Coordinated infraslow neural and cardiac oscillations mark fragility and offline periods in mammalian sleep

Central pattern generator control of a vertebrate ultradian sleep rhythm

The mechanisms underlying the mammalian ultradian sleep rhythm-the alternation of rapid-eye-movement (REM) and slow-wave (SW) states-are not well understood but probably depend, at least in part, on circuits in the brainstem1-6. Here, we use perturbation experiments to probe this ultradian rhythm in sleeping lizards (Pogona vitticeps)7-9 and test the hypothesis that it originates in a central pattern generator10,11-circuits that are typically susceptible to phase-dependent reset and entrainment by external stimuli12. Using light pulses, we find that Pogona's ultradian rhythm8 can be reset in a phase-dependent manner, with a critical transition from phase delay to phase advance in the middle of SW. The ultradian rhythm frequency can be decreased or increased, within limits, by entrainment with light pulses. During entrainment, Pogona REM (REMP) can be shortened but not lengthened, whereas SW can be dilated more flexibly. In awake animals, a few alternating light/dark epochs matching natural REMP and SW durations entrain a sleep-like brain rhythm, suggesting the transient activation of an ultradian rhythm generator. In sleeping animals, a light pulse delivered to a single eye causes an immediate ultradian rhythm reset, but only of the contralateral hemisphere; both sides resynchronize spontaneously, indicating that sleep is controlled by paired rhythm-generating circuits linked by functional excitation. Our results indicate that central pattern generators of a type usually known to control motor rhythms may also organize the ultradian sleep rhythm in a vertebrate.

Topography of putative bidirectional interaction between hippocampal sharp wave ripples and neocortical slow oscillations

Systems consolidation relies on coordination between hippocampal sharp-wave ripples (SWRs) and neocortical UP/DOWN states during sleep. However, whether this coupling exists across neocortex and the mechanisms enabling it remain unknown. By combining electrophysiology in mouse hippocampus (HPC) and retrosplenial cortex (RSC) with widefield imaging of dorsal neocortex, we found spatially and temporally precise bidirectional hippocampo-neocortical interaction. HPC multi-unit activity and SWR probability was correlated with UP/DOWN states in mouse default mode network, with highest modulation by RSC in deep sleep. Further, some SWRs were preceded by the high rebound excitation accompanying DMN DOWN→UP transitions, while large-amplitude SWRs were often followed by DOWN states originating in RSC. We explain these electrophysiological results with a model in which HPC and RSC are weakly coupled excitable systems capable of bi-directional perturbation and suggest RSC may act as a gateway through which SWRs can perturb downstream cortical regions via cortico-cortical propagation of DOWN states.

Serotonin modulates infraslow oscillation in the dentate gyrus during Non-REM sleep

Synchronous neuronal activity is organized into neuronal oscillations with various frequency and time domains across different brain areas and brain states. For example, hippocampal theta, gamma and sharp wave oscillations are critical for memory formation and communication between hippocampal subareas and the cortex. In this study, we investigated the neuronal activity of the dentate gyrus (DG) with optical imaging tools during sleep-wake cycles. We found that the activity of major glutamatergic cell populations in the DG is organized into infraslow oscillations (0.01 - 0.03 Hz) during NREM sleep. Although the DG is considered a sparsely active network during wakefulness, we found that 50% of granule cells and about 25% of mossy cells exhibit increased activity during NREM sleep. Further experiments revealed that the infraslow oscillation in the DG was correlated with rhythmic serotonin release during sleep, which oscillates at the same frequency but in an opposite phase. Genetic manipulation of 5-HT receptors revealed that this neuromodulatory regulation is mediated by 5-HT1a receptors and the knockdown of these receptors leads to memory impairment. Together, our results provide novel mechanistic insights into how the 5-HT system can influence hippocampal activity patterns during sleep.

Temporal dynamics of negative emotional memory reprocessing during sleep

Memory reprocessing during sleep is a well-established phenomenon in numerous studies. However, it is unclear whether the intensity of memory reprocessing is consistently maintained throughout the night or exhibits dynamic changes. This study investigates the temporal dynamics of negative emotional memory reprocessing during sleep, with a specific focus on slow oscillation (SO)-spindle coupling and its role in memory reprocessing. In the first experiment (N = 40, mean age = 22.5 years), we detected the negative emotional memory reprocessing strength in each sleep cycle, we found that the 2nd sleep cycle after negative emotional memory learning constitute the most sensitive window for memory reprocessing, furthermore, SO-spindle coupling signals in this window plays a role in stabilizing negative emotional memory. To verify the role of SO-spindle coupling in negative emotional memory reprocessing, we utilized transcranial alternating current stimulation (tACS) to disrupt SO-spindle coupling during the 2nd sleep cycle (N = 21, mean age = 19.3 years). Notably, the outcomes of the tACS intervention demonstrated a significant reduction in the recognition of negative emotional memories. These findings offer new insights into the mechanisms that regulate emotional memory consolidation during sleep and may have implications for addressing psychiatric disorders associated with pathological emotional memory.

Emerging Functions of Neuromodulation during Sleep

Neuromodulators act on multiple timescales to affect neuronal activity and behavior. They function as synaptic fine-tuners and master coordinators of neuronal activity across distant brain regions and body organs. While much research on neuromodulation has focused on roles in promoting features of wakefulness and transitions between sleep and wake states, the precise dynamics and functions of neuromodulatory signaling during sleep have received less attention. This review discusses research presented at our minisymposium at the 2024 Society for Neuroscience meeting, highlighting how norepinephrine, dopamine, and acetylcholine orchestrate brain oscillatory activity, control sleep architecture and microarchitecture, regulate responsiveness to sensory stimuli, and facilitate memory consolidation. The potential of each neuromodulator to influence neuronal activity is shaped by the state of the synaptic milieu, which in turn is influenced by the organismal or systemic state. Investigating the effects of neuromodulator release across different sleep substates and synaptic environments offers unique opportunities to deepen our understanding of neuromodulation and explore the distinct computational opportunities that arise during sleep. Moreover, since alterations in neuromodulatory signaling and sleep are implicated in various neuropsychiatric disorders and because existing pharmacological treatments affect neuromodulatory signaling, gaining a deeper understanding of the less-studied aspects of neuromodulators during sleep is of high importance.

The timing of sleep spindles is modulated by the respiratory cycle in humans

OBJECTIVE

Coupling of sleep spindles with cortical slow waves and hippocampus sharp-waves ripples is crucial for sleep-related memory consolidation. Recent literature evidenced that nasal respiration modulates neural activity in large-scale brain networks. In rodents, this respiratory drive strongly varies according to vigilance states. Whether sleep oscillations are also respiration-modulated in humans remains open. In this work, we investigated the influence of breathing on sleep spindles during non-rapid-eye-movement sleep in humans.

METHODS

Full night polysomnography of twenty healthy participants were analysed. Spindles and slow waves were automatically detected during N2 and N3 stages. Spindle-related sigma power as well as spindle and slow wave events were analysed according to the respiratory phase.

RESULTS

We found a significant coupling between both slow and fast spindles and the respiration cycle, with enhanced sigma activity and occurrence probability of spindles during the middle part of the expiration phase. A different coupling was observed for slow waves negative peaks which were rather distributed around the two respiration phase transitions.

CONCLUSION

Our findings suggest that breathing cycle influences the dynamics of brain activity during non-rapid-eye-movement sleep.

SIGNIFICANCE

This coupling may enable sleep spindles to synchronize with other sleep oscillations and facilitate information transfer between distributed brain networks.

Oscillatory-Quality of sleep spindles links brain state with sleep regulation and function

Here, we characterized the dynamics of sleep spindles, focusing on their damping, which we estimated using a metric called oscillatory-Quality (o-Quality), derived by fitting an autoregressive model to electrophysiological signals, recorded from the cortex in mice. The o-Quality of sleep spindles correlates weakly with their amplitude, shows marked laminar differences and regional topography across cortical regions, reflects the level of synchrony within and between cortical networks, is strongly modulated by sleep-wake history, reflects the degree of sensory disconnection, and correlates with the strength of coupling between spindles and slow waves. As most spindle events are highly localized and not detectable with conventional low-density recording approaches, o-Quality thus emerges as a valuable metric that allows us to infer the spread and dynamics of spindle activity across the brain and directly links their spatiotemporal dynamics with local and global regulation of brain states, sleep regulation, and function.

Sleep oscillations related to memory consolidation during aromatases inhibitors for breast cancer

Aromatase inhibitors (AIs) are associated with sleep difficulties in breast cancer (BC) patients. Sleep is known to favor memory consolidation through the occurrence of specific oscillations, i.e., slow waves (SW) and sleep spindles, allowing a dialogue between prefrontal cortex and the hippocampus. Interestingly, neuroimaging studies in BC patients have consistently shown structural and functional modifications in these two brain regions. With the aim to evaluate sleep oscillations related to memory consolidation during AIs, we collected polysomnography data in BC patients treated (AI+, n = 17) or not (AI-, n = 17) with AIs compared to healthy controls (HC, n = 21). None of the patients had received chemotherapy and radiotherapy was finished since at least 6 months, that limit the confounding effects of other treatments than AIs. Fast and slow spindles were detected during sleep stage 2 at centro-parietal and frontal electrodes respectively. SW were detected at frontal electrodes during stage 3. Here, we show lower frontal SW densities in AI + patients compared to HC. These results concord with previous reports about frontal cortical alterations in cancer following AIs administration. Moreover, AI + patients tended to have lower spindle density at C4 electrode. Regression analyses showed that, in both patient groups, spindle density at C4 electrode explained a large variance of memory performances. Slow spindle characteristics did not differ between groups and sleep oscillations characteristics of AI- patients did not differ significantly from those of both AI + patients and HC. Overall, our results add to the compelling evidence of the systemic effects of AIs previously reported in animals, with deleterious effects on cortical activity during sleep and associated memory consolidation in the current study. There is thus a need to further investigate sleep modifications during AIs administration. Longitudinal studies are needed to confirm these findings and investigation in other cancers on this topic should be conducted.

Thalamic epileptic spikes disrupt sleep spindles in patients with epileptic encephalopathy

In severe epileptic encephalopathies, epileptic activity contributes to progressive cognitive dysfunction. Epileptic encephalopathies share the trait of spike-wave activation during non-REM sleep (EE-SWAS), a sleep stage dominated by sleep spindles, which are brain oscillations known to coordinate offline memory consolidation. Epileptic activity has been proposed to hijack the circuits driving these thalamocortical oscillations, thereby contributing to cognitive impairment. Using a unique dataset of simultaneous human thalamic and cortical recordings in subjects with and without EE-SWAS, we provide evidence for epileptic spike interference of thalamic sleep spindle production in patients with EE-SWAS. First, we show that epileptic spikes and sleep spindles are both predicted by slow oscillations during stage two sleep (N2), but at different phases of the slow oscillation. Next, we demonstrate that sleep-activated cortical epileptic spikes propagate to the thalamus (thalamic spike rate increases after a cortical spike, P ≈ 0). We then show that epileptic spikes in the thalamus increase the thalamic spindle refractory period (P ≈ 0). Finally, we show that in three patients with EE-SWAS, there is a downregulation of sleep spindles for 30 s after each thalamic spike (P < 0.01). These direct human thalamocortical observations support a proposed mechanism for epileptiform activity to impact cognitive function, wherein epileptic spikes inhibit thalamic sleep spindles in epileptic encephalopathy with spike and wave activation during sleep.

Circuit mechanism underlying fragmented sleep and memory deficits in 16p11.2 deletion mouse model of autism

Sleep disturbances are prevalent in children with autism spectrum disorder (ASD) and have a major impact on the quality of life. Strikingly, sleep problems are positively correlated with the severity of ASD symptoms, such as memory impairment. However, the neural mechanisms underlying sleep disturbances and cognitive deficits in ASD are largely unexplored. Here, we show that non-rapid eye movement sleep (NREMs) is highly fragmented in the 16p11.2 deletion mouse model of ASD. The degree of sleep fragmentation is reflected in an increased number of calcium transients in the activity of locus coeruleus noradrenergic (LC-NE) neurons during NREMs. Exposure to a novel environment further exacerbates sleep disturbances in 16p11.2 deletion mice by fragmenting NREMs and decreasing rapid eye movement sleep (REMs). In contrast, optogenetic inhibition of LC-NE neurons and pharmacological blockade of noradrenergic transmission using clonidine reverse sleep fragmentation. Furthermore, inhibiting LC-NE neurons restores memory. Rabies-mediated unbiased screening of presynaptic neurons reveals altered connectivity of LC-NE neurons with sleep- and memory regulatory brain regions in 16p11.2 deletion mice. Our findings demonstrate that heightened activity of LC-NE neurons and altered brain-wide connectivity underlies sleep fragmentation in 16p11.2 deletion mice and identify a crucial role of the LC-NE system in regulating sleep stability and memory in ASD.

Shared EEG correlates between non-REM parasomnia experiences and dreams

Sleepwalking and related parasomnias result from incomplete awakenings out of non-rapid eye movement sleep. Behavioral episodes can occur without consciousness or recollection, or in relation to dream-like experiences. To understand what accounts for these differences in consciousness and recall, here we recorded parasomnia episodes with high-density electroencephalography (EEG) and interviewed participants immediately afterward about their experiences. Compared to reports of no experience (19%), reports of conscious experience (56%) were preceded by high-amplitude EEG slow waves in anterior cortical regions and activation of posterior cortical regions, similar to previously described EEG correlates of dreaming. Recall of the content of the experience (56%), compared to no recall (25%), was associated with higher EEG activation in the right medial temporal region before movement onset. Our work suggests that the EEG correlates of parasomnia experiences are similar to those reported for dreams and may thus reflect core physiological processes involved in sleep consciousness.

Nociceptor spontaneous activity is responsible for fragmenting non-rapid eye movement sleep in mouse models of neuropathic pain

Spontaneous pain, a major complaint of patients with neuropathic pain, has eluded study because there is no reliable marker in either preclinical models or clinical studies. Here, we performed a comprehensive electroencephalogram/electromyogram analysis of sleep in several mouse models of chronic pain: neuropathic (spared nerve injury and chronic constriction injury), inflammatory (Freund's complete adjuvant and carrageenan, plantar incision) and chemical pain (capsaicin). We find that peripheral axonal injury drives fragmentation of sleep by increasing brief arousals from non-rapid eye movement sleep (NREMS) without changing total sleep amount. In contrast to neuropathic pain, inflammatory or chemical pain did not increase brief arousals. NREMS fragmentation was reduced by the analgesics gabapentin and carbamazepine, and it resolved when pain sensitivity returned to normal in a transient neuropathic pain model (sciatic nerve crush). Genetic silencing of peripheral sensory neurons or ablation of CGRP+ neurons in the parabrachial nucleus prevented sleep fragmentation, whereas pharmacological blockade of skin sensory fibers was ineffective, indicating that the neural activity driving the arousals originates ectopically in primary nociceptor neurons and is relayed through the lateral parabrachial nucleus. These findings identify NREMS fragmentation by brief arousals as an effective proxy to measure spontaneous neuropathic pain in mice.

Sleepiness and the transition from wakefulness to sleep

The transition from wakefulness to sleep is a progressive process that is reflected in the gradual loss of responsiveness, an alteration of cognitive functions, and a drastic shift in brain dynamics. These changes do not occur all at once. The sleep onset period (SOP) refers here to this period of transition between wakefulness and sleep. For example, although transitions of brain activity at sleep onset can occur within seconds in a given brain region, these changes occur at different time points across the brain, resulting in a SOP that can last several minutes. Likewise, the transition to sleep impacts cognitive and behavioral levels in a graded and staged fashion. It is often accompanied and preceded by a sensation of drowsiness and the subjective feeling of a need for sleep, also associated with specific physiological and behavioral signatures. To better characterize fluctuations in vigilance and the SOP, a multidimensional approach is thus warranted. Such a multidimensional approach could mitigate important limitations in the current classification of sleep, leading ultimately to better diagnoses and treatments of individuals with sleep and/or vigilance disorders. These insights could also be translated in real-life settings to either facilitate sleep onset in individuals with sleep difficulties or, on the contrary, prevent or control inappropriate sleep onsets.

Circuit mechanism underlying fragmented sleep and memory deficits in 16p11.2 deletion mouse model of autism

Sleep disturbances are prevalent in children with autism spectrum disorder (ASD) and have a major impact on the quality of life. Strikingly, sleep problems are positively correlated with the severity of ASD symptoms, such as memory impairment. However, the neural mechanisms underlying sleep disturbances and cognitive deficits in ASD are largely unexplored. Here, we show that non-rapid eye movement sleep (NREMs) is highly fragmented in the 16p11.2 deletion mouse model of ASD. The degree of sleep fragmentation is reflected in an increased number of calcium transients in the activity of locus coeruleus noradrenergic (LC-NE) neurons during NREMs. Exposure to a novel environment further exacerbates sleep disturbances in 16p11.2 deletion mice by fragmenting NREMs and decreasing rapid eye movement sleep (REMs). In contrast, optogenetic inhibition of LC-NE neurons and pharmacological blockade of noradrenergic transmission using clonidine reverse sleep fragmentation. Furthermore, inhibiting LC-NE neurons restores memory. Rabies-mediated unbiased screening of presynaptic neurons reveals altered connectivity of LC-NE neurons with sleep- and memory regulatory brain regions in 16p11.2 deletion mice. Our findings demonstrate that heightened activity of LC-NE neurons and altered brain-wide connectivity underlies sleep fragmentation in 16p11.2 deletion mice and identify a crucial role of the LC-NE system in regulating sleep stability and memory in ASD.

Individualized temporal patterns dominate cortical upstate and sleep depth in driving human sleep spindle timing

Sleep spindles are critical for memory consolidation and strongly linked to neurological disease and aging. Despite their significance, the relative influences of factors like sleep depth, cortical up/down states, and spindle temporal patterns on individual spindle production remain poorly understood. Moreover, spindle temporal patterns are typically ignored in favor of an average spindle rate. Here, we analyze spindle dynamics in 1008 participants from the Multi-Ethnic Study of Atherosclerosis using a point process framework. Results reveal fingerprint-like temporal patterns, characterized by a refractory period followed by a period of increased spindle activity, which are highly individualized yet consistent night-to-night. We observe increased timing variability with age and distinct gender/age differences. Strikingly, and in contrast to the prevailing notion, individualized spindle patterns are the dominant determinant of spindle timing, accounting for over 70% of the statistical deviance explained by all of the factors we assessed, surpassing the contribution of slow oscillation (SO) phase (~14%) and sleep depth (~16%). Furthermore, we show spindle/SO coupling dynamics with sleep depth are preserved across age, with a global negative shift towards the SO rising slope. These findings offer novel mechanistic insights into spindle dynamics with direct experimental implications and applications to individualized electroencephalography biomarker identification.

Sleep scoring in rodents: Criteria, automatic approaches and outstanding issues

There is nothing we spend as much time on in our lives as we do sleeping, which makes it even more surprising that we currently do not know why we need to sleep. Most of the research addressing this question is performed in rodents to allow for invasive, mechanistic approaches. However, in contrast to human sleep, we currently do not have shared and agreed upon standards on sleep states in rodents. In this article, we present an overview on sleep stages in humans and rodents and a historical perspective on the development of automatic sleep scoring systems in rodents. Further, we highlight specific issues in rodent sleep that also call into question some of the standards used in human sleep research.

Temporal cluster-based organization of sleep spindles underlies motor memory consolidation

Sleep benefits motor memory consolidation, which is mediated by sleep spindle activity and associated memory reactivations during non-rapid eye movement (NREM) sleep. However, the particular role of NREM2 and NREM3 sleep spindles and the mechanisms triggering this memory consolidation process remain unclear. Here, simultaneous electroencephalographic and functional magnetic resonance imaging (EEG-fMRI) recordings were collected during night-time sleep following the learning of a motor sequence task. Adopting a time-based clustering approach, we provide evidence that spindles iteratively occur within clustered and temporally organized patterns during both NREM2 and NREM3 sleep. However, the clustering of spindles in trains is related to motor memory consolidation during NREM2 sleep only. Altogether, our findings suggest that spindles' clustering and rhythmic occurrence during NREM2 sleep may serve as an intrinsic rhythmic sleep mechanism for the timed reactivation and subsequent consolidation of motor memories, through synchronized oscillatory activity within a subcortical-cortical network involved during learning.

Regulation of stress-induced sleep fragmentation by preoptic glutamatergic neurons

Sleep disturbances are detrimental to our behavioral and emotional well-being. Stressful events disrupt sleep, in particular by inducing brief awakenings (microarousals, MAs), resulting in sleep fragmentation. The preoptic area of the hypothalamus (POA) is crucial for sleep control. However, how POA neurons contribute to the regulation of MAs and thereby impact sleep quality is unknown. Using fiber photometry in mice, we examine the activity of genetically defined POA subpopulations during sleep. We find that POA glutamatergic neurons are rhythmically activated in synchrony with an infraslow rhythm in the spindle band of the electroencephalogram during non-rapid eye movement sleep (NREMs) and are transiently activated during MAs. Optogenetic stimulation of these neurons promotes MAs and wakefulness. Exposure to acute social defeat stress fragments NREMs and significantly increases the number of transients in the calcium activity of POA glutamatergic neurons during NREMs. By reducing MAs, optogenetic inhibition during spontaneous sleep and after stress consolidates NREMs. Monosynaptically restricted rabies tracing reveals that POA glutamatergic neurons are innervated by brain regions regulating stress and sleep. In particular, presynaptic glutamatergic neurons in the lateral hypothalamus become activated after stress, and stimulating their projections to the POA promotes MAs and wakefulness. Our findings uncover a novel circuit mechanism by which POA excitatory neurons regulate sleep quality after stress.

Recording physiological and pathological cortical activity and exogenous electric fields using graphene microtransistor arrays in vitro

Graphene-based solution-gated field-effect transistors (gSGFETs) allow the quantification of the brain's full-band signal. Extracellular alternating current (AC) signals include local field potentials (LFP, population activity within a reach of hundreds of micrometers), multiunit activity (MUA), and ultimately single units. Direct current (DC) potentials are slow brain signals with a frequency under 0.1 Hz, and commonly filtered out by conventional AC amplifiers. This component conveys information about what has been referred to as "infraslow" activity. We used gSGFET arrays to record full-band patterns from both physiological and pathological activity generated by the cerebral cortex. To this end, we used an in vitro preparation of cerebral cortex that generates spontaneous rhythmic activity, such as that occurring in slow wave sleep. This examination extended to experimentally induced pathological activities, including epileptiform discharges and cortical spreading depression. Validation of recordings obtained via gSGFETs, including both AC and DC components, was accomplished by cross-referencing with well-established technologies, thereby quantifying these components across different activity patterns. We then explored an additional gSGFET potential application, which is the measure of externally induced electric fields such as those used in therapeutic neuromodulation in humans. Finally, we tested the gSGFETs in human cortical slices obtained intrasurgically. In conclusion, this study offers a comprehensive characterization of gSGFETs for brain recordings, with a focus on potential clinical applications of this emerging technology.

Minute-scale oscillatory sequences in medial entorhinal cortex

The medial entorhinal cortex (MEC) hosts many of the brain's circuit elements for spatial navigation and episodic memory, operations that require neural activity to be organized across long durations of experience1. Whereas location is known to be encoded by spatially tuned cell types in this brain region2,3, little is known about how the activity of entorhinal cells is tied together over time at behaviourally relevant time scales, in the second-to-minute regime. Here we show that MEC neuronal activity has the capacity to be organized into ultraslow oscillations, with periods ranging from tens of seconds to minutes. During these oscillations, the activity is further organized into periodic sequences. Oscillatory sequences manifested while mice ran at free pace on a rotating wheel in darkness, with no change in location or running direction and no scheduled rewards. The sequences involved nearly the entire cell population, and transcended epochs of immobility. Similar sequences were not observed in neighbouring parasubiculum or in visual cortex. Ultraslow oscillatory sequences in MEC may have the potential to couple neurons and circuits across extended time scales and serve as a template for new sequence formation during navigation and episodic memory formation.

Dusk2Dawn: an EEGLAB plugin for automatic cleaning of whole-night sleep electroencephalogram using Artifact Subspace Reconstruction

Whole-night sleep electroencephalogram (EEG) is plagued by several types of large-amplitude artifacts. Common approaches to remove them are fraught with issues: channel interpolation, rejection of noisy intervals, and independent component analysis are time-consuming, rely on subjective user decisions, and result in signal loss. Artifact Subspace Reconstruction (ASR) is an increasingly popular approach to rapidly and automatically clean wake EEG data. Indeed, ASR adaptively removes large-amplitude artifacts regardless of their scalp topography or consistency throughout the recording. This makes ASR, at least in theory, a highly-promising tool to clean whole-night EEG. However, ASR crucially relies on calibration against a subset of relatively clean "baseline" data. This is problematic when the baseline changes substantially over time, as in whole-night EEG data. Here we tackled this issue and, for the first time, validated ASR for cleaning sleep EEG. We demonstrate that ASR applied out-of-the-box, with the parameters recommended for wake EEG, results in the dramatic removal of slow waves. We also provide an appropriate procedure to use ASR for automatic and rapid cleaning of whole-night sleep EEG data or any long EEG recording. Our procedure is freely available in Dusk2Dawn, an open-source plugin for EEGLAB.

Effect of sleep deprivation and NREM sleep stage on physiological brain pulsations

Introduction

Sleep increases brain fluid transport and the power of pulsations driving the fluids. We investigated how sleep deprivation or electrophysiologically different stages of non-rapid-eye-movement (NREM) sleep affect the human brain pulsations.

Methods

Fast functional magnetic resonance imaging (fMRI) was performed in healthy subjects (n = 23) with synchronous electroencephalography (EEG), that was used to verify arousal states (awake, N1 and N2 sleep). Cardiorespiratory rates were verified with physiological monitoring. Spectral power analysis assessed the strength, and spectral entropy assessed the stability of the pulsations.

Results

In N1 sleep, the power of vasomotor (VLF < 0.1 Hz), but not cardiorespiratory pulsations, intensified after sleep deprived vs. non-sleep deprived subjects. The power of all three pulsations increased as a function of arousal state (N2 > N1 > awake) encompassing brain tissue in both sleep stages, but extra-axial CSF spaces only in N2 sleep. Spectral entropy of full band and respiratory pulsations decreased most in N2 sleep stage, while cardiac spectral entropy increased in ventricles.

Discussion

In summary, the sleep deprivation and sleep depth, both increase the power and harmonize the spectral content of human brain pulsations.

What is sleep exactly? Global and local modulations of sleep oscillations all around the clock

Wakefulness, non-rapid eye-movement (NREM) and rapid eye-movement (REM) sleep differ from each other along three dimensions: behavioral, phenomenological, physiological. Although these dimensions often fluctuate in step, they can also dissociate. The current paradigm that views sleep as made of global NREM and REM states fail to account for these dissociations. This conundrum can be dissolved by stressing the existence and significance of the local regulation of sleep. We will review the evidence in animals and humans, healthy and pathological brains, showing different forms of local sleep and the consequences on behavior, cognition, and subjective experience. Altogether, we argue that the notion of local sleep provides a unified account for a host of phenomena: dreaming in REM and NREM sleep, NREM and REM parasomnias, intrasleep responsiveness, inattention and mind wandering in wakefulness. Yet, the physiological origins of local sleep or its putative functions remain unclear. Exploring further local sleep could provide a unique and novel perspective on how and why we sleep.

Reconsidering sleep perception in insomnia: from misperception to mismeasurement

So-called 'sleep misperception' refers to a phenomenon in which individuals have the impression of sleeping little or not at all despite normal objective measures of sleep. It is unknown whether this subjective-objective mismatch truly reflects an abnormal perception of sleep, or whether it results from the inability of standard sleep recording techniques to capture 'wake-like' brain activity patterns that could account for feeling awake during sleep. Here, we systematically reviewed studies reporting sleep macro- and microstructural, metabolic, and mental correlates of sleep (mis)perception. Our findings suggest that most individuals tend to accurately estimate their sleep duration measured with polysomnography (PSG). In good sleepers, feeling awake during sleep is the rule at sleep onset, remains frequent in the first non-rapid eye movement sleep cycle and almost never occurs in rapid eye movement (REM) sleep. In contrast, there are patients with insomnia who consistently underestimate their sleep duration, regardless of how long they sleep. Unlike good sleepers, they continue to feel awake after the first sleep cycle and importantly, during REM sleep. Their mental activity during sleep is also more thought-like. Initial studies based on standard PSG parameters largely failed to show consistent differences in sleep macrostructure between these patients and controls. However, recent studies assessing sleep with more refined techniques have revealed that these patients show metabolic and microstructural electroencephalography changes that likely reflect a shift towards greater cortical activation during sleep and correlate with feeling awake. We discuss the significance of these correlates and conclude with open questions and possible ways to address them.

Prefrontal Cortical Regulation of REM Sleep

Rapid-eye-movement (REM) sleep is accompanied by intense cortical activity, underlying its wake-like electroencephalogram (EEG). The neural activity inducing REM sleep is thought to originate from subcortical circuits in brainstem and hypothalamus. However, whether cortical neurons can also trigger REM sleep has remained unknown. Here, we show in mice that the medial prefrontal cortex (mPFC) strongly promotes REM sleep. Bidirectional optogenetic manipulations demonstrate that excitatory mPFC neurons promote REM sleep through their projections to the lateral hypothalamus (LH) and regulate phasic events, reflected in accelerated EEG theta oscillations and increased eye-movement density during REM sleep. Calcium imaging reveals that the majority of LH-projecting mPFC neurons are maximally activated during REM sleep and a subpopulation is recruited during phasic theta accelerations. Our results delineate a cortico-hypothalamic circuit for the top-down control of REM sleep and identify a critical role of the mPFC in regulating phasic events during REM sleep.

Closed-loop auditory stimulation of sleep slow oscillations: Basic principles and best practices

Sleep is essential for our physical and mental well-being. During sleep, despite the paucity of overt behavior, our brain remains active and exhibits a wide range of coupled brain oscillations. In particular slow oscillations are characteristic for sleep, however whether they are directly involved in the functions of sleep, or are mere epiphenomena, is not yet fully understood. To disentangle the causality of these relationships, experiments utilizing techniques to detect and manipulate sleep oscillations in real-time are essential. In this review, we first overview the theoretical principles of closed-loop auditory stimulation (CLAS) as a method to study the role of slow oscillations in the functions of sleep. We then describe technical guidelines and best practices to perform CLAS and analyze results from such experiments. We further provide an overview of how CLAS has been used to investigate the causal role of slow oscillations in various sleep functions. We close by discussing important caveats, open questions, and potential topics for future research.

How we sleep: From brain states to processes

All our lives, we alternate between wakefulness and sleep with direct consequences on our ability to interact with our environment, the dynamics and contents of our subjective experience, and our brain activity. Consequently, sleep has been extensively characterised in terms of behavioural, phenomenological, and physiological changes, the latter constituting the gold standard of sleep research. The common view is thus that sleep represents a collection of discrete states with distinct neurophysiological signatures. However, recent findings challenge such a monolithic view of sleep. Indeed, there can be sharp discrepancies in time and space in the activity displayed by different brain regions or networks, making it difficult to assign a global vigilance state to such a mosaic of contrasted dynamics. Viewing sleep as a multidimensional continuum rather than a succession of non-overlapping and mutually exclusive states could account for these local aspects of sleep. Moving away from the focus on sleep states, sleep can also be investigated through the brain processes that are present in sleep, if not necessarily specific to sleep. This focus on processes rather than states allows to see sleep for what it does rather than what it is, avoiding some of the limitations of the state perspective and providing a powerful heuristic to understand sleep. Indeed, what is sleep if not a process itself that makes up wake up every morning with a brain cleaner, leaner and less cluttered.

Prefrontal cortical regulation of REM sleep

Rapid eye movement (REM) sleep is accompanied by intense cortical activity, underlying its wake-like electroencephalogram. The neural activity inducing REM sleep is thought to originate from subcortical circuits in brainstem and hypothalamus. However, whether cortical neurons can also trigger REM sleep has remained unknown. Here we show in mice that the medial prefrontal cortex (mPFC) strongly promotes REM sleep. Bidirectional optogenetic manipulations demonstrate that excitatory mPFC neurons promote REM sleep through their projections to the lateral hypothalamus and regulate phasic events, reflected in accelerated electroencephalogram theta oscillations and increased eye movement density during REM sleep. Calcium imaging reveals that the majority of lateral hypothalamus-projecting mPFC neurons are maximally activated during REM sleep and a subpopulation is recruited during phasic theta accelerations. Our results delineate a cortico-hypothalamic circuit for the top-down control of REM sleep and identify a critical role of the mPFC in regulating phasic events during REM sleep.

U-shaped association between sleep duration and urgency urinary incontinence in women: a cross-sectional study

BACKGROUND

To investigate the association between sleep duration and urgency urinary incontinence (UUI) among adult women.

METHODS

Cross-sectional data were retrieved from the 2005-2014 National Health and Nutrition Examination Survey. To explore the association between sleep duration and urgency urinary incontinence, multivariable logistic regression and restricted cubic spline (RCS) regression analysis was carried out.

RESULTS

Among 9204 adult women, the weighted urinary incontinence prevalence was  31% for urgency urinary incontinence (UUI). The fully adjusted multivariable model revealed that participants with short (< 7 h) or long (> 9 h) sleep duration were more likely to report UUI compared to participants with normal (7-9 h) sleep duration (OR 1.20, 95% CI 1.03-1.40, p = 0.02, OR 1.40, 95% CI 1.11-1.76, p = 0.005, respectively). Subgroup analysis showed no significant interaction. Furthermore, additional analysis demonstrated a U-shaped correlation between sleep duration and incident UUI.

CONCLUSION

The non-linear association exists between sleep duration and urgency urinary incontinence. Compared with insufficient or excessive sleep, normal sleep duration is related to lower prevalence of urgency urinary incontinence. Future prospective longitudinal studies should be conducted to further investigate and determine the degree of the association between sleep time and urgent urinary incontinence.

The neurophysiologic landscape of the sleep onset: a systematic review

Background

The sleep onset process is an ill-defined complex process of transition from wakefulness to sleep, characterized by progressive modifications at the subjective, behavioural, cognitive, and physiological levels. To this date, there is no international consensus which could aid a principled characterisation of this process for clinical research purposes. The current review aims to systemise the current knowledge about the underlying mechanisms of the natural heterogeneity of this process.

Methods

In this systematic review, studies investigating the process of the sleep onset from 1970 to 2022 were identified using electronic database searches of PsychINFO, MEDLINE, and Embase.

Results

A total of 139 studies were included; 110 studies in healthy participants and 29 studies in participants with sleep disorders. Overall, there is a limited consensus across a body of research about what distinct biomarkers of the sleep onset constitute. Only sparse data exists on the physiology, neurophysiology and behavioural mechanisms of the sleep onset, with majority of studies concentrating on the non-rapid eye movement stage 2 (NREM 2) as a potentially better defined and a more reliable time point that separates sleep from the wake, on the sleep wake continuum.

Conclusions

The neurophysiologic landscape of sleep onset bears a complex pattern associated with a multitude of behavioural and physiological markers and remains poorly understood. The methodological variation and a heterogenous definition of the wake-sleep transition in various studies to date is understandable, given that sleep onset is a process that has fluctuating and ill-defined boundaries. Nonetheless, the principled characterisation of the sleep onset process is needed which will allow for a greater conceptualisation of the mechanisms underlying this process, further influencing the efficacy of current treatments for sleep disorders.

Sleep-related motor skill consolidation and generalizability after physical practice, motor imagery, and action observation

Sleep benefits the consolidation of motor skills learned by physical practice, mainly through periodic thalamocortical sleep spindle activity. However, motor skills can be learned without overt movement through motor imagery or action observation. Here, we investigated whether sleep spindle activity also supports the consolidation of non-physically learned movements. Forty-five electroencephalographic sleep recordings were collected during a daytime nap after motor sequence learning by physical practice, motor imagery, or action observation. Our findings reveal that a temporal cluster-based organization of sleep spindles underlies motor memory consolidation in all groups, albeit with distinct behavioral outcomes. A daytime nap offers an early sleep window promoting the retention of motor skills learned by physical practice and motor imagery, and its generalizability toward the inter-manual transfer of skill after action observation. Findings may further have practical impacts with the development of non-physical rehabilitation interventions for patients having to remaster skills following peripherical or brain injury.

The temporal structure of REM sleep shows minute-scale fluctuations across brain and body in mice and humans

Rapid eye movement sleep (REM) is believed to have a binary temporal structure with "phasic" and "tonic" microstates, characterized by motoric activity versus quiescence, respectively. However, we observed in mice that the frequency of theta activity (a marker of rodent REM) fluctuates in a nonbinary fashion, with the extremes of that fluctuation correlating with phasic-type and tonic-type facial motricity. Thus, phasic and tonic REM may instead represent ends of a continuum. These cycles of brain physiology and facial movement occurred at 0.01 to 0.06 Hz, or infraslow frequencies, and affected cross-frequency coupling and neuronal activity in the neocortex, suggesting network functional impact. We then analyzed human data and observed that humans also demonstrate nonbinary phasic/tonic microstates, with continuous 0.01 to 0.04-Hz respiratory rate cycles matching the incidence of eye movements. These fundamental properties of REM can yield insights into our understanding of sleep health.

Sleep disturbances in autism spectrum disorder: Animal models, neural mechanisms, and therapeutics

Sleep is crucial for brain development. Sleep disturbances are prevalent in children with autism spectrum disorder (ASD). Strikingly, these sleep problems are positively correlated with the severity of ASD core symptoms such as deficits in social skills and stereotypic behavior, indicating that sleep problems and the behavioral characteristics of ASD may be related. In this review, we will discuss sleep disturbances in children with ASD and highlight mouse models to study sleep disturbances and behavioral phenotypes in ASD. In addition, we will review neuromodulators controlling sleep and wakefulness and how these neuromodulatory systems are disrupted in animal models and patients with ASD. Lastly, we will address how the therapeutic interventions for patients with ASD improve various aspects of sleep. Together, gaining mechanistic insights into the neural mechanisms underlying sleep disturbances in children with ASD will help us to develop better therapeutic interventions.

Sleep-A brain-state serving systems memory consolidation

Although long-term memory consolidation is supported by sleep, it is unclear how it differs from that during wakefulness. Our review, focusing on recent advances in the field, identifies the repeated replay of neuronal firing patterns as a basic mechanism triggering consolidation during sleep and wakefulness. During sleep, memory replay occurs during slow-wave sleep (SWS) in hippocampal assemblies together with ripples, thalamic spindles, neocortical slow oscillations, and noradrenergic activity. Here, hippocampal replay likely favors the transformation of hippocampus-dependent episodic memory into schema-like neocortical memory. REM sleep following SWS might balance local synaptic rescaling accompanying memory transformation with a sleep-dependent homeostatic process of global synaptic renormalization. Sleep-dependent memory transformation is intensified during early development despite the immaturity of the hippocampus. Overall, beyond its greater efficacy, sleep consolidation differs from wake consolidation mainly in that it is supported, rather than impaired, by spontaneous hippocampal replay activity possibly gating memory formation in neocortex.

How our understanding of memory replay evolves

Memory reactivations and replay, widely reported in the hippocampus and cortex across species, have been implicated in memory consolidation, planning, and spatial and skill learning. Technological advances in electrophysiology, calcium imaging, and human neuroimaging techniques have enabled neuroscientists to measure large-scale neural activity with increasing spatiotemporal resolution and have provided opportunities for developing robust analytic methods to identify memory replay. In this article, we first review a large body of historically important and representative memory replay studies from the animal and human literature. We then discuss our current understanding of memory replay functions in learning, planning, and memory consolidation and further discuss the progress in computational modeling that has contributed to these improvements. Next, we review past and present analytic methods for replay analyses and discuss their limitations and challenges. Finally, looking ahead, we discuss some promising analytic methods for detecting nonstereotypical, behaviorally nondecodable structures from large-scale neural recordings. We argue that seamless integration of multisite recordings, real-time replay decoding, and closed-loop manipulation experiments will be essential for delineating the role of memory replay in a wide range of cognitive and motor functions.

Assessment of Cognitive Function with Sleep Spindle Characteristics in Adults with Epilepsy

Objective

Epilepsy may cause chronic cognitive impairment by disturbing sleep plasticity. Sleep spindles play a crucial role in sleep maintenance and brain plasticity. This study explored the relationship between cognition and spindle characteristics in adult epilepsy.

Methods

Participants underwent one-night sleep electroencephalogram recording and neuropsychological tests on the same day. Spindle characteristics during N2 sleep were extracted using a learning-based system for sleep staging and an automated spindle detection algorithm. We investigated the difference between cognitive subgroups in spindle characteristics. Multiple linear regressions were applied to analyze associations between cognition and spindle characteristics.

Results

Compared with no/mild cognitive impairment, epilepsy patients who developed severe cognitive impairment had lower sleep spindle density, the differences mainly distributed in central, occipital, parietal, middle temporal, and posterior temporal (P < 0.05), and had relatively long spindle duration in occipital and posterior temporal (P < 0.05). Mini-Mental State Examination (MMSE) was associated with spindle density (pars triangularis of the inferior frontal gyrus (IFGtri): β = 0.253, P = 0.015, and P.adjust = 0.074) and spindle duration (IFGtri: β = -0.262, P = 0.004, and P.adjust = 0.030). Montreal Cognitive Assessment (MoCA) was associated with spindle duration (IFGtri: β = -0.246, P = 0.010, and P.adjust = 0.055). Executive Index Score (MoCA-EIS) was associated with spindle density (IFGtri: β = 0.238, P = 0.019, and P.adjust = 0.087; parietal: β = 0.227, P = 0.017, and P.adjust = 0.082) and spindle duration (parietal: β = -0.230, P = 0.013, and P.adjust = 0.065). Attention Index Score (MoCA-AIS) was associated with spindle duration (IFGtri: β = -0.233, P = 0.017, and P.adjust = 0.081).

Conclusions

The findings suggested that the altered spindle activity in epilepsy with severe cognitive impairment, the associations between the global cognitive status of adult epilepsy and spindle characteristics, and specific cognitive domains may relate to spindle characteristics in particular brain regions.

Association between sleep duration and kidney stones in 34 190 American adults: A cross-sectional analysis of NHANES 2007-2018

OBJECTIVE

To explore the association between sleep duration and kidney stones among United States adults.

PARTICIPANTS AND METHODS

This cross-sectional study is based on National Health and Nutrition Examination Surveys (NHANES) 2007-2018. Participants aged 20 years and above who self-reported history of kidney stones and sleep duration were included. Weighted proportions, multivariable analysis, and piecewise linear regression were used to evaluate the associations between sleep duration and kidney stones, while adjusting for gender, age, race, poverty income ratio, body mass index, education, marital status, trouble sleeping, smoking, alcohol and some comorbidities. Stratified logistic regression models were used in subgroup analyses and included all potential confounding factors above.

RESULTS

Of the 34,190 participants, the overall weighted kidney stone prevalence was 9.73%, weighted mean age was 47.67 ± 16.99 years, and mean sleep duration was 7.15 ± 1.44 hours. The fully adjusted multivariable model demonstrated that people with normal (7-9 hours) and long (>9 hours) sleep duration had 17% and 20% lower odds of kidney stone prevalence than people with short sleep duration (<7 hours), respectively. However, fitting a smooth curve showed a nonlinear association between sleep duration and kidney stones. A piecewise linear regression model showed that one hour longer sleep duration was associated with 7% lower kidney stone prevalence for people with short sleep duration and with 22% higher prevalence for participants with long sleep duration. However, for people with normal sleep duration, increasing sleep duration was nonsignificantly associated with lower prevalence of kidney stones. Subgroup analysis showed no significant interaction effects.

CONCLUSIONS

There is a curvilinear relationship between sleep duration and kidney stones. Normal sleep duration is associated with lower prevalence of kidney stones than short sleep duration. This study provides new insight into potential strategies for the prevention and treatment of kidney stones.

REM sleep is associated with distinct global cortical dynamics and controlled by occipital cortex

The cerebral cortex is spontaneously active during sleep, yet it is unclear how this global cortical activity is spatiotemporally organized, and whether such activity not only reflects sleep states but also contributes to sleep state switching. Here we report that cortex-wide calcium imaging in mice revealed distinct sleep stage-dependent spatiotemporal patterns of global cortical activity, and modulation of such patterns could regulate sleep state switching. In particular, elevated activation in the occipital cortical regions (including the retrosplenial cortex and visual areas) became dominant during rapid-eye-movement (REM) sleep. Furthermore, such pontogeniculooccipital (PGO) wave-like activity was associated with transitions to REM sleep, and optogenetic inhibition of occipital activity strongly promoted deep sleep by suppressing the NREM-to-REM transition. Thus, whereas subcortical networks are critical for initiating and maintaining sleep and wakefulness states, distinct global cortical activity also plays an active role in controlling sleep states.

A noradrenergic-hypothalamic neural substrate for stress-induced sleep disturbances

In our daily life, we are exposed to uncontrollable and stressful events that disrupt our sleep. However, the underlying neural mechanisms deteriorating the quality of non-rapid eye movement sleep (NREMs) and REM sleep are largely unknown. Here, we show in mice that acute psychosocial stress disrupts sleep by increasing brief arousals (microarousals [MAs]), reducing sleep spindles, and impairing infraslow oscillations in the spindle band of the electroencephalogram during NREMs, while reducing REMs. This poor sleep quality was reflected in an increased number of calcium transients in the activity of noradrenergic (NE) neurons in the locus coeruleus (LC) during NREMs. Opto- and chemogenetic LC-NE activation in naïve mice is sufficient to change the sleep microarchitecture similar to stress. Conversely, chemogenetically inhibiting LC-NE neurons reduced MAs during NREMs and normalized their number after stress. Specifically inhibiting LC-NE neurons projecting to the preoptic area of the hypothalamus (POA) decreased MAs and enhanced spindles and REMs after stress. Optrode recordings revealed that stimulating LC-NE fibers in the POA indeed suppressed the spiking activity of POA neurons that are activated during sleep spindles and REMs and inactivated during MAs. Our findings reveal that changes in the dynamics of the stress-regulatory LC-NE neurons during sleep negatively affect sleep quality, partially through their interaction with the POA.

The sleep EEG envelope is a novel, neuronal firing-based human biomarker

Sleep EEG reflects voltage differences relative to a reference, while its spectrum reflects its composition of various frequencies. In contrast, the envelope of the sleep EEG reflects the instantaneous amplitude of oscillations, while its spectrum reflects the rhythmicity of the occurrence of these oscillations. The sleep EEG spectrum is known to relate to demographic, psychological and clinical characteristics, but the envelope spectrum has been rarely studied. In study 1, we demonstrate in human invasive data from cortex-penetrating microelectrodes and subdural grids that the sleep EEG envelope spectrum reflects neuronal firing. In study 2, we demonstrate that the scalp EEG envelope spectrum is stable within individuals. A multivariate learning algorithm could predict age (r = 0.6) and sex (r = 0.5) from the EEG envelope spectrum. With age, oscillations shifted from a 4-5 s rhythm to faster rhythms. Our results demonstrate that the sleep envelope spectrum is a promising biomarker of demographic and disease-related phenotypes.

Understanding the roles of central and autonomic activity during sleep in the improvement of working memory and episodic memory

The last decade has seen significant progress in identifying sleep mechanisms that support cognition. Most of these studies focus on the link between electrophysiological events of the central nervous system during sleep and improvements in different cognitive domains, while the dynamic shifts of the autonomic nervous system across sleep have been largely overlooked. Recent studies, however, have identified significant contributions of autonomic inputs during sleep to cognition. Yet, there remain considerable gaps in understanding how central and autonomic systems work together during sleep to facilitate cognitive improvement. In this article we examine the evidence for the independent and interactive roles of central and autonomic activities during sleep and wake in cognitive processing. We specifically focus on the prefrontal-subcortical structures supporting working memory and mechanisms underlying the formation of hippocampal-dependent episodic memory. Our Slow Oscillation Switch Model identifies separate and competing underlying mechanisms supporting the two memory domains at the synaptic, systems, and behavioral levels. We propose that sleep is a competitive arena in which both memory domains vie for limited resources, experimentally demonstrated when boosting one system leads to a functional trade-off in electrophysiological and behavioral outcomes. As these findings inevitably lead to further questions, we suggest areas of future research to better understand how the brain and body interact to support a wide range of cognitive domains during a single sleep episode.

Predictive coding, multisensory integration, and attentional control: A multicomponent framework for lucid dreaming

Lucid dreaming (LD) is a mental state in which we realize not being awake but are dreaming while asleep. It often involves vivid, perceptually intense dream images as well as peculiar kinesthetic sensations, such as flying, levitating, or out-of-body experiences. LD is in the cross-spotlight of cognitive neuroscience and sleep research as a particular case to study consciousness, cognition, and the neural background of dream experiences. Here, we present a multicomponent framework for the study and understanding of neurocognitive mechanisms and phenomenological aspects of LD. We propose that LD is associated with prediction error signals arising during sleep and occurring at higher or lower levels of the processing hierarchy. Prediction errors are resolved by generating a superordinate self-model able to integrate ambiguous stimuli arriving from sensory periphery and higher-order cortical regions. While multisensory integration enables lucidity maintenance and contributes to peculiar kinesthetic experiences, attentional control facilitates multisensory integration by dynamically regulating the balance between the influence of top-down mental models and the precision weighting of bottom-up sensory inputs. Our novel framework aims to link neural correlates of LD with current concepts of sleep and arousal regulation and provide testable predictions on interindividual differences in LD as well as neurocognitive mechanisms inducing lucid dreams.

Oscillatory Population-Level Activity of Dorsal Raphe Serotonergic Neurons Is Inscribed in Sleep Structure

Dorsal raphe (DR) 5-HT neurons regulate sleep-wake transitions. Previous studies demonstrated that single-unit activity of DR 5-HT neurons is high during wakefulness, decreases during non-rapid eye movement (NREM) sleep, and ceases during rapid eye movement (REM) sleep. However, characteristics of the population-level activity of DR 5-HT neurons, which influence the entire brain, are largely unknown. Here, we measured population activities of 5-HT neurons in the male and female mouse DR across the sleep-wake cycle by ratiometric fiber photometry. We found a slow oscillatory activity of compound intracellular Ca2+ signals during NREM sleep. The trough of the concave 5-HT activity increased across sleep progression, but 5-HT activity always returned to that seen during the wake period. When the trough reached a minimum and remained there, REM sleep was initiated. We also found a unique coupling of the oscillatory 5-HT activity and wideband EEG power fluctuation. Furthermore, optogenetic activation of 5-HT neurons during NREM sleep triggered a high EMG power and induced wakefulness, demonstrating a causal role of 5-HT neuron activation. Optogenetic inhibition induced REM sleep or sustained NREM, with an EEG power increase and EEG fluctuation, and pharmacological silencing of 5-HT activity using a selective serotonin reuptake inhibitor led to sustained NREM, with an EEG power decrease and EEG fluctuation. These inhibitory manipulations supported the association between oscillatory 5-HT activity and EEG fluctuation. We propose that NREM sleep is not a monotonous state, but rather it contains dynamic changes that coincide with the oscillatory population-level activity of DR 5-HT neurons.SIGNIFICANCE STATEMENT Previous studies have demonstrated single-cell 5-HT neuronal activity across sleep-wake conditions. However, population-level activities of these neurons are not well understood. We monitored DR 5-HT population activity using a fiber photometry system in mice and found that activity was highest during wakefulness and lowest during REM sleep. Surprisingly, during non-REM sleep, the 5-HT population activity decreased with an oscillatory pattern, coinciding with EEG fluctuations. EEG fluctuations persisted when DR 5-HT neuron activity was silenced by either optogenetic or pharmacological interventions during non-REM sleep, suggesting an association between the two. Although oscillatory DR 5-HT neuron activity did not generate EEG fluctuations, it provides evidence that non-REM sleep exhibits at least binary states.

Memory-enhancing properties of sleep depend on the oscillatory amplitude of norepinephrine

Sleep has a complex micro-architecture, encompassing micro-arousals, sleep spindles and transitions between sleep stages. Fragmented sleep impairs memory consolidation, whereas spindle-rich and delta-rich non-rapid eye movement (NREM) sleep and rapid eye movement (REM) sleep promote it. However, the relationship between micro-arousals and memory-promoting aspects of sleep remains unclear. In this study, we used fiber photometry in mice to examine how release of the arousal mediator norepinephrine (NE) shapes sleep micro-architecture. Here we show that micro-arousals are generated in a periodic pattern during NREM sleep, riding on the peak of locus-coeruleus-generated infraslow oscillations of extracellular NE, whereas descending phases of NE oscillations drive spindles. The amplitude of NE oscillations is crucial for shaping sleep micro-architecture related to memory performance: prolonged descent of NE promotes spindle-enriched intermediate state and REM sleep but also associates with awakenings, whereas shorter NE descents uphold NREM sleep and micro-arousals. Thus, the NE oscillatory amplitude may be a target for improving sleep in sleep disorders.

Unconscious mind activates central cardiovascular network and promotes adaptation to microgravity possibly anti-aging during 1-year-long spaceflight

The intrinsic cardiovascular regulatory system (β, 0.00013–0.02 Hz) did not adapt to microgravity after a 6-month spaceflight. The infraslow oscillation (ISO, 0.01–0.10 Hz) coordinating brain dynamics via thalamic astrocytes plays a key role in the adaptation to novel environments. We investigate the adaptive process of a healthy astronaut during a 12-month-long spaceflight by analyzing heart rate variability (HRV) in the LF (0.01–0.05 Hz) and MF1 (0.05–0.10 Hz) bands for two consecutive days on four occasions: before launch, at 1-month (ISS01) and 11-month (ISS02) in space, and after return to Earth. Alteration of β during ISS01 improved during ISS02 (P = 0.0167). During ISS01, LF and MF1 bands, reflecting default mode network (DMN) activity, started to increase at night (by 43.1% and 32.0%, respectively), when suprachiasmatic astrocytes are most active, followed by a 25.9% increase in MF1-band throughout the entire day during ISS02, larger at night (47.4%) than during daytime. Magnetic declination correlated positively with β during ISS01 (r = 0.6706, P < 0.0001) and ISS02 (r = 0.3958, P = 0.0095). Magnetic fluctuations may affect suprachiasmatic astrocytes, and the DMN involving ISOs and thalamic astrocytes may then be activated, first at night, then during the entire day, a mechanism that could perhaps promote an anti-aging effect noted in other investigations.

Association Between Sleep Microstructure and Incident Hypertension in a Population‐Based Sample: The HypnoLaus Study

Background

Poor sleep quality is associated with increased incident hypertension. However, few studies have investigated the impact of objective sleep structure parameters on hypertension. This study investigated the association between sleep macrostructural and microstructural parameters and incident hypertension in a middle‐ to older‐aged sample.

Methods and Results

Participants from the HypnoLaus population‐based cohort without hypertension at baseline were included. Participants had at‐home polysomnography at baseline, allowing assessment of sleep macrostructure (nonrapid eye movement sleep stages 1, 2, and 3; rapid eye movement sleep stages; and total sleep time) and microstructure including power spectral density of electroencephalogram in nonrapid eye movement sleep and spindles characteristics (density, duration, frequency, amplitude) in nonrapid eye movement sleep stage 2. Associations between sleep macrostructure and microstructure parameters at baseline and incident clinical hypertension over a mean follow‐up of 5.2 years were assessed with multiple‐adjusted logistic regression. A total of 1172 participants (42% men; age 55±10 years) were included. Of these, 198 (17%) developed hypertension. After adjustment for confounders, no sleep macrostructure features were associated with incident hypertension. However, low absolute delta and sigma power were significantly associated with incident hypertension where participants in the lowest quartile of delta and sigma had a 1.69‐fold (95% CI, 1.00–2.89) and 1.72‐fold (95% CI, 1.05–2.82) increased risk of incident hypertension, respectively, versus those in the highest quartile. Lower spindle density (odds ratio, 0.87; 95% CI, 0.76–0.99) and amplitude (odds ratio, 0.98; 95% CI, 0.95–1.00) were also associated with higher incident hypertension.

Conclusions

Sleep microstructure is associated with incident hypertension. Slow‐wave activity and sleep spindles, 2 hallmarks of objective sleep continuity and quality, were inversely and consistently associated with incident hypertension. This supports the protective role of sleep continuity in the development of hypertension.