Enhancement of sleep slow waves: underlying mechanisms and practical consequences

Protocol to fabricate a self-adhesive and long-term stable hydrogel for sleep EEG recording

Long-term continuous electroencephalogram (EEG) monitoring is crucial for neuroengineering but suffers from hardware limitations. Here, we present a protocol for EEG recording using a long-term stable and reagent-free-cross-linked hydrogel with configurable mechanical and adhesive properties. We describe steps for fabricating the hydrogel and performing material characterizations and stability tests. We detail procedures for setting up the EEG recording configuration and data analysis. This protocol can facilitate EEG recording experiments with the hydrogel, as well as other novel materials and devices. For complete details on the use and execution of this protocol, please refer to Hsieh et al.1.

Consciousness and sleep

Sleep is a universal, essential biological process. It is also an invaluable window on consciousness. It tells us that consciousness can be lost but also that it can be regained, in all its richness, when we are disconnected from the environment and unable to reflect. By considering the neurophysiological differences between dreaming and dreamless sleep, we can learn about the substrate of consciousness and understand why it vanishes. We also learn that the ongoing state of the substrate of consciousness determines the way each experience feels regardless of how it is triggered-endogenously or exogenously. Dreaming consciousness is also a window on sleep and its functions. Dreams tell us that the sleeping brain is remarkably lively, recombining intrinsic activation patterns from a vast repertoire, freed from the requirements of ongoing behavior and cognitive control.

A classification-based generative approach to selective targeting of global slow oscillations during sleep

Background

Given sleep's crucial role in health and cognition, numerous sleep-based brain interventions are being developed, aiming to enhance cognitive function, particularly memory consolidation, by improving sleep. Research has shown that Transcranial Alternating Current Stimulation (tACS) during sleep can enhance memory performance, especially when used in a closed-loop (cl-tACS) mode that coordinates with sleep slow oscillations (SOs, 0.5-1.5Hz). However, sleep tACS research is characterized by mixed results across individuals, which are often attributed to individual variability.

Objective/Hypothesis

This study targets a specific type of SOs, widespread on the electrode manifold in a short delay ("global SOs"), due to their close relationship with long-term memory consolidation. We propose a model-based approach to optimize cl-tACS paradigms, targeting global SOs not only by considering their temporal properties but also their spatial profile.

Methods

We introduce selective targeting of global SOs using a classification-based approach. We first estimate the current elicited by various stimulation paradigms, and optimize parameters to match currents found in natural sleep during a global SO. Then, we employ an ensemble classifier trained on sleep data to identify effective paradigms. Finally, the best stimulation protocol is determined based on classification performance.

Results

Our study introduces a model-driven cl-tACS approach that specifically targets global SOs, with the potential to extend to other brain dynamics. This method establishes a connection between brain dynamics and stimulation optimization.

Conclusion

Our research presents a novel approach to optimize cl-tACS during sleep, with a focus on targeting global SOs. This approach holds promise for improving cl-tACS not only for global SOs but also for other physiological events, benefiting both research and clinical applications in sleep and cognition.

The neurophysiology of closed-loop auditory stimulation in sleep: A magnetoencephalography study

Closed-loop auditory stimulation (CLAS) is a brain modulation technique in which sounds are timed to enhance or disrupt endogenous neurophysiological events. CLAS of slow oscillation up-states in sleep is becoming a popular tool to study and enhance sleep's functions, as it increases slow oscillations, evokes sleep spindles and enhances memory consolidation of certain tasks. However, few studies have examined the specific neurophysiological mechanisms involved in CLAS, in part because of practical limitations to available tools. To evaluate evidence for possible models of how sound stimulation during brain up-states alters brain activity, we simultaneously recorded electro- and magnetoencephalography in human participants who received auditory stimulation across sleep stages. We conducted a series of analyses that test different models of pathways through which CLAS of slow oscillations may affect widespread neural activity that have been suggested in literature, using spatial information, timing and phase relationships in the source-localized magnetoencephalography data. The results suggest that auditory information reaches ventral frontal lobe areas via non-lemniscal pathways. From there, a slow oscillation is created and propagated. We demonstrate that while the state of excitability of tissue in auditory cortex and frontal ventral regions shows some synchrony with the electroencephalography (EEG)-recorded up-states that are commonly used for CLAS, it is the state of ventral frontal regions that is most critical for slow oscillation generation. Our findings advance models of how CLAS leads to enhancement of slow oscillations, sleep spindles and associated cognitive benefits and offer insight into how the effectiveness of brain stimulation techniques can be improved.

Wake slow waves in focal human epilepsy impact network activity and cognition

Slow waves of neuronal activity are a fundamental component of sleep that are proposed to have homeostatic and restorative functions. Despite this, their interaction with pathology is unclear and there is only indirect evidence of their presence during wakefulness. Using intracortical recordings from the temporal lobe of 25 patients with epilepsy, we demonstrate the existence of local wake slow waves (LoWS) with key features of sleep slow waves, including a down-state of neuronal firing. Consistent with a reduction in neuronal activity, LoWS were associated with slowed cognitive processing. However, we also found that LoWS showed signatures of a homeostatic relationship with interictal epileptiform discharges (IEDs): exhibiting progressive adaptation during the build-up of network excitability before an IED and reducing the impact of subsequent IEDs on network excitability. We therefore propose an epilepsy homeostasis hypothesis: that slow waves in epilepsy reduce aberrant activity at the price of transient cognitive impairment.

A system based on machine learning for improving sleep

Closed-loop auditory stimulation is one of the well-known and emerging sensory stimulation techniques, which achieves the purpose of sleep regulation by driving the EEG slow oscillation (SO, <1 Hz) through auditory stimulation. The main challenge is to accurately identify the stimulation timing and provide feedback in real-time, which has high requirements on the response time and recognition accuracy of the closed-loop auditory stimulation system. To reduce the impact of systematic errors on the regulation results, most traditional closed-loop auditory stimulation systems try to identify a single feature to determine the timing of stimulus delivery and reduce the system feedback delay by simplifying the calculation. Unlike existing closed-loop regulation systems that identify specific brain features, this paper proposes a closed-loop auditory stimulation sleep regulation system deploying machine learning. The process is: through online sleep real-time automatic staging, tracking the sleep stage to provide feedback quickly, and continuously offering external auditory stimulation at a specific SO phase. This paper uses this system to conduct sleep auditory stimulation regulation experiments on ten subjects. The experimental results show that the sleep closed-loop regulation system proposed in this paper can achieve consistency (effective for almost all subjects in the experiment) and immediate (taking effect immediately after stimulation) modulation effects on SOs. More importantly, the proposed method is superior to existing advanced methods. Therefore, the system designed in this paper has great potential to be more reliable and flexible in sleep regulation.

Dawn of a New Dawn: Advances in Sleep Health to Optimize Performance

Optimal sleep health is a critical component to high-level performance. In populations such as the military, public service (eg, firefighters), and health care, achieving optimal sleep health is difficult and subsequently deficiencies in sleep health may lead to performance decrements. However, advances in sleep monitoring technologies and mitigation strategies for poor sleep health show promise for further ecological scientific investigation within these populations. The current review briefly outlines the relationship between sleep health and performance as well as current advances in behavioral and technological approaches to improving sleep health for performance.

Micro SleepNet: efficient deep learning model for mobile terminal real-time sleep staging

The real-time sleep staging algorithm that can perform inference on mobile devices without burden is a prerequisite for closed-loop sleep modulation. However, current deep learning sleep staging models have poor real-time efficiency and redundant parameters. We propose a lightweight and high-performance sleep staging model named Micro SleepNet, which takes a 30-s electroencephalography (EEG) epoch as input, without relying on contextual signals. The model features a one-dimensional group convolution with a kernel size of 1 × 3 and an Efficient Channel and Spatial Attention (ECSA) module for feature extraction and adaptive recalibration. Moreover, the model efficiently performs feature fusion using dilated convolution module and replaces the conventional fully connected layer with Global Average Pooling (GAP). These design choices significantly reduce the total number of model parameters to 48,226, with only approximately 48.95 Million Floating-point Operations per Second (MFLOPs) computation. The proposed model is conducted subject-independent cross-validation on three publicly available datasets, achieving an overall accuracy of up to 83.3%, and the Cohen Kappa is 0.77. Additionally, we introduce Class Activation Mapping (CAM) to visualize the model's attention to EEG waveforms, which demonstrate the model's ability to accurately capture feature waveforms of EEG at different sleep stages. This provides a strong interpretability foundation for practical applications. Furthermore, the Micro SleepNet model occupies approximately 100 KB of memory on the Android smartphone and takes only 2.8 ms to infer one EEG epoch, meeting the real-time requirements of sleep staging tasks on mobile devices. Consequently, our proposed model has the potential to serve as a foundation for accurate closed-loop sleep modulation.

Reduced slow-wave activity and autonomic dysfunction during sleep precede cognitive deficits in Alzheimer's disease transgenic mice

Occurrence of amyloid-β (Aβ) aggregation in brain begins before the clinical onset of Alzheimer's disease (AD), as preclinical AD. Studies have reported that sleep problems and autonomic dysfunction associate closely with AD. However, whether they, especially the interaction between sleep and autonomic function, play critical roles in preclinical AD are unclear. Therefore, we investigated how sleep patterns and autonomic regulation at different sleep-wake stages changed and whether they were related to cognitive performance in pathogenesis of AD mice. Polysomnographic recordings in freely-moving APP/PS1 and wild-type (WT) littermates were collected to study sleep patterns and autonomic function at 4 (early disease stage) and 8 months of age (advanced disease stage), cognitive tasks including novel object recognition and Morris water maze were performed, and Aβ levels in brain were measured. APP/PS1 mice at early stage of AD pathology with Aβ aggregation but without significant differences in cognitive performance had frequent sleep-wake transitions, lower sleep-related delta power percentage, lower overall autonomic activity, and lower parasympathetic activity mainly during sleep compared with WT mice. The same phenomenon was observed in advanced-stage APP/PS1 mice with significant cognitive deficits. In mice at both disease stages, sleep-related delta power percentage correlated positively with memory performance. At early stage, memory performance correlated positively with sympathetic activity during wakefulness; at advanced stage, memory performance correlated positively with parasympathetic activity during both wakefulness and sleep. In conclusion, sleep quality and distinction between wake- and sleep-related autonomic function may be biomarkers for early AD detection.

Lateralized tactile stimulation during NREM sleep globally increases both slow and fast frequency activities

Slow frequency activity during non-rapid eye movement (NREM) sleep emerges from synchronized activity of widely distributed thalamo-cortical and cortico-cortical networks, reflecting homeostatic and restorative properties of sleep. Slow frequency activity exhibits a reactive nature, and can be increased by acoustic stimulation. Although non-invasive brain stimulation is a promising technique in basic and clinical sleep research, sensory stimulation studies focusing on modalities other than the acoustic are scarce. We explored here the potential of lateralized vibro-tactile stimulation (VTS) of the finger to locally modify electroencephalographic activity during nocturnal NREM sleep. Eight seconds-long sequences of vibro-tactile pulses were delivered at a rate of 1 Hz either to the left or to the right index finger, in addition to a sham condition, in fourteen healthy participants. VTS markedly increased slow frequency activity that peaked between 1-4 Hz but extended to higher (~13 Hz) frequencies, with fronto-central dominance. Enhanced slow frequency activity was accompanied by increased (14-22 Hz) fast frequency power peaking over central and posterior locations. VTS increased the amplitude of slow waves, especially during the first 3-4 s of stimulation. Noticeably, we did not observe local-hemispheric effects, that is, VTS resulted in a global cortical response regardless of stimulation laterality. VTS moderately increased slow and fast frequency activities in resting wakefulness, to a much lower extent compared to NREM sleep. The concomitant increase in slow and fast frequency activities in response to VTS indicates an instant homeostatic response coupled with wake-like, high-frequency activity potentially reflecting transient periods of increased environmental processing.

Sleep Disorders, Comorbidities, Actions, Lower Urinary Tract Dysfunction, and Medications ("Sleep C.A.L.M.") in the evaluation and management of nocturia: A simple approach to a complex diagnosis

INTRODUCTION

Nocturia arises from a fundamental mismatch between nocturnal urine production, storage capacity, and sleep architecture, which may be driven by abnormalities of the genitourinary tract, but also by sleep disorders, medical diseases, patient actions/lifestyle factors, or medications. This article introduces a novel system for organizing the complex differential diagnosis for nocturia, as proposed by an international collective of practicing urologists, physician specialists, and sleep experts: "Sleep CALM"-Sleep Disorders, Comorbidities, Actions, Lower Urinary Tract Dysfunction, and Medications.

METHODS

Narrative review of current evidence regarding the relevance of each "Sleep CALM" factor to nocturia pathogenesis, evaluation, and management.

RESULTS

Nocturia and sleep disorders are highly intertwined and often bidirectional, such that nocturnal awakenings for reasons other than a sensation of bladder fullness should not be used as grounds for exclusion from nocturia treatment, but rather leveraged to broaden therapeutic options for nocturia. Nocturia is an important potential harbinger of several serious medical conditions beyond the genitourinary tract. Urologists should have a low threshold for primary care and medical specialty referral for medical optimization, which carries the potential to significantly improve nocturnal voiding frequency in addition to overall health status. Adverse patient actions/lifestyle factors, lower urinary tract dysfunction, and medication use commonly coexist with disordered sleep and comorbid medical conditions, and may be the primary mediators of nocturia severity and treatment response, or further exacerbate nocturia severity and complicate treatment.

CONCLUSION

"Sleep CALM" provides a memorable and clinically relevant means by which to structure the initial patient history, physical exam, and clinical testing in accordance with current best-practice guidelines for nocturia. Although not intended as an all-encompassing diagnostic tool, the "Sleep CALM" schema may also be useful in guiding individualized ancillary testing, identifying the need for specialty referral and multidisciplinary care, and uncovering first-line treatment targets.

Many faces of sleep regulation: beyond the time of day and prior wake time

The two-process model of sleep regulation posits two main processes regulating sleep: the circadian process controlled by the circadian clock and the homeostatic process that depends on the history of sleep and wakefulness. The model has provided a dominant conceptual framework for sleep research since its publication ~ 40 years ago. The time of day and prior wake time are the primary factors affecting the circadian and homeostatic processes, respectively. However, it is critical to consider other factors influencing sleep. Since sleep is incompatible with other behaviors, it is affected by the need for essential behaviors such as eating, foraging, mating, caring for offspring, and avoiding predators. Sleep is also affected by sensory inputs, sickness, increased need for memory consolidation after learning, and other factors. Here, we review multiple factors influencing sleep and discuss recent insights into the mechanisms balancing competing needs.

Arginine-vasopressin-expressing neurons in the murine suprachiasmatic nucleus exhibit a circadian rhythm in network coherence in vivo

The suprachiasmatic nucleus (SCN) is composed of functionally distinct subpopulations of GABAergic neurons which form a neural network responsible for synchronizing most physiological and behavioral circadian rhythms in mammals. To date, little is known regarding which aspects of SCN rhythmicity are generated by individual SCN neurons, and which aspects result from neuronal interaction within a network. Here, we utilize in vivo miniaturized microscopy to measure fluorescent GCaMP-reported calcium dynamics in arginine vasopressin (AVP)-expressing neurons in the intact SCN of awake, behaving mice. We report that SCN AVP neurons exhibit periodic, slow calcium waves which we demonstrate, using in vivo electrical recordings, likely reflect burst firing. Further, we observe substantial heterogeneity of function in that AVP neurons exhibit unstable rhythms, and relatively weak rhythmicity at the population level. Network analysis reveals that correlated cellular behavior, or coherence, among neuron pairs also exhibited stochastic rhythms with about 33% of pairs rhythmic at any time. Unlike single-cell variables, coherence exhibited a strong rhythm at the population level with time of maximal coherence among AVP neuronal pairs at CT/ZT 6 and 9, coinciding with the timing of maximal neuronal activity for the SCN as a whole. These results demonstrate robust circadian variation in the coordination between stochastically rhythmic neurons and that interactions between AVP neurons in the SCN may be more influential than single-cell activity in the regulation of circadian rhythms. Furthermore, they demonstrate that cells in this circuit, like those in many other circuits, exhibit profound heterogenicity of function over time and space.

Cereset Research Standard Operating Procedures for Insomnia: A Randomized, Controlled Clinical Trial

Background

Interventions for insomnia that also address autonomic dysfunction are needed.

Objective

We evaluate Cereset Research™ Standard Operating Procedures (CR-SOP) in a pilot randomized, controlled trial. CR-SOP is a less operator-dependent, more generalizable innovation of HIRREM^®, a noninvasive, closed-loop, allostatic, acoustic stimulation neurotechnology demonstrated to improve insomnia and autonomic function.

Methods

Adults with Insomnia Severity Index (ISI) scores of ≥8 were randomized to receive ten sessions of CR-SOP, with tones linked to brainwaves (LB, intervention), or a sham condition of random tones not linked to brainwaves (NL, control). Measures were collected at enrollment and 0-14 days and 4-6 weeks post-allocated intervention. The primary outcome was differential change in ISI from baseline to 4-6 weeks post-intervention. Secondary self-report measures assessed sleep quality65 and behavioral outcomes. Ten-minute recordings of heart rate and blood pressure were collected to analyze autonomic function (heart rate variability [HRV] and baroreflex sensitivity).

Results

Of 22 randomized, 20 participants completed the allocated condition. Intention to treat analysis of change from baseline to the 4-6 week outcome demonstrated mean ISI score reduction of 4.69 points among controls (SE 1.40). In the intervention group, there was an additional 2.58 point reduction in ISI score (SE 2.13; total reduction of 7.27, P = .24). Sleep quality and some measures of autonomic function improved significantly among the intervention group compared to control.

Conclusions

This pilot study compared use of a standardized, allostatic, acoustic neurotechnology intervention with a sham, active control condition. The magnitude of change in insomnia severity was clinically relevant and similar to the findings in a prior, fully powered trial, but the differential improvement observed was not statistically significant. Significant improvements were demonstrated in sleep quality and some autonomic function measures.

High-Quality Sleep Mitigates ABCA7-Related Generalization Deficits in Healthy Older African Americans

BACKGROUND

Both sleep deficiencies and Alzheimer's disease (AD) disproportionately affect older African Americans. Genetic susceptibility to AD further compounds risk for cognitive decline in this population. Aside from APOE ɛ4, ABCA7 rs115550680 is the strongest genetic locus associated with late-onset AD in African Americans. While sleep and ABCA7 rs115550680 independently influence late-life cognitive outcomes, we know too little about the interplay between these two factors on cognitive function.

OBJECTIVE

We investigated the interaction between sleep and ABCA7 rs115550680 on hippocampal-dependent cognitive function in older African Americans.

METHODS

One-hundred fourteen cognitively healthy older African Americans were genotyped for ABCA7 risk (n = 57 carriers of risk "G" allele; n = 57 non-carriers), responded to lifestyle questionnaires, and completed a cognitive battery. Sleep was assessed via a self-reported rating of sleep quality (poor, average, good). Covariates included age and years of education.

RESULTS

Using ANCOVA, we found that carriers of the risk genotype who reported poor or average sleep quality demonstrated significantly poorer generalization of prior learning-a cognitive marker of AD-compared to their non-risk counterparts. Conversely, there was no genotype-related difference in generalization performance in individuals who reported good sleep quality.

CONCLUSION

These results indicate that sleep quality may be neuroprotective against genetic risk for AD. Future studies employing more rigorous methodology should investigate the mechanistic role of sleep neurophysiology in the pathogenesis and progression of AD associated with ABCA7. There is also need for the continued development of non-invasive sleep interventions tailored to racial groups with specific AD genetic risk profiles.

Somatostatin neuron contributions to cortical slow wave dysfunction in adult mice exposed to developmental ethanol

Introduction

Transitions between sleep and waking and sleep-dependent cortical oscillations are heavily dependent on GABAergic neurons. Importantly, GABAergic neurons are especially sensitive to developmental ethanol exposure, suggesting a potential unique vulnerability of sleep circuits to early ethanol. In fact, developmental ethanol exposure can produce long-lasting impairments in sleep, including increased sleep fragmentation and decreased delta wave amplitude. Here, we assessed the efficacy of optogenetic manipulations of somatostatin (SST) GABAergic neurons in the neocortex of adult mice exposed to saline or ethanol on P7, to modulate cortical slow-wave physiology.

Methods

SST-cre × Ai32 mice, which selectively express channel rhodopsin in SST neurons, were exposed to ethanol or saline on P7. This line expressed similar developmental ethanol induced loss of SST cortical neurons and sleep impairments as C57BL/6By mice. As adults, optical fibers were implanted targeting the prefrontal cortex (PFC) and telemetry electrodes were implanted in the neocortex to monitor slow-wave activity and sleep-wake states.

Results

Optical stimulation of PFC SST neurons evoked slow-wave potentials and long-latency single-unit excitation in saline treated mice but not in ethanol mice. Closed-loop optogenetic stimulation of PFC SST neuron activation on spontaneous slow-waves enhanced cortical delta oscillations, and this manipulation was more effective in saline mice than P7 ethanol mice.

Discussion

Together, these results suggest that SST cortical neurons may contribute to slow-wave impairment after developmental ethanol.

Neuronal-spiking-based closed-loop stimulation during cortical ON- and OFF-states in freely moving mice

The slow oscillation is a central neuronal dynamic during sleep, and is generated by alternating periods of high and low neuronal activity (ON- and OFF-states). Mounting evidence causally links the slow oscillation to sleep's functions, and it has recently become possible to manipulate the slow oscillation non-invasively and phase-specifically. These developments represent promising clinical avenues, but they also highlight the importance of improving our understanding of how ON/OFF-states affect incoming stimuli and what role they play in neuronal plasticity. Most studies using closed-loop stimulation rely on the electroencephalogram and local field potential signals, which reflect neuronal ON- and OFF-states only indirectly. Here we develop an online detection algorithm based on spiking activity recorded from laminar arrays in mouse motor cortex. We find that online detection of ON- and OFF-states reflects specific phases of spontaneous local field potential slow oscillation. Our neuronal-spiking-based closed-loop procedure offers a novel opportunity for testing the functional role of slow oscillation in sleep-related restorative processes and neural plasticity.

Closed-loop modulation of local slow oscillations in human NREM sleep

Slow-wave sleep is the deep non-rapid eye-movement (NREM) sleep stage that is most relevant for the recuperative function of sleep. Its defining property is the presence of slow oscillations (<2 Hz) in the scalp electroencephalogram (EEG). Slow oscillations are generated by a synchronous back and forth between highly active UP-states and silent DOWN-states in neocortical neurons. Growing evidence suggests that closed-loop sensory stimulation targeted at UP-states of EEG-defined slow oscillations can enhance the slow oscillatory activity, increase sleep depth, and boost sleep's recuperative functions. However, several studies failed to replicate such findings. Failed replications might be due to the use of conventional closed-loop stimulation algorithms that analyze the signal from one single electrode and thereby neglect the fact that slow oscillations vary with respect to their origins, distributions, and trajectories on the scalp. In particular, conventional algorithms nonspecifically target functionally heterogeneous UP-states of distinct origins. After all, slow oscillations at distinct sites of the scalp have been associated with distinct functions. Here we present a novel EEG-based closed-loop stimulation algorithm that allows targeting UP- and DOWN-states of distinct cerebral origins based on topographic analyses of the EEG: the topographic targeting of slow oscillations (TOPOSO) algorithm. We present evidence that the TOPOSO algorithm can detect and target local slow oscillations with specific, predefined voltage maps on the scalp in real-time. When compared to a more conventional, single-channel-based approach, TOPOSO leads to fewer but locally more specific stimulations in a simulation study. In a validation study with napping participants, TOPOSO targets auditory stimulation reliably at local UP-states over frontal, sensorimotor, and centro-parietal regions. Importantly, auditory stimulation temporarily enhanced the targeted local state. However, stimulation then elicited a standard frontal slow oscillation rather than local slow oscillations. The TOPOSO algorithm is suitable for the modulation and the study of the functions of local slow oscillations.

Optimising sounds for the driving of sleep oscillations by closed-loop auditory stimulation

Recent studies have shown that slow oscillations (SOs) can be driven by rhythmic auditory stimulation, which deepens slow-wave sleep (SWS) and improves memory and the immune-supportive hormonal milieu related to this sleep stage. While different attempts have been made to optimise the driving of the SOs by changing the number of click stimulations, no study has yet investigated the impact of applying more than five clicks in a row. Likewise, the importance of the type of sounds in eliciting brain responses is presently unclear. In a study of 12 healthy young participants (10 females; aged 18-26 years), we applied an established closed-loop stimulation method, which delivered sequences of 10 pink noises, 10 pure sounds (B note of 247 Hz), 10 pronounced "a" vowels, 10 sham, 10 variable sounds, and 10 "oddball" sounds on the up phase of the endogenous SOs. By analysing area under the curve, amplitude, and event related potentials, we explored whether the nature of the sound had a differential effect on driving SOs. We showed that every stimulus in a 10-click sequence, induces a SO response. Interestingly, all three types of sounds that we tested triggered SOs. However, pink noise elicited a more pronounced response compared to the other sounds, which was explained by a broader topographical recruitment of brain areas. Our data further suggest that varying the sounds may partially counteract habituation.

Technical feasibility of using auditory phase-targeted stimulation after pediatric severe traumatic brain injury in an intensive care setting

Background

Supplementary treatment options after pediatric severe traumatic brain injury (TBI) are needed to improve neurodevelopmental outcome. Evidence suggests enhancement of brain delta waves via auditory phase-targeted stimulation might support neuronal reorganization, however, this method has never been applied in analgosedated patients on the pediatric intensive care unit (PICU). Therefore, we conducted a feasibility study to investigate this approach: In a first recording phase, we examined feasibility of recording over time and in a second stimulation phase, we applied stimulation to address tolerability and efficacy.

Methods

Pediatric patients (> 12 months of age) with severe TBI were included between May 2019 and August 2021. An electroencephalography (EEG) device capable of automatic delta wave detection and sound delivery through headphones was used to record brain activity and for stimulation (MHSL-SleepBand version 2). Stimulation tolerability was evaluated based on report of nurses, visual inspection of EEG data and clinical signals (heart rate, intracranial pressure), and whether escalation of therapy to reduce intracranial pressure was needed. Stimulation efficacy was investigated by comparing EEG power spectra of active stimulation versus muted stimulation (unpaired t-tests).

Results

In total, 4 out of 32 TBI patients admitted to the PICU (12.5%) between 4 and 15 years of age were enrolled in the study. All patients were enrolled in the recording phase and the last one also to the stimulation phase. Recordings started within 5 days after insult and lasted for 1–4 days. Overall, 23–88 h of EEG data per patient were collected. In patient 4, stimulation was enabled for 50 min: No signs of patient stress reactions were observed. Power spectrums between active and muted stimulation were not statistically different (all P > .05).

Conclusion

Results suggests good feasibility of continuously applying devices needed for auditory stimulation over multiple days in pediatric patients with TBI on PICU. Very preliminary evidence suggests good tolerability of auditory stimuli, but efficacy of auditory stimuli to enhance delta waves remains unclear and requires further investigation. However, only low numbers of severe TBI patients could be enrolled in the study and, thus, future studies should consider an international multicentre approach.

An implantable neurophysiology platform: Broadening research capabilities in free-living and non-traditional animals

Animal-borne sensors that can record and transmit data (“biologgers”) are becoming smaller and more capable at a rapid pace. Biologgers have provided enormous insight into the covert lives of many free-ranging animals by characterizing behavioral motifs, estimating energy expenditure, and tracking movement over vast distances, thereby serving both scientific and conservational endpoints. However, given that biologgers are usually attached externally, access to the brain and neurophysiological data has been largely unexplored outside of the laboratory, limiting our understanding of how the brain adapts to, interacts with, or addresses challenges of the natural world. For example, there are only a handful of studies in free-living animals examining the role of sleep, resulting in a wake-centric view of behavior despite the fact that sleep often encompasses a large portion of an animal’s day and plays a vital role in maintaining homeostasis. The growing need to understand sleep from a mechanistic viewpoint and probe its function led us to design an implantable neurophysiology platform that can record brain activity and inertial data, while utilizing a wireless link to enable a suite of forward-looking capabilities. Here, we describe our design approach and demonstrate our device’s capability in a standard laboratory rat as well as a captive fox squirrel. We also discuss the methodological and ethical implications of deploying this new class of device “into the wild” to fill outstanding knowledge gaps.

Closed-loop acoustic stimulation during an afternoon nap to modulate subsequent encoding

Sleep is able to contribute not only to memory consolidation, but also to post-sleep learning. The notion exists that either synaptic downscaling or another process during sleep increase post-sleep learning capacity. A correlation between augmentation of the sleep slow oscillation and hippocampal activation at encoding support the contribution of sleep to encoding of declarative memories. In the present study, the effect of closed-loop acoustic stimulation during an afternoon nap on post-sleep encoding of two verbal (word pairs, verbal learning and memory test) and non-verbal (figural pairs) tasks and on electroencephalogram during sleep and learning were investigated in young healthy adults (N = 16). Closed-loop acoustic stimulation enhanced slow oscillatory and spindle activity, but did not affect encoding at the group level. Subgroup analyses and comparisons with similar studies lead us to the tentative conclusion that further parameters such as time of day and subjects' cognitive ability influenced responses to closed-loop acoustic stimulation.

Brain Stimulation for Improving Sleep and Memory

Over the past few decades, the importance of sleep has become increasingly recognized for many physiologic functions, including cognition. Many studies have reported the deleterious effect of sleep loss or sleep disruption on cognitive performance. Beyond ensuring adequate sleep quality and duration, discovering methods to enhance sleep to augment its restorative effects is important to improve learning in many populations, such as the military, students, age-related cognitive decline, and cognitive disorders.

Auditory stimulation in-phase with slow oscillations to enhance overnight memory consolidation in patients with schizophrenia?

Sleep-dependent memory consolidation is disturbed in patients with schizophrenia, who furthermore show reductions in sleep spindles and probably also in delta power during sleep. The memory dysfunction in these patients is one of the strongest markers for worse long-term functional outcome. However, therapeutic interventions to normalise memory functions, e.g., with medication, still do not exist. Against this backdrop, we investigated to what extent a non-invasive approach enhancing sleep with real-time auditory stimulation in-phase with slow oscillations might affect overnight memory consolidation in patients with schizophrenia. To this end, we examined 18 patients with stably medicated schizophrenia in a double-blinded sham-controlled design. Memory performance was assessed by a verbal (word list) and a non-verbal (complex figure) declarative memory task. In comparison to a sham condition without auditory stimuli, we found that in patients with schizophrenia, auditory stimulation evokes an electrophysiological response similar to that in healthy participants leading to an increase in slow wave and temporally coupled sleep spindle activity during stimulation. Despite this finding, patients did not show any beneficial effect on the overnight change in memory performance by stimulation. Although the stimulation in our study did not improve the patient's memory, the electrophysiological response gives hope that auditory stimulation could enable us to provide better treatment for sleep-related detriments in these patients in the future.

EEG microstate dynamics indicate a U-shaped path to propofol-induced loss of consciousness

Evidence suggests that the stream of consciousness is parsed into transient brain states manifesting themselves as discrete spatiotemporal patterns of global neuronal activity. Electroencephalographical (EEG) microstates are proposed as the neurophysiological correlates of these transiently stable brain states that last for fractions of seconds. To further understand the link between EEG microstate dynamics and consciousness, we continuously recorded high-density EEG in 23 surgical patients from their awake state to unconsciousness, induced by step-wise increasing concentrations of the intravenous anesthetic propofol. Besides the conventional parameters of microstate dynamics, we introduce a new implementation of a method to estimate the complexity of microstate sequences. The brain activity under the surgical anesthesia showed a decreased sequence complexity of the stereotypical microstates, which became sparser and longer-lasting. However, we observed an initial increase in microstates' temporal dynamics and complexity with increasing depth of sedation leading to a distinctive "U-shape" that may be linked to the paradoxical excitation induced by moderate levels of propofol. Our results support the idea that the brain is in a metastable state under normal conditions, balancing between order and chaos in order to flexibly switch from one state to another. The temporal dynamics of EEG microstates indicate changes of this critical balance between stability and transition that lead to altered states of consciousness.

Interbeat interval-based sleep staging: work in progress toward real-time implementation

Objective. Cardiac activity changes during sleep enable real-time sleep staging. We developed a deep neural network (DNN) to detect sleep stages using interbeat intervals (IBIs) extracted from electrocardiogram signals.Approach. Data from healthy and apnea subjects were used for training and validation; 2 additional datasets (healthy and sleep disorders subjects) were used for testing. R-peak detection was used to determine IBIs before resampling at 2 Hz; the resulting signal was segmented into 150 s windows (30 s shift). DNN output approximated the probabilities of a window belonging to light, deep, REM, or wake stages. Cohen's Kappa, accuracy, and sensitivity/specificity per stage were determined, and Kappa was optimized using thresholds on probability ratios for each stage versus light sleep.Main results. Mean (SD) Kappa and accuracy for 4 sleep stages were 0.44 (0.09) and 0.65 (0.07), respectively, in healthy subjects. For 3 sleep stages (light+deep, REM, and wake), Kappa and accuracy were 0.52 (0.12) and 0.76 (0.07), respectively. Algorithm performance on data from subjects with REM behavior disorder or periodic limb movement disorder was significantly worse, with Kappa of 0.24 (0.09) and 0.36 (0.12), respectively. Average processing time by an ARM microprocessor for a 300-sample window was 19.2 ms.Significance. IBIs can be obtained from a variety of cardiac signals, including electrocardiogram, photoplethysmography, and ballistocardiography. The DNN algorithm presented is 3 orders of magnitude smaller compared with state-of-the-art algorithms and was developed to perform real-time, IBI-based sleep staging. With high specificity and moderate sensitivity for deep and REM sleep, small footprint, and causal processing, this algorithm may be used across different platforms to perform real-time sleep staging and direct intervention strategies.Novelty & Significance(92/100 words) This article describes the development and testing of a deep neural network-based algorithm to detect sleep stages using interbeat intervals, which can be obtained from a variety of cardiac signals including photoplethysmography, electrocardiogram, and ballistocardiography. Based on the interbeat intervals identified in electrocardiogram signals, the algorithm architecture included a group of convolution layers and a group of long short-term memory layers. With its small footprint, fast processing time, high specificity and good sensitivity for deep and REM sleep, this algorithm may provide a good option for real-time sleep staging to direct interventions.

Local slow-wave activity over the right prefrontal cortex reveals individual risk preferences

In everyday life, we have to make decisions under varying degrees of risk. Even though previous research has shown that the manipulation of sleep affects risky decision-making, it remains unknown whether individual, temporally stable neural sleep characteristics relate to individual differences in risk preferences. Here, we collected sleep data under normal conditions in fifty-four healthy adults using a portable high-density EEG at participants' home. Whole-brain corrected for multiple testing, we found that lower slow-wave activity (SWA, an indicator of sleep depth) in a cluster of electrodes over the right prefrontal cortex (PFC) is associated with higher individual risk propensity. Importantly, the association between local sleep depth and risk preferences remained significant when controlling for total sleep time and for time spent in deep sleep, i.e., sleep stages N2 and N3. Moreover, the association between risk preferences and SWA over the right PFC was very similar in all sleep cycles. Because the right PFC plays a central role in cognitive control functions, we speculate that local sleep depth in this area, as reflected by SWA, might serve as a dispositional indicator of self-regulatory ability, which in turn reflects risk preferences.

Ongoing neural oscillations predict the post-stimulus outcome of closed loop auditory stimulation during slow-wave sleep

Large slow oscillations (SO, 0.5-2 Hz) characterise slow-wave sleep and are crucial to memory consolidation and other physiological functions. Manipulating slow oscillations may enhance sleep and memory, as well as benefitting the immune system. Closed-loop auditory stimulation (CLAS) has been demonstrated to increase the SO amplitude and to boost fast sleep spindle activity (11-16 Hz). Nevertheless, not all such stimuli are effective in evoking SOs, even when they are precisely phase locked. Here, we studied what factors of the ongoing activity patterns may help to determine what oscillations to stimulate to effectively enhance SOs or SO-locked spindle activity. Hence, we trained classifiers using the morphological characteristics of the ongoing SO, as measured by electroencephalography (EEG), to predict whether stimulation would lead to a benefit in terms of the resulting SO and spindle amplitude. Separate classifiers were trained using trials from spontaneous control and stimulated datasets, and we evaluated their performance by applying them to held-out data both within and across conditions. We were able to predict both when large SOs occurred spontaneously, and whether a phase-locked auditory click effectively enlarged them with good accuracy for predicting the SO trough (∼70%) and SO peak values (∼80%). Also, we were able to predict when stimulation would elicit spindle activity with an accuracy of ∼60%. Finally, we evaluate the importance of the various SO features used to make these predictions. Our results offer new insight into SO and spindle dynamics and may suggest techniques for developing future methods for online optimization of stimulation.

Local sleep: A new concept in brain plasticity

Traditionally, sleep and wakefulness have been considered as two global, mutually exclusive states. However, this view has been challenged by the discovery that sleep and wakefulness are actually locally regulated and that islands of these two states may often coexist in the same individual. Importantly, such a local regulation seems to be the key for many essential functions of sleep, including the maintenance of cognitive efficiency and the consolidation of new skills and memories. Indeed, local changes in sleep-related oscillations occur in brain areas that are used and involved in learning during wakefulness. In turn, these changes directly modulate experience-dependent brain adaptations and the consolidation of newly acquired memories. In line with these observations, alterations in the regional balance between wake- and sleep-like activity have been shown to accompany many pathologic conditions, including psychiatric and neurologic disorders. In the last decade, experimental research has started to shed light on the mechanisms involved in the local regulation of sleep and wakefulness. The results of this research have opened new avenues of investigation regarding the function of sleep and have revealed novel potential targets for the treatment of several pathologic conditions.

Sleep Homeostasis and Night Work: A Polysomnographic Study of Daytime Sleep Following Three Consecutive Simulated Night Shifts

PURPOSE

Millions of people work at times that overlap with the habitual time for sleep. Consequently, sleep often occurs during the day. Daytime sleep is, however, characterized by reduced sleep duration. Despite preserved time spent in deep NREM sleep (stage N3), daytime sleep is subjectively rated as less restorative. Knowledge on how night work influences homeostatic sleep pressure is limited. Therefore, we aimed to explore the effect of three consecutive simulated night shifts on daytime sleep and markers of sleep homeostasis.

PATIENTS AND METHODS

We performed continuous EEG, EMG and EOG recordings in the subjects' home setting for one nighttime sleep opportunity, and for the daytime sleep opportunities following three consecutive simulated night shifts.

RESULTS

For all daytime sleep opportunities, total sleep time was reduced compared to nighttime sleep. While time spent in stage N3 was preserved, sleep pressure at sleep onset, measured by slow wave activity (1-4 Hz), was higher than nighttime sleep and higher on day 3 than on day 1 and 2. Elevated EEG power during daytime sleep was sustained through 6 h of time in bed. Slow wave energy was not significantly different from nighttime sleep after 6 h, reflecting a less efficient relief of sleep pressure.

CONCLUSION

Adaptation to daytime sleep following three consecutive simulated night shifts is limited. The increased homeostatic response and continuation of sleep pressure relief even after 6 h of sleep, are assumed to reflect a challenge for appropriate homeostatic reduction to occur.

Alterations in TRN-anterodorsal thalamocortical circuits affect sleep architecture and homeostatic processes in oxidative stress vulnerable Gclm-/- mice

Schizophrenia is associated with alterations of sensory integration, cognitive processing and both sleep architecture and sleep oscillations in mouse models and human subjects, possibly through changes in thalamocortical dynamics. Oxidative stress (OxS) damage, including inflammation and the impairment of fast-spiking gamma-aminobutyric acid neurons have been hypothesized as a potential mechanism responsible for the onset and development of schizophrenia. Yet, the link between OxS and perturbation of thalamocortical dynamics and sleep remains unclear. Here, we sought to investigate the effects of OxS on sleep regulation by characterizing the dynamics of thalamocortical networks across sleep-wake states in a mouse model with a genetic deletion of the modifier subunit of glutamate-cysteine ligase (Gclm knockout, KO) using high-density electrophysiology in freely-moving mice. We found that Gcml KO mice exhibited a fragmented sleep architecture and impaired sleep homeostasis responses as revealed by the increased NREM sleep latencies, decreased slow-wave activities and spindle rate after sleep deprivation. These changes were associated with altered bursting activity and firing dynamics of neurons from the thalamic reticularis nucleus, anterior cingulate and anterodorsal thalamus. Administration of N-acetylcysteine (NAC), a clinically relevant antioxidant, rescued the sleep fragmentation and spindle rate through a renormalization of local neuronal dynamics in Gclm KO mice. Collectively, these findings provide novel evidence for a link between OxS and the deficits of frontal TC network dynamics as a possible mechanism underlying sleep abnormalities and impaired homeostatic responses observed in schizophrenia.

The impact of acoustic stimulation during sleep on memory and sleep architecture: A meta-analysis

The relationship between sleep and cognition has long been recognized, with slow-wave sleep thought to play a critical role in long-term memory consolidation. Recent research has presented the possibility that non-invasive acoustic stimulation during sleep could enhance memory consolidation. Herein, we report a random-effects model meta-analysis examining the impact of this intervention on memory and sleep architecture in healthy adults. Sixteen studies were identified through a systematic search. We found a medium significant effect of acoustic stimulation on memory task performance (g = 0.68, p = .031) in young adults <35 years of age, but no statistically significant effect in adults >35 years of age (g = -0.83, p = .223). In young adults, there was a large statistically significant effect for declarative memory tasks (g = 0.87, p = .014) but no effect for non-declarative tasks (g = -0.25, p = .357). There were no statistically significant differences in polysomnography-derived sleep architecture values between sham and stimulation conditions in either young or older adults. Based on these results, it appears that acoustic stimulation during sleep may only be an effective intervention for declarative memory consolidation in young adults. However, the small number of studies in this area, their small sample sizes, the short-term nature of most investigations and the high between-studies heterogeneity highlight a need for high-powered and long-term experiments to better elucidate, and subsequently maximise, any potential benefits of this novel approach.

Mechanosensory Stimulation via Nanchung Expressing Neurons Can Induce Daytime Sleep in Drosophila

The neuronal and genetic bases of sleep, a phenomenon considered crucial for well-being of organisms, has been under investigation using the model organism Drosophila melanogaster Although sleep is a state where sensory threshold for arousal is greater, it is known that certain kinds of repetitive sensory stimuli, such as rocking, can indeed promote sleep in humans. Here we report that orbital motion-aided mechanosensory stimulation promotes sleep of male and female Drosophila, independent of the circadian clock, but controlled by the homeostatic system. Mechanosensory receptor nanchung (Nan)-expressing neurons in the chordotonal organs mediate this sleep induction: flies in which these neurons are either silenced or ablated display significantly reduced sleep induction on mechanosensory stimulation. Transient activation of the Nan-expressing neurons also enhances sleep levels, confirming the role of these neurons in sleep induction. We also reveal that certain regions of the antennal mechanosensory and motor center in the brain are involved in conveying information from the mechanosensory structures to the sleep centers. Thus, we show, for the first time, that a circadian clock-independent pathway originating from peripherally distributed mechanosensors can promote daytime sleep of flies Drosophila melanogaster SIGNIFICANCE STATEMENT Our tendency to fall asleep in moving vehicles or the practice of rocking infants to sleep suggests that slow rhythmic movement can induce sleep, although we do not understand the mechanistic basis of this phenomenon. We find that gentle orbital motion can induce behavioral quiescence even in flies, a highly genetically tractable system for sleep studies. We demonstrate that this is indeed true sleep based on its rapid reversibility by sensory stimulation, enhanced arousal threshold, and homeostatic control. Furthermore, we demonstrate that mechanosensory neurons expressing a TRPV channel nanchung, located in the antennae and chordotonal organs, mediate orbital motion-induced sleep by communicating with antennal mechanosensory motor centers, which in turn may project to sleep centers in the brain.

A model characterizing the coupling between slow-wave activity, instantaneous heart rate and heart rate variability during sleep. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021;2021:72-75. [PMID: 34891242 DOI: 10.1109/embc46164.2021.9630006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

The cyclical and progressively decreasing dynamics of electroencephalogram (EEG) based slow-wave activity (SWA) during sleep reflects the homeostatic component of sleep-wake regulation. The dynamic changes of heart rate (HR) and heart rate variability (HRV) indices during sleep also exhibit quasi-cyclic trends that appear to correlate with SWA. This article proposes a model to characterize the relationship between SWA, HR and HRV in the polar-coordinate (r-θ) domain. Polar coordinates are particularly well-suited to model cyclic shapes with simple (linear) equations in the r-θ plane. Group-level analyses and individual-level ones of the correlations between the polar-coordinate transformations of SWA and HR reveal R² values of 0.99 and 0.95 respectively. Given that, HR and HRV can be estimated in less obtrusive ways compared to EEG. This research offers relevant options to conveniently monitor sleep SWA.Clinical Relevance- Slow wave activity is a marker of sleep restoration that most prominently manifests in the EEG. This research suggests that an electrocardiography (ECG)-based non-linear model can approximate a polar-coordinate version of SWA. Since ECG correlates can be unobtrusively acquired during sleep, these results suggest that practical SWA monitoring can be achieved through cardiac activity measurements.

Subjective Sleep Quality and Sleep Architecture in Patients With Migraine: A Meta-analysis

Background and Objectives

Sleep disturbance is often associated with migraine. However, there is a paucity of research investigating objective and subjective measures of sleep in patients with migraine. This meta-analysis aims to determine whether there are differences in subjective sleep quality measured using the Pittsburgh Sleep Quality Index (PSQI) and objective sleep architecture measured using polysomnography (PSG) between adult and pediatric patients and healthy controls.

Methods

This review was preregistered on PROSPERO (CRD42020209325). A systematic search of 5 databases (Embase, MEDLINE, Global Health, APA PsycINFO, and APA PsycArticles, last searched on December 17, 2020) was conducted to find case–control studies that measured PSG or PSQI in patients with migraine. Pregnant participants and those with other headache disorders were excluded. Effect sizes (Hedges g) were entered into a random effects model meta-analysis. Study quality was evaluated with the Newcastle Ottawa Scale and publication bias with the Egger regression test.

Results

Thirty-two studies were eligible, of which 21 measured PSQI or Migraine Disability Assessment Test in adults, 6 measured PSG in adults, and 5 measured PSG in children. The overall mean study quality score was 5/9; this did not moderate any of the results and there was no risk of publication bias. Overall, adults with migraine had higher PSQI scores than healthy controls (g = 0.75, p < 0.001, 95% confidence interval [CI] 0.54–0.96). This effect was larger in those with a chronic rather than episodic condition (g = 1.03, p < 0.001, 95% CI 0.37–1.01; g = 0.63, p < 0.001, 95% CI 0.38–0.88, respectively). For polysomnographic studies, adults and children with migraine displayed a lower percentage of rapid eye movement sleep (g = −0.22, p = 0.017, 95% CI −0.41 to −0.04; g = −0.71, p = 0.025, 95% CI −1.34 to −0.10, respectively) than controls. Pediatric patients displayed less total sleep time (g = −1.37, p = 0.039, 95% CI −2.66 to −0.10), more wake (g = 0.52, p < 0.001, 95% CI 0.08–0.79), and shorter sleep onset latency (g = −0.37, p < 0.001, 95% CI −0.54 to −0.21) than controls.

Discussion

People with migraine have significantly poorer subjective sleep quality and altered sleep architecture compared to healthy individuals. Further longitudinal empirical studies are required to enhance our understanding of this relationship.

Closed-loop auditory stimulation method to modulate sleep slow waves and motor learning performance in rats

Slow waves and cognitive output have been modulated in humans by phase-targeted auditory stimulation. However, to advance its technical development and further our understanding, implementation of the method in animal models is indispensable. Here, we report the successful employment of slow waves' phase-targeted closed-loop auditory stimulation (CLAS) in rats. To validate this new tool both conceptually and functionally, we tested the effects of up- and down-phase CLAS on proportions and spectral characteristics of sleep, and on learning performance in the single-pellet reaching task, respectively. Without affecting 24 hr sleep-wake behavior, CLAS specifically altered delta (slow waves) and sigma (sleep spindles) power persistently over chronic periods of stimulation. While up-phase CLAS does not elicit a significant change in behavioral performance, down-phase CLAS exerted a detrimental effect on overall engagement and success rate in the behavioral test. Overall CLAS-dependent spectral changes were positively correlated with learning performance. Altogether, our results provide proof-of-principle evidence that phase-targeted CLAS of slow waves in rodents is efficient, safe, and stable over chronic experimental periods, enabling the use of this high-specificity tool for basic and preclinical translational sleep research.

Sleep Abnormalities in Schizophrenia: State of the Art and Next Steps

Sleep disturbances are commonly observed in schizophrenia, including in chronic, early-course, and first-episode patients. This has generated considerable interest, both in clinical and research endeavors, in characterizing the relationship between disturbed sleep and schizophrenia. Sleep features can be objectively assessed with EEG recordings. Traditionally, EEG studies have focused on sleep architecture, which includes non-REM and REM sleep stages. More recently, numerous studies have investigated alterations in sleep-specific rhythms, including EEG oscillations, such as sleep spindles and slow waves, in individuals with schizophrenia compared with control subjects. In this article, the author reviews state-of-the-art evidence of disturbed sleep in schizophrenia, starting from the relationship between sleep disturbances and clinical symptoms. First, the author presents studies demonstrating abnormalities in sleep architecture and sleep-oscillatory rhythms in schizophrenia and related psychotic disorders, with an emphasis on recent work demonstrating sleep spindles and slow-wave deficits in early-course and first-episode schizophrenia. Next, the author shows how these sleep abnormalities relate to the cognitive impairments in patients diagnosed with schizophrenia and point to dysfunctions in underlying thalamocortical circuits, Ca+ channel activity, and GABA-glutamate neurotransmission. Finally, the author discusses some of the next steps needed to further establish the role of altered sleep in schizophrenia, including the need to investigate sleep abnormalities across the psychotic spectrum and to establish their relationship with circadian disturbances, which in turn will contribute to the development of novel sleep-informed treatment interventions.

Diazepam induced sleep spindle increase correlates with cognitive recovery in a child with epileptic encephalopathy

BACKGROUND

Continuous spike and wave of sleep with encephalopathy (CSWS) is a rare and severe developmental electroclinical epileptic encephalopathy characterized by seizures, abundant sleep activated interictal epileptiform discharges, and cognitive regression or deceleration of expected cognitive growth. The cause of the cognitive symptoms is unknown, and efforts to link epileptiform activity to cognitive function have been unrevealing. Converging lines of evidence implicate thalamocortical circuits in these disorders. Sleep spindles are generated and propagated by the same thalamocortical circuits that can generate spikes and, in healthy sleep, support memory consolidation. As such, sleep spindle deficits may provide a physiologically relevant mechanistic biomarker for cognitive dysfunction in epileptic encephalopathies.

CASE PRESENTATION

We describe the longitudinal course of a child with CSWS with initial cognitive regression followed by dramatic cognitive improvement after treatment. Using validated automated detection algorithms, we analyzed electroencephalograms for epileptiform discharges and sleep spindles alongside contemporaneous neuropsychological evaluations over the course of the patient's disease. We found that sleep spindles increased dramatically with high-dose diazepam treatment, corresponding with marked improvements in cognitive performance. We also found that the sleep spindle rate was anticorrelated to spike rate, consistent with a competitively shared underlying thalamocortical circuitry.

CONCLUSIONS

Epileptic encephalopathies are challenging electroclinical syndromes characterized by combined seizures and a deceleration or regression in cognitive skills over childhood. This report identifies thalamocortical circuit dysfunction in a case of epileptic encephalopathy and motivates future investigations of sleep spindles as a biomarker of cognitive function and a potential therapeutic target in this challenging disease.

Thalamic Influence on Slow Wave Slope Renormalization During Sleep

Objective

Slow waves are thought to mediate an overall reduction in synaptic strength during sleep. The specific contribution of the thalamus to this so‐called synaptic renormalization is unknown. Thalamic stroke is associated with daytime sleepiness, along with changes to sleep electroencephalography and cognition, making it a unique “experiment of nature” to assess the relationship between sleep rhythms, synaptic renormalization, and daytime functions.

Methods

Sleep was studied by polysomnography and high‐density electroencephalography over 17 nights in patients with thalamic (n = 12) and 15 nights in patients with extrathalamic (n = 11) stroke. Sleep electroencephalographic overnight slow wave slope changes and their relationship with subjective daytime sleepiness, cognition, and other functional tests were assessed.

Results

Thalamic and extrathalamic patients did not differ in terms of age, sleep duration, or apnea–hypopnea index. Conversely, overnight slope changes were reduced in a large cluster of electrodes in thalamic compared to extrathalamic stroke patients. This reduction was related to increased daytime sleepiness. No significant differences were found in other functional tests between the 2 groups.

Interpretation

In patients with thalamic stroke, a reduction in overnight slow wave slope change and increased daytime sleepiness was found. Sleep‐ and wake‐centered mechanisms for this relationship are discussed. Overall, this study suggests a central role of the thalamus in synaptic renormalization. ANN NEUROL 2021;90:821–833

Gene therapy using an ortholog of human fragile X mental retardation protein partially rescues behavioral abnormalities and EEG activity

Fragile X syndrome (FXS), a neurodevelopmental disorder with no known cure, is caused by a lack of expression of the fragile X mental retardation protein (FMRP). As a single-gene disorder, FXS is an excellent candidate for viral-vector-based gene therapy, although that is complicated by the existence of multiple isoforms of FMRP, whose individual cellular functions are unknown. We studied the effects of rat and mouse orthologs of human isoform 17, a major expressed isoform of FMRP. Injection of neonatal Fmr1 knockout rats and mice with adeno-associated viral vectors (AAV9 serotype) under the control of an MeCP2 mini-promoter resulted in widespread distribution of the FMRP transgenes throughout the telencephalon and diencephalon. Transgene expression occurred mainly in non-GABAergic neurons, with little expression in glia. Early postnatal treatment resulted in partial rescue of the Fmr1 KO rat phenotype, including improved social dominance in treated Fmr1 KO females and partial rescue of locomotor activity in males. Electro-encephalogram (EEG) recordings showed correction of abnormal slow-wave activity during the sleep-like state in male Fmr1 KO rats. These findings support the use of AAV-based gene therapy as a treatment for FXS and specifically demonstrate the potential therapeutic benefit of human FMRP isoform 17 orthologs.

Mind-wandering Is Accompanied by Both Local Sleep and Enhanced Processes of Spatial Attention Allocation

Mind-wandering (MW) is a subjective, cognitive phenomenon, in which thoughts move away from the task toward an internal train of thoughts, possibly during phases of neuronal sleep-like activity (local sleep, LS). MW decreases cortical processing of external stimuli and is assumed to decouple attention from the external world. Here, we directly tested how indicators of LS, cortical processing, and attentional selection change in a pop-out visual search task during phases of MW. Participants’ brain activity was recorded using magnetoencephalography, MW was assessed via self-report using randomly interspersed probes. As expected, the performance decreased under MW. Consistent with the occurrence of LS, MW was accompanied by a decrease in high-frequency activity (HFA, 80–150 Hz) and an increase in slow wave activity (SWA, 1–6 Hz). In contrast, visual attentional selection as indexed by the N2pc component was enhanced during MW with the N2pc amplitude being directly linked to participants’ performance. This observation clearly contradicts accounts of attentional decoupling that would predict a decrease in attention-related responses to external stimuli during MW. Together, our results suggest that MW occurs during phases of LS with processes of attentional target selection being upregulated, potentially to compensate for the mental distraction during MW.

You Snooze You Seize: GABAergic Potentiation of Genetic Generalized Seizures During NREM

Impaired State-Dependent Potentiation of GABAergic Synaptic Currents Triggers Seizures in a Genetic Generalized Epilepsy Model Zhang C-Q, Catron MA, Ding L, Hanna CM, Gallagher MJ, Macdonald RL, Zhou C. Cereb Cortex . 2021;31(2):768-784. doi:10.1093/cercor/bhaa256. https://pubmed.ncbi.nlm.nih.gov/32930324/ Epileptic activity in genetic generalized epilepsy (GGE) patients preferentially appears during sleep and its mechanism remains unknown. Here, we found that sleep-like slow-wave oscillations (0.5 Hz SWOs) potentiated excitatory and inhibitory synaptic currents in layer V cortical pyramidal neurons from wild-type (wt) mouse brain slices. In contrast, SWOs potentiated excitatory, but not inhibitory, currents in cortical neurons from a heterozygous (het) knock-in (KI) Gabrg2+Q/390X model of Dravet epilepsy syndrome. This created an imbalance between evoked excitatory and inhibitory currents to effectively prompt neuronal action potential firings. Similarly, physiologically similar up-/down-state induction (present during slow-wave sleep) in cortical neurons also potentiated excitatory synaptic currents within brain slices from wt and het KI mice. Moreover, this state-dependent potentiation of excitatory synaptic currents entailed some signaling pathways of homeostatic synaptic plasticity. Consequently, in het KI mice, in vivo SWO induction (using optogenetic methods) triggered generalized epileptic spike-wave discharges (SWDs), being accompanied by sudden immobility, facial myoclonus, and vibrissa twitching. In contrast, in wt littermates, SWO induction did not cause epileptic SWDs and motor behaviors. To our knowledge, this is the first mechanism to explain why epileptic SWDs preferentially happen during non-rapid eye-movement sleep and quiet-wakefulness in human GGE patients.

Abnormally abrupt transitions from sleep-to-wake in Huntington's disease sheep (Ovis aries) are revealed by automated analysis of sleep/wake transition dynamics

Sleep disturbance is a common and disruptive symptom of neurodegenerative diseases such as Alzheimer’s and Huntington’s disease (HD). In HD patients, sleep fragmentation appears at an early stage of disease, although features of the earliest sleep abnormalities in presymptomatic HD are not fully established. Here we used novel automated analysis of quantitative electroencephalography to study transitions between wake and non-rapid eye movement sleep in a sheep model of presymptomatic HD. We found that while the number of transitions between sleep and wake were similar in normal and HD sheep, the dynamics of transitions from sleep-to-wake differed markedly between genotypes. Rather than the gradual changes in EEG power that occurs during transitioning from sleep-to-wake in normal sheep, transition into wake was abrupt in HD sheep. Furthermore, transitions to wake in normal sheep were preceded by a significant reduction in slow wave power, whereas in HD sheep this prior reduction in slow wave power was far less pronounced. This suggests an impaired ability to prepare for waking in HD sheep. The abruptness of awakenings may also have potential to disrupt sleep-dependent processes if they are interrupted in an untimely and disjointed manner. We propose that not only could these abnormal dynamics of sleep transitions be useful as an early biomarker of HD, but also that our novel methodology would be useful for studying transition dynamics in other sleep disorders.

Effect of TAAR1/5-HT1A agonist SEP-363856 on REM sleep in humans

SEP-363856 is a trace amine-associated receptor 1 (TAAR1) and 5-hydroxytryptamine type 1A (5-HT_1A) agonist, currently in Phase 3 clinical trials for the treatment of schizophrenia. Although SEP-363856 activates TAAR1 and 5-HT_1A receptors in vitro, an accessible marker of time- and concentration-dependent effects of SEP-363856 in humans is lacking. In rodents, SEP-363856 has been shown to suppress rapid eye movement (REM) sleep. The aim of the current study was to translate the REM sleep effects to humans and determine pharmacokinetic/pharmacodynamic (PK/PD) relationships of SEP-363856 on a measure of brain activity. The effects of SEP-363856 were evaluated in a randomized, double-blind, placebo-controlled, 2-way crossover study of single oral doses (50 and 10 mg) on REM sleep in healthy male subjects (N = 12 at each dose level). Drug concentrations were sampled during sleep to interpolate individual subject's pharmacokinetic trajectories. SEP-363856 suppressed REM sleep parameters with very large effect sizes (>3) following single doses of 50 mg and plasma concentrations ≥100 ng/mL. Below that effective concentration, the 10 mg dose elicited much smaller effects, increasing only the latency to REM sleep (effect size = 1). The PK/PD relationships demonstrated that REM sleep probability increased as drug concentrations declined below 100 ng/mL over the course of the night. SEP-363856 was generally safe and well tolerated at both doses. The REM sleep-suppressing effects of SEP-363856 provide an accessible marker of brain activity, which can aid in dose selection and help elucidate its therapeutic potential in further clinical trials.

Examining the optimal timing for closed-loop auditory stimulation of slow-wave sleep in young and older adults

Study Objectives

Closed-loop auditory stimulation (CLAS) is a method for enhancing slow oscillations (SOs) through the presentation of auditory clicks during sleep. CLAS boosts SOs amplitude and sleep spindle power, but the optimal timing for click delivery remains unclear. Here, we determine the optimal time to present auditory clicks to maximize the enhancement of SO amplitude and spindle likelihood.

Methods

We examined the main factors predicting SO amplitude and sleep spindles in a dataset of 21 young and 17 older subjects. The participants received CLAS during slow-wave-sleep in two experimental conditions: sham and auditory stimulation. Post-stimulus SOs and spindles were evaluated according to the click phase on the SOs and compared between and within conditions.

Results

We revealed that auditory clicks applied anywhere on the positive portion of the SO increased SO amplitudes and spindle likelihood, although the interval of opportunity was shorter in the older group. For both groups, analyses showed that the optimal timing for click delivery is close to the SO peak phase. Click phase on the SO wave was the main factor determining the impact of auditory stimulation on spindle likelihood for young subjects, whereas for older participants, the temporal lag since the last spindle was a better predictor of spindle likelihood.

Conclusions

Our data suggest that CLAS can more effectively boost SOs during specific phase windows, and these differ between young and older participants. It is possible that this is due to the fluctuation of sensory inputs modulated by the thalamocortical networks during the SO.