycle and may encode sleep need via changes in intracellular signalling pathways. Astrocytes also exocytose/secrete sleep-inducing molecules which modulate brain activity, sleep architecture and sleep regulation. Many of these observations have been made in mice and Drosophila melanogaster, indicating that astroglial sleep mechanisms are evolutionarily conserved. We review recent findings and discuss future directions.

Maladaptive coping mechanisms of sleep.

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Maladaptive coping mechanisms of sleep.

Patients with insomnia have been shown to use many maladaptive coping mechanisms. This article examines the effect of such coping mechanisms on sleep quality by reviewing results of polysomnography and the Epworth Sleepiness Scale among 137 patients. The study showed that sleep quality was affected by these mechanisms.

Interactions between Sleep and Emotions in Humans and Animal Models.

Recently, increased interest and efforts were observed in describing the possible interaction between sleep and emotions. Human and animal model studies addressed the implication of both sleep patterns and emotional processing in neurophysiology and neuropathology in suggesting a bidirectional interaction intimately modulated by complex mechanisms and factors. In this context, we aimed to discuss recent evidence and possible mechanisms implicated in this interaction, as provided by both human and animal models in studies. In addition, considering the affective component of brain physiological patterns, we aimed to find reasonable evidence in describing the two-way association between comorbid sleep impairments and psychiatric disorders. The main scientific literature databases (PubMed/Medline, Web of Science) were screened with keyword combinations for relevant content taking into consideration only English written papers and the inclusion and exclusion criteria, according to PRISMA guidelines. We found that a strong modulatory interaction between sleep processes and emotional states resides on the activity of several key brain structures, such as the amygdala, prefrontal cortex, hippocampus, and brainstem nuclei. In addition, evidence suggested that physiologically and behaviorally related mechanisms of sleep are intimately interacting with emotional perception and processing which could advise the key role of sleep in the unconscious character of emotional processes. However, further studies are needed to explain and correlate the functional analysis with causative and protective factors of sleep impairments and negative emotional modulation on neurophysiologic processing, mental health, and clinical contexts.

Optimal configuration of 5G base station energy storage considering sleep mechanism

The high-energy consumption and high construction density of 5G base stations have greatly increased the demand for backup energy storage batteries. To maximize overall benefits for the investors and operators of base station energy storage, we proposed a bi-level optimization model for the operation of the energy storage, and the planning of 5G base stations considering the sleep mechanism. A multi-base station cooperative system composed of 5G acer stations was considered as the research object, and the outer goal was to maximize the net profit over the complete life cycle of the energy storage. Furthermore, the power and capacity of the energy storage configuration were optimized. The inner goal included the sleep mechanism of the base station, and the optimization of the energy storage charging and discharging strategy, for minimizing the daily electricity expenditure of the 5G base station system. Additionally, genetic algorithm and mixed integer programming were used to solve the bi-level optimization model, analyze the numerical example test comparison of the three types of batteries and the net income of the configuration, and finally verify the validity of the model. Furthermore, the sleep mechanism, the charging and discharging strategy for energy consumption, and the economic benefits for the operators were investigated to provide reference for the 5G base station energy storage configuration.

Delta Oscillations Coordinate Intracerebellar and Cerebello-Hippocampal Network Dynamics during Sleep.

During sleep, the widespread coordination of neuronal oscillations across both cortical and subcortical brain regions is thought to support various physiological functions. However, how sleep-related activity within the brain's largest sensorimotor structure, the cerebellum, is multiplexed with well-described sleep-related mechanisms in regions such as the hippocampus remains unknown. We therefore simultaneously recorded from the dorsal hippocampus and three distinct regions of the cerebellum (Crus I, lobule VI, and lobules II/III) in male mice during natural sleep. Local field potential (LFP) oscillations were found to be coordinated between these structures in a sleep stage-specific manner. During non-REM sleep, prominent δ frequency coherence was observed between lobule VI and hippocampus, whereas non-REM-associated hippocampal sharp-wave ripple activity evoked discrete LFP modulation in all recorded cerebellar regions, with the shortest latency effects in lobule VI. We also describe discrete phasic sharp potentials (PSPs), which synchronize across cerebellar regions and trigger sharp-wave ripple suppression. During REM, cerebellar δ phase significantly modulated hippocampal theta frequency, and this effect was greatest when PSPs were abundant. PSPs were phase-locked to cerebellar δ oscillation peak and hippocampal theta oscillation trough, respectively. Within all three cerebellar regions, prominent LFP oscillations were observed at both low (δ, <4 Hz) and very high frequencies (∼250 Hz) during non-REM and REM sleep. Intracerebellar cross-frequency analysis revealed that δ oscillations modulate those in the very high-frequency range. Together, these results reveal multiple candidate physiological mechanisms to support "offline," bidirectional interaction within distributed cerebello-hippocampal networks.SIGNIFICANCE STATEMENT Sleep is associated with widespread coordination of activity across a range of brain regions. However, little is known about how activity within the largest sensorimotor region of the brain, the cerebellum, is both intrinsically organized and links with higher-order structures, such as the hippocampus, during sleep. By making multisite local field potential recordings in naturally sleeping mice, we reveal and characterize multiple sleep stage-specific physiological mechanisms linking three distinct cerebellar regions with the hippocampus. Central to these physiological mechanisms is a prominent δ (<4 Hz) oscillation, which temporally coordinates both intracerebellar and cerebello-hippocampal network dynamics. Understanding this distributed network activity is important for gaining insight into cerebellar contributions to sleep-dependent processes, such as memory consolidation.

Sleep and Daily Social Experiences as Potential Mechanisms Linking Social Integration to Nocturnal Blood Pressure Dipping.

Socially integrated individuals are at lower risk of cardiovascular disease morbidity and mortality compared with their more isolated counterparts. This association may be due, in part, to the effect of social integration on nocturnal blood pressure (BP) decline or "dipping," a physiological process associated with decreased disease risk. However, the pathways linking social integration with nocturnal BP dipping are unknown. We sought to replicate the association between social integration and BP dipping, and to test whether sleep characteristics (duration, regularity, continuity) and/or daily social interactions (frequency, valence) helped to explain the association. A total of 391 healthy midlife adults completed an actigraphy assessment protocol that measured sleep. During four actigraphy assessment days, participants also completed ambulatory BP monitoring and ecological momentary assessment protocols that measured BP and social interactions at regular intervals throughout the day. Social integration was assessed via a questionnaire. Linear regression controlling for age, sex, race, education, and body mass index indicated that higher levels of social integration were associated with greater nocturnal BP dipping, as indicated by a smaller ratio of night/day mean arterial pressure (β = -0.11, p = .031). Analyses of indirect effects suggested that this association was explained, in part, by greater sleep regularity among more integrated individuals. We did not find evidence for other hypothesized indirect effects. This was the first study to investigate sleep and social mechanisms underlying the link between social integration and nocturnal BP dipping. Because sleep regularity is modifiable, this pathway represents a potential intervention target to promote nocturnal BP dipping.