The first-night effect and the consistency of short sleep in insomnia disorder.

The nature and degree of objective sleep impairments in insomnia disorder remain unclear. This issue is complicated further by potential changes in sleep architecture on the first compared with subsequent nights in the laboratory. Evidence regarding differential first-night effects in people with insomnia disorder and controls is mixed. Here, we aimed to further characterize insomnia- and night-related differences in sleep architecture. A comprehensive set of 26 sleep variables was derived from two consecutive nights of polysomnography in 61 age-matched patients with insomnia and 61 good sleeper controls. People with insomnia expressed consistently poorer sleep than controls on several variables during both nights. While poorer sleep during the first night was observed in both groups, there were qualitative differences regarding the specific sleep variables expressing a first-night effect. Short sleep (total sleep time < 6 hr) was more likely during the first night and in insomnia, although approximately 40% of patients with insomnia presenting with short sleep on night 1 no longer met this criterion on night 2, which is important given the notion of short-sleeping insomnia as a robust subtype.

Associations between signs of sleep bruxism and insomnia: A polysomnographic study.

Sleep bruxism (SB) is a repetitive jaw-muscle activity characterised by clenching or grinding of the teeth and/or by bracing or thrusting of the mandible. Sleep bruxism has been linked with insomnia symptoms. Moreover, it has been suggested that there is a positive association between distress and the occurrence of sleep bruxism. However, the occurrence of sleep bruxism and its association with distress have not been studied in patients with insomnia. Therefore, we hypothesised that: (1) the occurrence of sleep bruxism is higher in patients with insomnia than in healthy controls; and (2) the occurrence of sleep bruxism in insomnia patients with moderate to high distress (IMHD) is higher than that in insomnia patients with slight distress (ISD). A total of 44 controls (34 females, 10 males, mean ± SD age = 46.8 ± 14.4 years) and 42 participants with insomnia (35 females, 7 males, mean ± SD age = 51.3 ± 12.1 years) were enrolled in this study. Among 42 participants with insomnia, 20 participants were subtyped as IMHD, 17 participants as ISD. Another five participants were not subtyped due to insufficient information. Group differences in rhythmic masticatory muscle activity (RMMA), a biomarker of sleep bruxism, were evaluated with Mann-Whitney U tests. The medians and interquartile ranges of the RMMA indices were 0.8|1.8|3.3 in controls, 1.1|1.6|2.3 in IMHD and 1.2|1.9|2.9 in ISD. There was no significant difference in the RMMA index, neither between participants with insomnia and controls (P = 0.514) nor between IMHD versus ISD (P = 0.270). The occurrence of RMMA indicators of possible sleep bruxism is not significantly different between individuals with insomnia and controls, nor between IMHD versus ISD.

Functional connectivity correlates of attentional networks in insomnia disorder: A pilot study.

Insomnia disorder has been associated with poor executive functioning. Functional imaging studies of executive functioning in insomnia are scarce and inconclusive. Because the Attentional Network Test relies on well-defined cortical networks and sensitively distinguishes different aspects of executive function, it might reveal brain functional alterations in relatively small samples of patients. The current pilot study assessed functional connectivity during the Attentional Network Test performed using magnetic resonance imaging in 12 participants with insomnia and 13 self-defined good sleepers. ANCOVAs were used to evaluate group differences in performance and functional connectivity in the regions of interest representing the attentional networks (i.e. alerting, orienting and executive control) at p < 0.05, uncorrected. During the orienting part, participants with insomnia showed weaker connectivity of the precentral gyrus with the superior parietal lobe (false discovery rate-corrected), while they showed stronger connectivity between premotor and visual regions. Individual differences in connectivity between premotor and visual regions correlated inversely with reaction time. Reaction times suggested more efficient executive control in participants with insomnia compared with good sleepers. During the executive control part, participants with insomnia showed stronger connectivity of thalamic parts of the arousal circuit with the middle frontal and the occipital gyri. Conversely, connectivity between the inferior and superior frontal gyri was weaker. Participants with insomnia seem to recruit more cortical resources in visuo-motor regions to orient attention than good sleepers do, and seem to have enhanced executive control that relates to stronger connectivity of arousal-related thalamic areas. This latter result should be treated with caution and requires confirmation.

Actigraphy in studies on insomnia: Worth the effort?

In the past decades, actigraphy has emerged as a promising, cost-effective, and easy-to-use tool for ambulatory sleep recording. Polysomnography (PSG) validation studies showed that actigraphic sleep estimates fare relatively well in healthy sleepers. Additionally, round-the-clock actigraphy recording has been used to study circadian rhythms in various populations. To this date, however, there is little evidence that the diagnosis, monitoring, or treatment of insomnia can significantly benefit from actigraphy recordings. Using a case-control design, we therefore critically examined whether mean or within-subject variability of actigraphy sleep estimates or circadian patterns add to the understanding of sleep complaints in insomnia. We acquired actigraphy recordings and sleep diaries of 37 controls and 167 patients with varying degrees of insomnia severity for up to 9 consecutive days in their home environment. Additionally, the participants spent one night in the laboratory, where actigraphy was recorded alongside PSG to check whether sleep, in principle, is well estimated. Despite moderate to strong agreement between actigraphy and PSG sleep scoring in the laboratory, ambulatory actigraphic estimates of average sleep and circadian rhythm variables failed to successfully differentiate patients with insomnia from controls in the home environment. Only total sleep time differed between the groups. Additionally, within-subject variability of sleep efficiency and wake after sleep onset was higher in patients. Insomnia research may therefore benefit from shifting attention from average sleep variables to day-to-day variability or from the development of non-motor home-assessed indicators of sleep quality.

Improved Manual Annotation of EEG Signals through Convolutional Neural Network Guidance.

The development of validated algorithms for automated handling of artifacts is essential for reliable and fast processing of EEG signals. Recently, there have been methodological advances in designing machine-learning algorithms to improve artifact detection of trained professionals who usually meticulously inspect and manually annotate EEG signals. However, validation of these methods is hindered by the lack of a gold standard as data are mostly private and data annotation is time consuming and error prone. In the effort to circumvent these issues, we propose an iterative learning model to speed up and reduce errors of manual annotation of EEG. We use a convolutional neural network (CNN) to train on expert-annotated eyes-open and eyes-closed resting-state EEG data from typically developing children (n = 30) and children with neurodevelopmental disorders (n = 141). To overcome the circular reasoning of aiming to develop a new algorithm and benchmarking to a manually-annotated gold standard, we instead aim to improve the gold standard by revising the portion of the data that was incorrectly learned by the network. When blindly presented with the selected signals for re-assessment (23% of the data), the two independent expert-annotators changed the annotation in 25% of the cases. Subsequently, the network was trained on the expert-revised gold standard, which resulted in improved separation between artifacts and nonartifacts as well as an increase in balanced accuracy from 74% to 80% and precision from 59% to 76%. These results show that CNNs are promising to enhance manual annotation of EEG artifacts and can be improved further with better gold-standard data.

Single-case experimental designs for bumetanide across neurodevelopmental disorders: BUDDI protocol.

BACKGROUND: Bumetanide is a selective NKCC1 chloride importer antagonist which is being repurposed as a mechanism-based treatment for neurodevelopmental disorders (NDDs). Due to their specific actions, these kinds of interventions will only be effective in particular subsets of patients. To anticipate stratified application, we recently completed three bumetanide trials each focusing on different stratification strategies with the additional objective of deriving the most optimal endpoints. Here we publish the protocol of the post-trial access combined cohort study to confirm previous effects and stratification strategies in the trial cohorts and in new participants. METHOD/DESIGN: Participants of the three previous cohorts and a new cohort will be subjected to 6 months bumetanide treatment using multiple baseline Single Case Experimental Designs. The primary outcome is the change, relative to baseline, in a set of patient reported outcome measures focused on direct and indirect effects of sensory processing difficulties. Secondary outcome measures include the conventional questionnaires 'social responsiveness scale', 'repetitive behavior scale', 'sensory profile' and 'aberrant behavior scale'. Resting-state EEG measurements will be performed at several time-points including at Tmax after the first administration. Assessment of cognitive endpoints will be conducted using the novel Emma Tool box, an in-house designed battery of computerized tests to measure neurocognitive functions in children. DISCUSSION: This study aims to replicate previously shown effects of bumetanide in NDD subpopulations, validate a recently proposed treatment prediction effect methodology and refine endpoint measurements. TRIAL REGISTRATION: EudraCT: 2020-002196-35, registered 16 November 2020, https://www.clinicaltrialsregister.eu/ctr-search/trial/2020-002196-35/NL.

Sleep classification from wrist-worn accelerometer data using random forests.

Accurate and low-cost sleep measurement tools are needed in both clinical and epidemiological research. To this end, wearable accelerometers are widely used as they are both low in price and provide reasonably accurate estimates of movement. Techniques to classify sleep from the high-resolution accelerometer data primarily rely on heuristic algorithms. In this paper, we explore the potential of detecting sleep using Random forests. Models were trained using data from three different studies where 134 adult participants (70 with sleep disorder and 64 good healthy sleepers) wore an accelerometer on their wrist during a one-night polysomnography recording in the clinic. The Random forests were able to distinguish sleep-wake states with an F1 score of 73.93% on a previously unseen test set of 24 participants. Detecting when the accelerometer is not worn was also successful using machine learning ([Formula: see text]), and when combined with our sleep detection models on day-time data provide a sleep estimate that is correlated with self-reported habitual nap behaviour ([Formula: see text]). These Random forest models have been made open-source to aid further research. In line with literature, sleep stage classification turned out to be difficult using only accelerometer data.

STXBP1 Syndrome Is Characterized by Inhibition-Dominated Dynamics of Resting-State EEG.

STXBP1 syndrome is a rare neurodevelopmental disorder caused by heterozygous variants in the STXBP1 gene and is characterized by psychomotor delay, early-onset developmental delay, and epileptic encephalopathy. Pathogenic STXBP1 variants are thought to alter excitation-inhibition (E/I) balance at the synaptic level, which could impact neuronal network dynamics; however, this has not been investigated yet. Here, we present the first EEG study of patients with STXBP1 syndrome to quantify the impact of the synaptic E/I dysregulation on ongoing brain activity. We used high-frequency-resolution analyses of classical and recently developed methods known to be sensitive to E/I balance. EEG was recorded during eyes-open rest in children with STXBP1 syndrome (n = 14) and age-matched typically developing children (n = 50). Brain-wide abnormalities were observed in each of the four resting-state measures assessed here: (i) slowing of activity and increased low-frequency power in the range 1.75-4.63 Hz, (ii) increased long-range temporal correlations in the 11-18 Hz range, (iii) a decrease of our recently introduced measure of functional E/I ratio in a similar frequency range (12-24 Hz), and (iv) a larger exponent of the 1/f-like aperiodic component of the power spectrum. Overall, these findings indicate that large-scale brain activity in STXBP1 syndrome exhibits inhibition-dominated dynamics, which may be compensatory to counteract local circuitry imbalances expected to shift E/I balance toward excitation, as observed in preclinical models. We argue that quantitative EEG investigations in STXBP1 and other neurodevelopmental disorders are a crucial step to understand large-scale functional consequences of synaptic E/I perturbations.

Optimizing actigraphic estimates of polysomnographic sleep features in insomnia disorder.

STUDY OBJECTIVES: Actigraphy is a useful tool for estimating sleep, but less accurately distinguishes sleep and wakefulness in patients with insomnia disorder (ID) than in good sleepers. Specific algorithm parameter settings have been suggested to improve the accuracy of actigraphic estimates of sleep onset or nocturnal sleep and wakefulness in ID. However, a direct comparison of how different algorithm parameter settings affect actigraphic estimates of sleep features has been lacking. This study aimed to define the optimal algorithm parameter settings for actigraphic estimates of polysomnographic sleep features in people suffering from ID and matched good sleepers. METHODS: We simultaneously recorded actigraphy and polysomnography without sleep diaries during 210 laboratory nights of people with ID (n = 58) and matched controls (CTRL) without sleep complaints (n = 56). We analyzed cross-validation errors using 150 algorithm parameter configurations and Bland-Altman plots of sleep features using the optimal settings. RESULTS: Optimal sleep onset latency and total sleep time (TST) errors were lower in CTRL (8.9 ± 2.1 and 16.5 ± 2.1 min, respectively) than in ID (11.7 ± 0.8 and 29.1 ± 3.4 min). The sleep-wake algorithm, a period duration of 5 min, and a wake sensitivity threshold of 40 achieved optimal results in ID and near-optimal results in CTRL. Bland-Altman plots were nearly identical for ID and controls for all common all-night sleep features except for TST. CONCLUSION: This systematic evaluation shows that actigraphic sleep feature estimation can be improved by using uncommon parameter settings. One specific parameter setting provides (near-)optimal estimation of sleep onset and nocturnal sleep across ID and controls.

Internet-guided cognitive, behavioral and chronobiological interventions in depression-prone insomnia subtypes: protocol of a randomized controlled prevention trial.

BACKGROUND: Major depressive disorder is among the most burdening and costly chronic health hazards. Since its prognosis is poor and treatment effectiveness is moderate at best, prevention would be the strategy of first choice. Insomnia may be the best modifiable risk factor. Insomnia is highly prevalent (4-10%) and meta-analysis estimates ±13% of people with insomnia to develop depression within a year. Among people with insomnia, recent work identified three subtypes with a particularly high lifetime risk of depression. The current randomized controlled trial (RCT) evaluates the effects of internet-guided Cognitive Behavioral Therapy for Insomnia (CBT-I), Chronobiological Therapy (CT), and their combination on insomnia and the development of depressive symptoms. METHODS: We aim to include 120 participants with Insomnia Disorder (ID) of one of the three subtypes that are more prone to develop depression. In a two by two factorial repeated measures design, participants will be randomized to CBT-I, CT, CBT-I + CT or treatment as usual, and followed up for one year. The primary outcome is the change, relative to baseline, of the severity of depressive symptoms integrated over four follow-ups spanning one year. Secondary outcome measures include a diagnosis of major depressive disorder, insomnia severity, sleep diaries, actigraphy, cost-effectiveness, and brain structure and function. DISCUSSION: Pre-selection of three high-risk insomnia subtypes allows for a sensitive assessment of the possibility to prevent the development and worsening of depressive symptoms through interventions targeting insomnia. TRIAL REGISTRATION: Netherlands Trial Register (NL7359). Registered on 19 October 2018.

Dynamics of sleep: Exploring critical transitions and early warning signals.

BACKGROUND AND OBJECTIVES: In standard practice, sleep is classified into distinct stages by human observers according to specific rules as for instance specified in the AASM manual. We here show proof of principle for a conceptualization of sleep stages as attractor states in a nonlinear dynamical system in order to develop new empirical criteria for sleep stages. METHODS: EEG (single channel) of two healthy sleeping participants was used to demonstrate this conceptualization. Firstly, distinct EEG epochs were selected, both detected by a MLR classifier and through manual scoring. Secondly, change point analysis was used to identify abrupt changes in the EEG signal. Thirdly, these detected change points were evaluated on whether they were preceded by early warning signals. RESULTS: Multiple change points were identified in the EEG signal, mostly in interplay with N2. The dynamics before these changes revealed, for a part of the change points, indicators of generic early warning signals, characteristic of complex systems (e.g., ecosystems, climate, epileptic seizures, global finance systems). CONCLUSIONS: The sketched new framework for studying critical transitions in sleep EEG might benefit the understanding of individual and pathological differences in the dynamics of sleep stage transitions. Formalising sleep as a nonlinear dynamical system can be useful for definitions of sleep quality, i.e. stability and accessibility of an equilibrium state, and disrupted sleep, i.e. constant shifting between instable sleep states.

Consistent altered internal capsule white matter microstructure in insomnia disorder.

STUDY OBJECTIVES: Suggested neural correlates of insomnia disorder have been hard to replicate. Even the most consistent finding, altered white matter microstructure in the anterior limb of the internal capsule, is based on handful studies. The urge for replicable targets to understand the underlying mechanisms of insomnia made us study white matter fractional anisotropy (FA) across three samples of cases and controls. METHODS: 3-Tesla MRI diffusion tensor imaging data of three independent samples were combined for analysis, resulting in n = 137 participants, of whom 73 were diagnosed with insomnia disorder and 64 were matched controls without sleep complaints. Insomnia severity was measured with the Insomnia Severity Index (ISI). White matter microstructure was assessed with FA. White matter tracts were skeletonized and analyzed using tract-based spatial statistics. We performed a region-of-interest analysis using linear mixed-effect models to evaluate case-control differences in internal capsule FA as well as associations between internal capsule FA and insomnia severity. RESULTS: FA in the right limb of the anterior internal capsule was lower in insomnia disorder than in controls (ß = -9.76e-3; SE = 4.17e-3, p = .034). In the entire sample, a higher ISI score was associated with a lower FA value of the right internal capsule (ß = -8.05e- 4 FA/ISI point, SE = 2.60e- 4, p = .008). Ancillary whole brain voxel-wise analyses showed no significant group difference or association with insomnia severity after correction for multiple comparisons. CONCLUSIONS: The internal capsule shows small but consistent insomnia-related alterations. The findings support a circuit-based approach to underlying mechanisms since this tract connects many brain areas previously implicated in insomnia.

Actigraphic multi-night home-recorded sleep estimates reveal three types of sleep misperception in Insomnia Disorder and good sleepers.

People with Insomnia Disorder tend to underestimate their sleep compared with polysomnography or actigraphy, a phenomenon known as paradoxical insomnia or sleep-state misperception. Previous studies suggested that night-to-night variability could be an important feature differentiating subtypes of misperception. This study aimed for a data-driven definition of misperception subtypes revealed by multiple sleep features including night-to-night variability. We assessed features describing the mean and dispersion of misperception and objective and subjective sleep duration from 7-night diary and actigraphy recordings of 181 people with Insomnia Disorder and 55 people without sleep complaints. A minimally collinear subset of features was submitted to latent class analysis for data-driven subtyping. Analysis revealed three subtypes, best discriminated by three of five selected features: an individual's shortest reported subjective sleep duration; and the mean and standard deviation of misperception. These features were on average 5.4, -0.0 and 0.5 hr in one subtype accommodating the majority of good sleepers; 4.1, -1.4 and 1.0 hr in a second subtype representing the majority of people with Insomnia Disorder; and 1.7, -2.2 and 1.5 hr in a third subtype representing a quarter of people with Insomnia Disorder and hardly any good sleepers. Subtypes did not differ on an individual's objective sleep duration mean (6.9, 7.2 and 6.9 hr) and standard deviation (0.8, 0.8 and 0.9 hr). Data-driven analysis of naturalistic sleep revealed three subtypes that markedly differed in misperception features. Future studies may include misperception subtype to investigate whether it contributes to the unexplained considerable individual variability in treatment response.

Restless REM Sleep Impedes Overnight Amygdala Adaptation.

Animal studies show that insufficient silencing of the locus coeruleus (LC) during REM sleep impairs sleep-related brain plasticity. Restless REM sleep, a characteristic of several psychiatric disorders, likely reflects insufficient LC silencing. We investigated whether endogenous REM sleep interruptions interfere with overnight reorganization of limbic circuits in human volunteers with a wide range of insomnia severity, from no insomnia complaints to fulfilling community-sample criteria for insomnia disorder. We induced a self-conscious emotion during two functional MRI sessions and recorded sleep EEG in between. Amygdala reactivity decreased overnight in proportion to the total duration of consolidated REM sleep. Restless REM sleep, in contrast, impeded overnight amygdala adaptation. Using targeted memory reactivation with odors tagged to the self-conscious emotional stimulus, we could experimentally enhance both the favorable effect of consolidated REM sleep and the unfavorable effect of restless REM sleep. The findings reveal a maladaptive type of sleep, providing a target for interventions in mental disorders characterized by restless REM sleep.

Data-Driven Analysis of EEG Reveals Concomitant Superficial Sleep During Deep Sleep in Insomnia Disorder.

Study Objectives: The subjective suffering of people with Insomnia Disorder (ID) is insufficiently accounted for by traditional sleep classification, which presumes a strict sequential occurrence of global brain states. Recent studies challenged this presumption by showing concurrent sleep- and wake-type neuronal activity. We hypothesized enhanced co-occurrence of diverging EEG vigilance signatures during sleep in ID. Methods: Electroencephalography (EEG) in 55 cases with ID and 64 controls without sleep complaints was subjected to a Latent Dirichlet Allocation topic model describing each 30 s epoch as a mixture of six vigilance states called Topics (T), ranked from N3-related T1 and T2 to wakefulness-related T6. For each stable epoch we determined topic dominance (the probability of the most likely topic), topic co-occurrence (the probability of the remaining topics), and epoch-to-epoch transition probabilities. Results: In stable epochs where the N1-related T4 was dominant, T4 was more dominant in ID than in controls, and patients showed an almost doubled co-occurrence of T4 during epochs where the N3-related T1 was dominant. Furthermore, patients had a higher probability of switching from T1- to T4-dominated epochs, at the cost of switching to N3-related T2-dominated epochs, and a higher probability of switching from N2-related T3- to wakefulness-related T6-dominated epochs. Conclusion: Even during their deepest sleep, the EEG of people with ID express more N1-related vigilance signatures than good sleepers do. People with ID are moreover more likely to switch from deep to light sleep and from N2 sleep to wakefulness. The findings suggest that hyperarousal never rests in ID.

Haunted by the past: old emotions remain salient in insomnia disorder.

Studies suggest that sleep supports persistent changes in the neuronal representation of emotional experiences such that they are remembered better and less distressful when recalled than when they were first experienced. It is conceivable that sleep fragmentation by arousals, a key characteristic of insomnia disorder, could hamper the downregulation of distress. In this study, we sought further support for the idea that insomnia disorder may involve a lasting deficiency to downregulate emotional distress. We used functional MRI in insomnia disorder (n = 27) and normal sleepers (n = 30) to identify how brain activation differs between novel and relived self-conscious emotions. We evaluated whether brain activity elicited by reliving emotional memories from the distant past resembles the activity elicited by novel emotional experiences more in insomnia disorder than in normal sleepers. Limbic areas were activated during novel shameful experiences as compared to neutral experiences in both normal sleepers and insomnia disorder. In normal sleepers, reliving of shameful experiences from the past did not elicit a limbic response. In contrast, participants with insomnia disorder recruited overlapping parts of the limbic circuit, in particular the dorsal anterior cingulate cortex, during both new and relived shameful experiences. The differential activity patterns with new and old emotions in normal sleepers suggest that reactivation of the long-term memory trace does not recruit the limbic circuit. The overlap of activations in insomnia disorder is in line with the hypothesis that the disorder involves a deficiency to dissociate the limbic circuit from the emotional memory trace. Moreover, the findings provide further support for a role of the anterior cingulate cortex in insomnia.

Insomnia disorder subtypes derived from life history and traits of affect and personality.

BACKGROUND: Insomnia disorder is the second most prevalent mental disorder, and it is a primary risk factor for depression. Inconsistent clinical and biomarker findings in patients with insomnia disorder suggest that heterogeneity exists and that subtypes of this disease remain unrecognised. Previous top-down proposed subtypes in nosologies have had insufficient validity. In this large-scale study, we aimed to reveal robust subtypes of insomnia disorder by use of data-driven analyses on a multidimensional set of biologically based traits. METHODS: In this series of studies, we recruited participants from the Netherlands Sleep Registry, a database of volunteers aged 18 years or older, who we followed up online to survey traits, sleep, life events, and health history with 34 selected questionnaires of which participants completed at least one. We identified insomnia disorder subtypes by use of latent class analyses. We evaluated the value of our identified subtypes of insomnia disorder by use of a second, non-overlapping cohort who were recruited through a newsletter that was emailed to a new sample of Netherlands Sleep Registry participants, and by assessment of within-subject stability over several years of follow-up. We extensively tested the clinical validity of these subtypes for the development of sleep complaints, comorbidities (including depression), and response to benzodiazepines; in two subtypes of insomnia disorder, we also assessed the clinical relevance of these subtypes by use of an electroencephalogram biomarker and the effectiveness of cognitive behavioural therapy. To facilitate implementation, we subsequently constructed a concise subtype questionnaire and we validated this questionnaire in the second, non-overlapping cohort. FINDINGS: 4322 Netherlands Sleep Registry participants completed at least one of the selected questionnaires, a demographic questionnaire, and an assessment of their Insomnia Severity Index (ISI) between March 2, 2010, and Oct 28, 2016. 2224 (51%) participants had probable insomnia disorder, defined as an ISI score of at least 10, and 2098 (49%) participants with a lower ISI score served as a control group. With a latent class analysis of the questionnaire responses of 2224 participants, we identified five novel insomnia disorder subtypes: highly distressed, moderately distressed but reward sensitive (ie, with intact responses to pleasurable emotions), moderately distressed and reward insensitive, slightly distressed with high reactivity (to their environment and life events), and slightly distressed with low reactivity. In a second, non-overlapping replication sample of 251 new participants who were assessed between June 12, 2017, and Nov 26, 2017, five subtypes were also identified to be optimal. In both the development sample and replication sample, each participant was classified as having only one subtype with high posterior probability (0·91-1·00). In 215 of the original sample of 2224 participants with insomnia who were reassessed 4·8 (SD 1·6) years later (between April 13, 2017, and June 21, 2017), the probability of maintaining their original subtype was 0·87, indicating a high stability of the classification. We found differences between the identified subtypes in developmental trajectories, response to treatment, the presence of an electroencephalogram biomarker, and the risk of depression that was up to five times different between groups, which indicated a clinical relevance of these subtypes. INTERPRETATION: High-dimensional data-driven subtyping of people with insomnia has addressed an unmet need to reduce the heterogeneity of insomnia disorder. Subtyping facilitates identification of the underlying causes of insomnia, development of personalised treatments, and selection of patients with the highest risk of depression for inclusion in trials regarding prevention of depression. FUNDING: European Research Council and Netherlands Organization for Scientific Research.

Increased hippocampal-prefrontal functional connectivity in insomnia.

Insomnia Disorder (ID) is the second-most common mental disorder and has a far-reaching impact on daytime functioning. A meta-analysis indicates that, of all cognitive domains, declarative memory involving the hippocampus is most affected in insomnia. Hippocampal functioning has consistently been shown to be sensitive to experimental sleep deprivation. Insomnia however differs from sleep deprivation in many aspects, and findings on hippocampal structure and function have been equivocal. The present study used both structural and resting-state functional Magnetic Resonance Imaging in a larger sample than previously reported to evaluate hippocampal volume and functional connectivity in ID. Included were 65 ID patients (mean age = 48.3 y ±â€¯14.0, 17 males) and 65 good sleepers (mean age = 44.1 y ±â€¯15.2, 23 males). Insomnia severity was assessed with the Insomnia Severity Index (ISI), subjective sleep with the Consensus Sleep Diary (CSD) and objective sleep by two nights of polysomnography (PSG). Seed-based analysis showed a significantly stronger connectivity of the bilateral hippocampus with the left middle frontal gyrus in ID than in controls (p = .035, cluster based correction for multiple comparisons). Further analyses across all participants moreover showed that individual differences in the strength of this connectivity were associated with insomnia severity (ISI, r = 0.371, p = 9.3e-5) and with subjective sleep quality (CSD sleep efficiency, r = -0.307, p = .009) (all p FDR-corrected). Hippocampal volume did not differ between ID and controls. The findings indicate more severe insomnia and worse sleep quality in people with a stronger functional connectivity between the bilateral hippocampus and the left middle frontal gyrus, part of a circuit that characteristically activates with maladaptive rumination and deactivates with sleep.

EEG Microstates Indicate Heightened Somatic Awareness in Insomnia: Toward Objective Assessment of Subjective Mental Content.

People with Insomnia Disorder (ID) not only experience abundant nocturnal mentation, but also report altered spontaneous mental content during daytime wakefulness, such as an increase in bodily experiences (heightened somatic awareness). Previous studies have shown that resting-state EEG can be temporally partitioned into quasi-stable microstates, and that these microstates form a small number of canonical classes that are consistent across people. Furthermore, the microstate classes have been associated with individual differences in resting mental content including somatic awareness. To address the hypothesis that altered resting mental content in ID would be reflected in an altered representation of the corresponding EEG microstates, we analyzed resting-state high-density EEG of 32 people with ID and 32 age- and sex-matched controls assessed during 5-min eyes-closed wakefulness. Using data-driven topographical k-means clustering, we found that 5 microstate classes optimally explained the EEG scalp voltage map sequences across participants. For each microstate class, 3 dynamic features were obtained: mean duration, frequency of occurrence, and proportional coverage time. People with ID had a shorter mean duration of class C microstates, and more frequent occurrence of class D microstates. The finding is consistent with previously established associations of these microstate properties with somatic awareness, and increased somatic awareness in ID. EEG microstate assessment could provide objective markers of subjective experience dimensions in studies on consciousness during the transition between wake and sleep, when self-report is not possible because it would interfere with the very process under study. Addressing somatic awareness may benefit psychotherapeutic treatment of insomnia.

Sustained effects of prior red light on pupil diameter and vigilance during subsequent darkness.

Environmental light can exert potent effects on physiology and behaviour, including pupil size, vigilance and sleep. Previous work showed that these non-image forming effects can last long beyond discontinuation of short-wavelength light exposure. The possible functional effects after switching off long-wavelength light, however, have been insufficiently characterized. In a series of controlled experiments in healthy adult volunteers, we evaluated the effects of five minutes of intense red light on physiology and performance during subsequent darkness. As compared to prior darkness, prior red light induced a subsequent sustained pupil dilation. Prior red light also increased subsequent heart rate and heart rate variability when subjects were asked to perform a sustained vigilance task during the dark exposure. While these changes suggest an increase in the mental effort required for the task, it could not prevent a post-red slowing of response speed. The suggestion that exposure to intense red light affects vigilance during subsequent darkness, was confirmed in a controlled polysomnographic study that indeed showed a post-red facilitation of sleep onset. Our findings suggest the possibility of using red light as a nightcap.