Conscious experiences and high-density EEG patterns predicting subjective sleep depth

Decreased Delta/Beta ratio index as the sleep state-independent electrophysiological signature of sleep state misperception in Insomnia disorder: A focus on the sleep onset and the whole night

PURPOSE

Sleep State Misperception (SSM) is described as the tendency of Insomnia Disorder (ID) patients to overestimate Sleep Latency (SL) and underestimate Total Sleep Time (TST). Literature exploring topographical components in ID with SSM is scarce and does not allow us to fully understand the potential mechanisms underlying this phenomenon. This study aims to evaluate the existence of sleep EEG topography alterations in ID patients associated with SSM compared to Healthy Controls (HC), focusing on two distinct periods: the Sleep Onset (SO) and the whole night.

METHODS

Twenty ID patients (mean age: 43.5 ± 12.7; 7 M/13F) and 18 HCs (mean age: 41.6 ± 11.9; 8 M/10F) underwent a night of Polysomnography (PSG) and completed sleep diaries the following morning upon awakening. Two SSM indices, referring to the misperception of SL (SLm) and TST (TSTm), were calculated by comparing objective and subjective sleep indices extracted by PSG and sleep diary. According to these indices, the entire sample was split into 4 sub-groups: ID +SLm vs HC -SLm; ID +TSTm vs HC -TSTm.

RESULTS

Considering the SO, the two-way mixed-design ANOVA showed a significant main effect of Groups pointing to a decreased delta/beta ratio in the whole scalp topography. Moreover, we found a significant interaction effect for the sigma and beta bands. Post Hoc tests showed higher sigma and beta power in anterior and temporo-parietal sites during the SO period in IDs +SLm compared to HC -SLm. Considering the whole night, the unpaired t-test revealed in IDs +TSTm significantly lower delta power during NREM, and lower delta/beta ratio index during NREM and REM sleep compared to HCs -TSTm. Finally, we found diffuse significant negative correlations between SSM indices and the delta/beta ratio during SO, NREM, and REM sleep.

CONCLUSION

The main finding of the present study suggests that higher SL overestimation and TST underestimation are both phenomena related to diffuse cortical hyperarousal interpreted as a sleep state-independent electrophysiological correlate of the SSM, both during the SO and the whole night.

A REM-active basal ganglia circuit that regulates anxiety

Rapid eye movement (REM) sleep has been hypothesized to promote emotional resilience, but any neuronal circuits mediating this have not been identified. We find that in mice, somatostatin (Som) neurons in the entopeduncular nucleus (EPSom)/internal globus pallidus are predominantly active during REM sleep. This unique REM activity is both necessary and sufficient for maintaining normal REM sleep. Inhibiting or exciting EPSom neurons reduced or increased REM sleep duration, respectively. Activation of the sole downstream target of EPSom neurons, Vglut2 cells in the lateral habenula (LHb), increased sleep via the ventral tegmental area (VTA). A simple chemogenetic scheme to periodically inhibit the LHb over 4 days selectively removed a significant amount of cumulative REM sleep. Chronic, but not acute, REM reduction correlated with mice becoming anxious and more sensitive to aversive stimuli. Therefore, we suggest that cumulative REM sleep, in part generated by the EP → LHb → VTA circuit identified here, could contribute to stabilizing reactions to habitual aversive stimuli.

Performance of wearable sleep trackers during nocturnal sleep and periods of simulated real-world smartphone use

GOAL AND AIMS

To test sleep/wake transition detection of consumer sleep trackers and research-grade actigraphy during nocturnal sleep and simulated peri-sleep behavior involving minimal movement.

FOCUS TECHNOLOGY

Oura Ring Gen 3, Fitbit Sense, AXTRO Fit 3, Xiaomi Mi Band 7, and ActiGraph GT9X.

REFERENCE TECHNOLOGY

Polysomnography.

SAMPLE

Sixty-three participants (36 female) aged 20-68.

DESIGN

Participants engaged in common peri-sleep behavior (reading news articles, watching videos, and exchanging texts) on a smartphone before and after the sleep period. They were woken up during the night to complete a short questionnaire to simulate responding to an incoming message.

CORE ANALYTICS

Detection and timing accuracy for the sleep onset times and wake times.

ADDITIONAL ANALYTICS AND EXPLORATORY ANALYSES

Discrepancy analysis both including and excluding the peri-sleep activity periods. Epoch-by-epoch analysis of rate and extent of wake misclassification during peri-sleep activity periods.

CORE OUTCOMES

Oura and Fitbit were more accurate at detecting sleep/wake transitions than the actigraph and the lower-priced consumer sleep tracker devices. Detection accuracy was less reliable in participants with lower sleep efficiency.

IMPORTANT ADDITIONAL OUTCOMES

With inclusion of peri-sleep periods, specificity and Kappa improved significantly for Oura and Fitbit, but not ActiGraph. All devices misclassified motionless wake as sleep to some extent, but this was less prevalent for Oura and Fitbit.

CORE CONCLUSIONS

Performance of Oura and Fitbit is robust on nights with suboptimal bedtime routines or minor sleep disturbances. Reduced performance on nights with low sleep efficiency bolsters concerns that these devices are less accurate for fragmented or disturbed sleep.

Chronic insomnia, REM sleep instability and emotional dysregulation: A pathway to anxiety and depression?

The world-wide prevalence of insomnia disorder reaches up to 10% of the adult population. Women are more often afflicted than men, and insomnia disorder is a risk factor for somatic and mental illness, especially depression and anxiety disorders. Persistent hyperarousals at the cognitive, emotional, cortical and/or physiological levels are central to most theories regarding the pathophysiology of insomnia. Of the defining features of insomnia disorder, the discrepancy between minor objective polysomnographic alterations of sleep continuity and substantive subjective impairment in insomnia disorder remains enigmatic. Microstructural alterations, especially in rapid eye movement sleep ("rapid eye movement sleep instability"), might explain this mismatch between subjective and objective findings. As rapid eye movement sleep represents the most highly aroused brain state during sleep, it might be particularly prone to fragmentation in individuals with persistent hyperarousal. In consequence, mentation during rapid eye movement sleep may be toned more as conscious-like wake experience, reflecting pre-sleep concerns. It is suggested that this instability of rapid eye movement sleep is involved in the mismatch between subjective and objective measures of sleep in insomnia disorder. Furthermore, as rapid eye movement sleep has been linked in previous works to emotional processing, rapid eye movement sleep instability could play a central role in the close association between insomnia and depressive and anxiety disorders.

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.

Human Prosocial Preferences Are Related to Slow-Wave Activity in Sleep

Prosocial behavior is crucial for the smooth functioning of the society. Yet, individuals differ vastly in the propensity to behave prosocially. Here, we try to explain these individual differences under normal sleep conditions without any experimental modulation of sleep. Using a portable high-density EEG, we measured the sleep data in 54 healthy adults (28 females) during a normal night's sleep at the participants' homes. To capture prosocial preferences, participants played an incentivized public goods game in which they faced real monetary consequences. The whole-brain analyses showed that a higher relative slow-wave activity (SWA, an indicator of sleep depth) in a cluster of electrodes over the right temporoparietal junction (TPJ) was associated with increased prosocial preferences. Source localization and current source density analyses further support these findings. Recent sleep deprivation studies imply that sleeping enough makes us more prosocial; the present findings suggest that it is not only sleep duration, but particularly sufficient sleep depth in the TPJ that is positively related to prosociality. Because the TPJ plays a central role in social cognitive functions, we speculate that sleep depth in the TPJ, as reflected by relative SWA, might serve as a dispositional indicator of social cognition ability, which is reflected in prosocial preferences. These findings contribute to the emerging framework explaining the link between sleep and prosocial behavior by shedding light on the underlying mechanisms.

Embracing sleep-onset complexity

Sleep is crucial for many vital functions and has been extensively studied. By contrast, the sleep-onset period (SOP), often portrayed as a mere prelude to sleep, has been largely overlooked and remains poorly characterized. Recent findings, however, have reignited interest in this transitional period and have shed light on its neural mechanisms, cognitive dynamics, and clinical implications. This review synthesizes the existing knowledge about the SOP in humans. We first examine the current definition of the SOP and its limits, and consider the dynamic and complex electrophysiological changes that accompany the descent to sleep. We then describe the interplay between internal and external processing during the wake-to-sleep transition. Finally, we discuss the putative cognitive benefits of the SOP and identify novel directions to better diagnose sleep-onset disorders.

Objective sleep quality predicts subjective sleep ratings

In both clinical and observational studies, sleep quality is usually assessed by subjective self-report. The literature is mixed about how accurately these self-reports track objectively (e.g. via polysomnography) assessed sleep quality, with frequent reports of little to no association. However, previous research on this question focused on between-subject designs, which may be confounded by trait-level variables. In the current study, we used the novel Budapest Sleep, Experiences and Traits Study (BSETS) dataset to investigate if within-subject differences in subjectively reported sleep quality are related to sleep macrostructure and quantitative EEG variables assessed using a mobile EEG headband. We found clear evidence that self-reported sleep quality in the morning is influenced by within-subject variations in sleep onset latency, wake after sleep onset, total sleep time, and sleep efficiency. These effects were replicated if detailed sleep composition metrics (percentage and latency of specific vigilance states) or two alternative measures of subjective sleep quality were used instead. We found no effect of the number of awakenings or relative EEG delta and sigma power. Between-subject effects (relationships between individual mean values of sleep metrics and subjective sleep quality) were also found, highlighting that analyses focusing only on these may be erroneous. Our findings show that while previous investigations of this issue may have been confounded by between-subject effects, objective sleep quality is indeed reflected in subjective sleep ratings.

Methodological approach to sleep state misperception in insomnia disorder: Comparison between multiple nights of actigraphy recordings and a single night of polysomnography recording

STUDY OBJECTIVE

To provide a comprehensive assessment of sleep state misperception in insomnia disorder (INS) and good sleepers (GS) by comparing recordings performed for one night in-lab (PSG and night review) and during several nights at-home (actigraphy and sleep diaries).

METHODS

Fifty-seven INS and 29 GS wore an actigraphy device and filled a sleep diary for two weeks at-home. They subsequently completed a PSG recording and filled a night review in-lab. Sleep perception index (subjective/objective × 100) of sleep onset latency (SOL), sleep duration (TST) and wake duration (TST) were computed and compared between methods and groups.

RESULTS

GS displayed a tendency to overestimate TST and WASO but correctly perceived SOL. The degree of misperception was similar across methods within the GS group. In contrast, INS underestimated their TST and overestimated their SOL both in-lab and at-home, yet the severity of misperception of SOL was larger at-home than in-lab. Finally, INS overestimated WASO only in-lab while correctly perceiving it at-home. While only the degree of TST misperception was stable across methods in INS, misperception of SOL and WASO were dependent on the method used.

CONCLUSIONS

We found that GS and INS exhibit opposite patterns and severity of sleep misperception. While the degree of misperception in GS was similar across methods, only sleep duration misperception was reliably detected by both in-lab and at-home methods in INS. Our results highlight that, when assessing sleep misperception in insomnia disorder, the environment and method of data collection should be carefully considered.

Evaluating the impact of adjunct bright light therapy on subjective sleep quality in major depressive disorder

BACKGROUND

Sleep disturbances are a fundamental feature of depression, with their persistence after remission serving as a key risk factor for recurrence of depressive episodes, suicide, and hypnotics abuse. Though Adjunct Bright Light Therapy (BLT) has shown efficacy in treating depression by improving sleep duration and timing, its impact on subjective sleep quality remains underexplored.

OBJECTIVE

This study investigates the effect of adjunct BLT on the subjective experience of sleep quality of Major Depressive Disorder (MDD) inpatients.

METHODS

A randomized controlled trial was undertaken with 100 MDD consecutively admitted inpatients on consistent antidepressant regimens. Participants were divided into two groups; Group A, received pharmacotherapy augmented with BLT, Group B, received pharmacotherapy alone. The Hamilton Depression Rating Scale assessed depressive symptoms, while the Pittsburgh Sleep Quality Index (PSQI) evaluated subjective sleep quality.

RESULTS

While both groups displayed enhanced depressive symptomatology, only Group A manifested significant improvement in perceived sleep quality (PSQI scores: A T0 8.05 ± 5.07 vs. T1 5.64 ± 3.64, p < 0.001; B T0 7.11 ± 3.17 vs. T1 6.50 ± 3.04, p = 0.072).

LIMITATIONS

Study limitations include its single-site design, lack of objective sleep measurement, and exclusive SSRI use, suggesting caution in generalizing findings. Further, the absence of placebo control and unmeasured expectancy effects may influence treatment outcomes.

CONCLUSIONS

These findings underscore the criticality of subjective sleep quality in clinical evaluations and highlight the potential of adjunct BLT as an augmentation therapeutic strategy to ameliorate sleep perception in MDD patients, emphasizing its potential role in enhancing therapeutic outcomes.

Cardio-audio synchronization elicits neural and cardiac surprise responses in human wakefulness and sleep

The human brain can encode auditory regularities with fixed sound-to-sound intervals and with sound onsets locked to cardiac inputs. Here, we investigated auditory and cardio-audio regularity encoding during sleep, when bodily and environmental stimulus processing may be altered. Using electroencephalography and electrocardiography in healthy volunteers (N = 26) during wakefulness and sleep, we measured the response to unexpected sound omissions within three regularity conditions: synchronous, where sound and heartbeat are temporally coupled, isochronous, with fixed sound-to-sound intervals, and a control condition without regularity. Cardio-audio regularity encoding manifested as a heartbeat deceleration upon omissions across vigilance states. The synchronous and isochronous sequences induced a modulation of the omission-evoked neural response in wakefulness and N2 sleep, the former accompanied by background oscillatory activity reorganization. The violation of cardio-audio and auditory regularity elicits cardiac and neural responses across vigilance states, laying the ground for similar investigations in altered consciousness states such as coma and anaesthesia.

Neurophysiological Parameters Influencing Sleep-Wake Discrepancy in Insomnia Disorder: A Preliminary Analysis on Alpha Rhythm during Sleep Onset

Sleep state misperception (SSM) is a common issue in insomnia disorder (ID), causing a discrepancy between objective and subjective sleep/wake time estimation and increased daytime impairments. In this context, the hyperarousal theory assumes that sustained central nervous system activation contributes to the SSM. This study investigates factors influencing SSM during sleep latency (SL) and total sleep time (TST). Objective polysomnographic sleep variables (the alpha density index, latency-to-sleep stages and the first K-complex, and Rapid Eye Movement (REM) arousal density) and subjective sleep indices, taken from sleep diaries, were analyzed in 16 ID patients. Correlation analyses revealed a positive association between the degree of SL misperception (SLm) and the percentage of epochs that contained a visually scored stereotyped alpha rhythm during objective SL. A regression analysis showed that the REM arousal density and alpha density index significantly predicted TST misperception (TSTm). Furthermore, the degree of SLm was associated with an increased probability of transitioning from stage 1 of non-REM sleep to wakefulness during subjective SL. These findings support the role of hyperarousal in SSM and highlight the importance of alpha activity in unravelling the heterogeneous underpinnings of SSM.

Reduced subjective sleep quality in people rating themselves as electro-hypersensitive: An observational study

BACKGROUND

Disturbed sleep is among the most frequent health complaints of people exposed to radio frequency electromagnetic fields (RF-EMF) used in mobile telecommunication, particularly in individuals who consider themselves as EMF hypersensitive (EHS). We aimed at investigating whether the EHS status per se is associated with sleep complaints. Because allelic variants of the gene encoding the L-type, voltage-gated calcium channel Cav1.2 (CACNA1C) were previously associated with sleep complaints reminiscent of those reported by EHS individuals, we also explored whether self-rated EHS status and sleep quality associate with these gene variants.

METHODS

A total of 2'040 participants (1'381 females) aged 18-30 years completed online, validated questionnaires on EMF sensitivity, subjective sleep quality, daytime sleepiness, mentation during sleep, and diurnal preference. They also provided a saliva sample for genotyping three functional variants of CACNA1C (rs7304986, rs16929277 and rs2302729). Eligible participants endorsing the question "Are you electro-hypersensitive?" were considered as "EHS" (n = 105), those denying this question yet believing to develop detrimental health symptoms due to prevailing electromagnetic pollution as "attributers" (n = 254), and the remaining participants as "non-EHS" (n = 1'406). We combined the EHS and attributers into one group for binary analyses. In exploratory analyses, we then tested possible associations between EMF sensitivity, subjective sleep variables and CACNA1C variants using linear and logistic regression. We used age, sex, level of education, presence of sleep disorders and habitual mobile phone use as covariates and corrected with Benjamini-Hochberg False Discovery Rate for multiple comparisons.

RESULTS

The EHS/attributers consistently reported prolonged sleep latency, reduced sleep quality, higher sleepiness and more nocturnal mentation when compared to non-EHS. Habitual mobile phone use was not associated with self-rated sleep latency and sleep quality scores. While the T-allele of variant rs2302729 of CACNA1C was associated with both, self-reported EMF sensitivity and reduced subjective sleep quality, we found no evidence for the hypothesis that EHS mediates impaired sleep quality via this allelic variant.

CONCLUSIONS

Irrespective of reported RF-EMF exposure, self-rated EHS/attributers rated subjective sleep quality worse than non-EHS individuals.

TRIAL REGISTRATION

Swiss National Clinical Trials Portal (SNCTP000002285) and ClinicalTrials.gov (NCT03074617).

Sleep and circadian rhythmicity as entangled processes serving homeostasis

Sleep is considered essential for the brain and body. A predominant concept is that sleep is regulated by circadian rhythmicity and sleep homeostasis, processes that were posited to be functionally and mechanistically separate. Here we review and re-evaluate this concept and its assumptions using findings from recent human and rodent studies. Alterations in genes that are central to circadian rhythmicity affect not only sleep timing but also putative markers of sleep homeostasis such as electroencephalogram slow-wave activity (SWA). Perturbations of sleep change the rhythmicity in the expression of core clock genes in tissues outside the central clock. The dynamics of recovery from sleep loss vary across sleep variables: SWA and immediate early genes show an early response, but the recovery of non-rapid eye movement and rapid eye movement sleep follows slower time courses. Changes in the expression of many genes in response to sleep perturbations outlast the effects on SWA and time spent asleep. These findings are difficult to reconcile with the notion that circadian- and sleep-wake-driven processes are mutually independent and that the dynamics of sleep homeostasis are reflected in a single variable. Further understanding of how both sleep and circadian rhythmicity contribute to the homeostasis of essential physiological variables may benefit from the assessment of multiple sleep and molecular variables over longer time scales.

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.

Penguins snatch seconds-long microsleeps

Chinstrap penguins fall asleep thousands of times per day in the wild.

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.

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.

Does providing feedback and guidance on sleep perceptions using sleep wearables improve insomnia? Findings from "Novel Insomnia Treatment Experiment": a randomized controlled trial

STUDY OBJECTIVES

Insomnia is a disorder diagnosed based on self-reported sleep complaints. Differences between self-reported and sensor-based sleep parameters (sleep-wake state discrepancy) are common but not well-understood in individuals with insomnia. This two-arm, parallel-group, single-blind, superiority randomized-controlled trial examined whether monitoring sleep using wearable devices and providing support for interpretation of sensor-based sleep data improved insomnia symptoms or impacted sleep-wake state discrepancy.

METHODS

A total of 113 (age M = 47.53; SD = 14.37, 64.9% female) individuals with significant insomnia symptoms (Insomnia Severity Index(ISI) ≥10) from the community were randomized 1:1 (permuted block randomization) to receive 5 weeks (1) Intervention (n = 57): feedback about sensor-based sleep (Fitbit and EEG headband) with guidance for data interpretation and ongoing monitoring, and (2) Control (n = 56): sleep education and hygiene. Both groups received one individual session and two check-in calls. The ISI (primary outcome), sleep disturbance (SDis), sleep-related impairment (SRI), depression, and anxiety were assessed at baseline and post-intervention.

RESULTS

In total, 103 (91.2%) participants completed the study. Intention-to-treat multiple regression with multiple imputations showed that after controlling for baseline values, compared to the Control group (n = 51), the Intervention group (n = 52) had lower ISI (p = .011, d = 0.51) and SDis (p = .036, d = 0.42) post-intervention, but differences in SRI, depression, anxiety, and sleep-wake state discrepancy parameters (total sleep time, sleep onset latency, and wake after sleep onset) were not meaningful (P-values >.40).

CONCLUSIONS

Providing feedback and guidance about sensor-based sleep parameters reduced insomnia severity and sleep disturbance but did not alter sleep-wake state discrepancy in individuals with insomnia more than sleep hygiene and education. The role of sleep wearable devices among individuals with insomnia requires further research.

CLINICAL TRIAL REGISTRATION

The Novel Insomnia Treatment Experiment (NITE): the effectiveness of incorporating appropriate guidance for sleep wearables in users with insomnia. https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=378452, Australia New Zealand Clinical Trials Registry: ACTRN12619001636145.

Understanding the Need for Sleep to Improve Cognition

The restorative function of sleep is shaped by its duration, timing, continuity, subjective quality, and efficiency. Current sleep recommendations specify only nocturnal duration and have been largely derived from sleep self-reports that can be imprecise and miss relevant details. Sleep duration, preferred timing, and ability to withstand sleep deprivation are heritable traits whose expression may change with age and affect the optimal sleep prescription for an individual. Prevailing societal norms and circumstances related to work and relationships interact to influence sleep opportunity and quality. The value of allocating time for sleep is revealed by the impact of its restriction on behavior, functional brain imaging, sleep macrostructure, and late-life cognition. Augmentation of sleep slow oscillations and spindles have been proposed for enhancing sleep quality, but they inconsistently achieve their goal. Crafting bespoke sleep recommendations could benefit from large-scale, longitudinal collection of objective sleep data integrated with behavioral and self-reported data.

Sleeping with time in mind? A literature review and a proposal for a screening questionnaire on self-awakening

Some people report being able to spontaneously "time" the end of their sleep. This ability to self-awaken challenges the idea of sleep as a passive cognitive state. Yet, current evidence on this phenomenon is limited, partly because of the varied definitions of self-awakening and experimental approaches used to study it. Here, we provide a review of the literature on self-awakening. Our aim is to i) contextualise the phenomenon, ii) propose an operating definition, and iii) summarise the scientific approaches used so far. The literature review identified 17 studies on self-awakening. Most of them adopted an objective sleep evaluation (76%), targeted nocturnal sleep (76%), and used a single criterion to define the success of awakening (82%); for most studies, this corresponded to awakening occurring in a time window of 30 minutes around the expected awakening time. Out of 715 total participants, 125 (17%) reported to be self-awakeners, with an average age of 23.24 years and a slight predominance of males compared to females. These results reveal self-awakening as a relatively rare phenomenon. To facilitate the study of self-awakening, and based on the results of the literature review, we propose a quick paper-and-pencil screening questionnaire for self-awakeners and provide an initial validation for it. Taken together, the combined results of the literature review and the proposed questionnaire help in characterising a theoretical framework for self-awakenings, while providing a useful tool and empirical suggestions for future experimental studies, which should ideally employ objective measurements.

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.

Insomnia disorder: State of the science and challenges for the future

Insomnia disorder comprises symptoms during night and day that strongly affect quality of life and wellbeing. Prolonged sleep latency, difficulties to maintain sleep and early morning wakening characterize sleep complaints, whereas fatigue, reduced attention, impaired cognitive functioning, irritability, anxiety and low mood are key daytime impairments. Insomnia disorder is well acknowledged in all relevant diagnostic systems: Diagnostic and Statistical Manual of the American Psychiatric Association, 5th revision, International Classification of Sleep Disorders, 3rd version, and International Classification of Diseases, 11th revision. Insomnia disorder as a chronic condition is frequent (up to 10% of the adult population, with a preponderance of females), and signifies an important and independent risk factor for physical and, especially, mental health. Insomnia disorder diagnosis primarily rests on self-report. Objective measures like actigraphy or polysomnography are not (yet) part of the routine diagnostic canon, but play an important role in research. Disease concepts of insomnia range from cognitive-behavioural models to (epi-) genetics and psychoneurobiological approaches. The latter is derived from knowledge about basic sleep-wake regulation and encompass theories like rapid eye movement sleep instability/restless rapid eye movement sleep. Cognitive-behavioural models of insomnia led to the conceptualization of cognitive-behavioural therapy for insomnia, which is now considered as first-line treatment for insomnia worldwide. Future research strategies will include the combination of experimental paradigms with neuroimaging and may benefit from more attention to dysfunctional overnight alleviation of distress in insomnia. With respect to therapy, cognitive-behavioural therapy for insomnia merits widespread implementation, and digital cognitive-behavioural therapy may assist delivery along treatment guidelines. However, given the still considerable proportion of patients responding insufficiently to cognitive-behavioural therapy for insomnia, fundamental studies are highly necessary to better understand the brain and behavioural mechanisms underlying insomnia. Mediators and moderators of treatment response/non-response and the associated development of tailored and novel interventions also require investigation. Recent studies suggest that treatment of insomnia may prove to add significantly as a preventive strategy to combat the global burden of mental disorders.

Pre-Sleep Cognitive Arousal Is Negatively Associated with Sleep Misperception in Healthy Sleepers during Habitual Environmental Noise Exposure: An Actigraphy Study

Specific noises (e.g., traffic or wind turbines) can disrupt sleep and potentially cause a mismatch between subjective sleep and objective sleep (i.e., “sleep misperception”). Some individuals are likely to be more vulnerable than others to noise-related sleep disturbances, potentially as a result of increased pre-sleep cognitive arousal. The aim of the present study was to examine the relationships between pre-sleep cognitive arousal and sleep misperception. Sixteen healthy sleepers participated in this naturalistic, observational study. Three nights of sleep were measured using actigraphy, and each 15-s epoch was classified as sleep or wake. Bedside noise was recorded, and each 15-s segment was classified as containing noise or no noise and matched to actigraphy. Participants completed measures of habitual pre-sleep cognitive and somatic arousal and noise sensitivity. Pre-sleep cognitive and somatic arousal levels were negatively associated with subjective−objective total sleep time discrepancy (p < 0.01). There was an association between sleep/wake and noise presence/absence in the first and last 90 min of sleep (p < 0.001). These results indicate that higher levels of habitual pre-sleep arousal are associated with a greater degree of sleep misperception, and even in healthy sleepers, objective sleep is vulnerable to habitual bedside noise.

Sleep discrepancy is associated with alterations in the salience network in patients with insomnia disorder: An EEG-fMRI study

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Simultaneous EEG-fMRI was used to clarify the association between the brain functional connectivity and sleep discrepancy between self-report and polysomnography in patients with insomnia disorder.

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An altered anterior insula-based connectivity across wakefulness and all NREM stages.

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Sleep discrepancy was significantly associated with anterior insula–putamen/thalamus connectivity during wakefulness.

Background

Positron emission tomography – computed tomography (PET-CT) research has shown that sleep discrepancy recorded by self-report and polysomnography (PSG) may be related to the altered metabolic rate of the anterior insula (aINS) during non-rapid eye movement (NREM) sleep in patients with insomnia disorder. We aim to explore the functional connectivity of aINS across wake and NREM sleep in the patients and to reveal the association between aINS connectivity and sleep discrepancy.

Methods

Patients with insomnia disorder (n = 33) and healthy controls (n = 31) underwent simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI) during nighttime sleep, and aINS-based connectivity was calculated across wake and NREM sleep. A linear mixed-effects model was used to assess the main effect of group and group-by-stage (wake, NREM stages 1–3) interaction effect on aINS connectivity. Similar mixed models were used to assess the potential correlation between aINS connectivity and the sleep misperception index (MI).

Results

A significant group-by-stage interaction effect on aINS-based connectivity was observed in the bilateral frontal gyrus, right inferior temporal gyrus, bilateral middle occipital gyrus and right postcentral gyrus (p < 0.05, corrected). There was also a significant group-by-MI interaction effect on aINS connectivity with the putamen and thalamus during wakefulness (p < 0.05 corrected); MI was significantly associated with aINS–putamen/thalamus connectivity in the control group, whereas the association was weak or even nonsignificant in the patient group. There was no significant main effect of group.

Conclusion

The waking activity of a neural pathway containing the aINS, putamen, and thalamus may underlie sleep perception, potentially providing important perspectives to reveal complex mechanisms of sleep discrepancy between self-report and PSG.

Sleep: Feeling awake while asleep

What makes a good night's sleep? It is often assumed that sleep is the deepest when brain activity is dominated by hyper-synchronized slow waves. However, sleep appears subjectively the deepest in rapid eye movement (REM) sleep, when slow waves are absent.