Selective enhancement of post-sleep visual motion perception by repetitive tactile stimulation during sleep.

Tactile sensations can bias visual perception in the awake state while visual sensitivity is known to be facilitated by sleep. It remains unknown, however, whether the tactile sensation during sleep can bias the visual improvement after sleep. Here, we performed nap experiments in human participants (n = 56, 18 males, 38 females) to demonstrate that repetitive tactile motion stimulation on the fingertip during slow wave sleep selectively enhanced subsequent visual motion detection. The visual improvement was associated with slow wave activity. The high activation at the high beta frequency was found in the occipital electrodes after the tactile motion stimulation during sleep, indicating a visual-tactile cross-modal interaction during sleep. Furthermore, a second experiment (n = 14, 14 females) to examine whether a hand- or head-centered coordination is dominant for the interpretation of tactile motion direction showed that the biasing effect on visual improvement occurs according to the hand-centered coordination. These results suggest that tactile information can be interpreted during sleep, and can induce the selective improvement of post-sleep visual motion detection.Significant statement:Tactile sensations can bias our visual perception as a form of cross-modal interaction. However, it was reported only in the awake state. Here we show that repetitive directional tactile motion stimulation on the fingertip during slow wave sleep selectively enhanced subsequent visual motion perception. Moreover, the visual improvement was positively associated with sleep slow wave activity. The tactile motion stimulation during slow wave activity increased the activation at the high beta frequency over the occipital electrodes. The visual improvement occurred in agreement with a hand-centered reference frame. These results suggest that our sleeping brain can interpret tactile information based on a hand-centered reference frame, which can cause the sleep-dependent improvement of visual motion detection.

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.

Treating Insomnia with High Risk of Depression Using Therapist-Guided Digital Cognitive, Behavioral, and Circadian Rhythm Support Interventions to Prevent Worsening of Depressive Symptoms: A Randomized Controlled Trial.

INTRODUCTION: The global disease burden of major depressive disorder urgently requires prevention in high-risk individuals, such as recently discovered insomnia subtypes. Previous studies targeting insomnia with fully automated eHealth interventions to prevent depression are inconclusive: dropout was high and likely biased, and depressive symptoms in untreated participants on average improved rather than worsened. OBJECTIVE: This randomized controlled trial aimed to efficiently prevent the worsening of depressive symptoms by selecting insomnia subtypes at high risk of depression for internet-based circadian rhythm support (CRS), cognitive behavioral therapy for insomnia (CBT-I), or their combination (CBT-I+CRS), with online therapist guidance to promote adherence. METHODS: Participants with an insomnia disorder subtype conveying an increased risk of depression (n = 132) were randomized to no treatment (NT), CRS, CBT-I, or CBT-I+CRS. The Inventory of Depressive Symptomatology - Self Report (IDS-SR) was self-administered at baseline and at four follow-ups spanning 1 year. RESULTS: Without treatment, depressive symptoms indeed worsened (d = 0.28, p = 0.041) in high-risk insomnia, but not in a reference group with low-risk insomnia. Therapist-guided CBT-I and CBT-I+CRS reduced IDS-SR ratings across all follow-up assessments (respectively, d = -0.80, p = 0.001; d = -0.95, p < 0.001). Only CBT-I+CRS reduced the 1-year incidence of clinically meaningful worsening (p = 0.002). Dropout during therapist-guided interventions was very low (8%) compared to previous automated interventions (57-62%). CONCLUSIONS: The findings tentatively suggest that the efficiency of population-wide preventive strategies could benefit from the possibility to select insomnia subtypes at high risk of developing depression for therapist-guided digital CBT-I+CRS. This treatment may provide effective long-term prevention of worsening of depressive symptoms. TRIAL REGISTRATION: the Netherlands Trial Register (NL7359).

ENIGMA-Sleep: Challenges, opportunities, and the road map.

Neuroimaging and genetics studies have advanced our understanding of the neurobiology of sleep and its disorders. However, individual studies usually have limitations to identifying consistent and reproducible effects, including modest sample sizes, heterogeneous clinical characteristics and varied methodologies. These issues call for a large-scale multi-centre effort in sleep research, in order to increase the number of samples, and harmonize the methods of data collection, preprocessing and analysis using pre-registered well-established protocols. The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium provides a powerful collaborative framework for combining datasets across individual sites. Recently, we have launched the ENIGMA-Sleep working group with the collaboration of several institutes from 15 countries to perform large-scale worldwide neuroimaging and genetics studies for better understanding the neurobiology of impaired sleep quality in population-based healthy individuals, the neural consequences of sleep deprivation, pathophysiology of sleep disorders, as well as neural correlates of sleep disturbances across various neuropsychiatric disorders. In this introductory review, we describe the details of our currently available datasets and our ongoing projects in the ENIGMA-Sleep group, and discuss both the potential challenges and opportunities of a collaborative initiative in sleep medicine.

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.

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.

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.

Hyperarousal dynamics reveal an overnight increase boosted by insomnia.

Hyperarousal is a key symptom of anxiety, stress-related disorders, and insomnia. However, it has been conceptualized in many different ways, ranging from various physiological markers (e.g. cortisol levels, high-frequency EEG activity) to personality traits, or state assessments of subjective anxiety and tension. This approach resulted in partly inconsistent evidence, complicating unified interpretations. Crucially, no previous studies addressed the likely variability of hyperarousal within and across days, nor the relationship of such variability in hyperarousal with the night-by-night variability in sleep quality characteristic of insomnia. Here, we present a novel data-driven approach to understanding dynamics of state hyperarousal in insomnia. Using ecological momentary assessment, we tracked fluctuations in a wide range of emotions across 9 days in 169 people with insomnia disorders and 38 controls without sleep problems. Exploratory factor analysis identified a hyperarousal factor, comprised of items describing tension and distress. People with insomnia scored significantly higher on this factor than controls at all timepoints. In both groups, the hyperarousal factor score peaked in the morning and waned throughout the day, pointing to a potential contributing role of sleep or other circadian processes. Importantly, the overnight increase in hyperarousal was stronger in people with in insomnia than in controls. Subsequent adaptive LASSO regression analysis revealed a stronger overnight increase in hyperarousal across nights of worse subjective sleep quality. These findings demonstrate the relationship between subjective sleep quality and overnight modulations of hyperarousal. Disorders in which hyperarousal is a predominant complaint might therefore benefit from interventions focused on improving sleep quality.

Insomnia Subtypes Have Differentiating Deviations in Brain Structural Connectivity.

BACKGROUND: Insomnia disorder is the most common sleep disorder. A better understanding of insomnia-related deviations in the brain could inspire better treatment. Insufficiently recognized heterogeneity within the insomnia population could obscure detection of involved brain circuits. In the current study, we investigated whether structural brain connectivity deviations differed between recently discovered and validated insomnia subtypes. METHODS: Structural and diffusion-weighted 3T magnetic resonance imaging data from 4 independent studies were harmonized. The sample consisted of 73 control participants without sleep complaints and 204 participants with insomnia who were grouped into 5 insomnia subtypes based on their fingerprint of mood and personality traits assessed with the Insomnia Type Questionnaire. Linear regression correcting for age and sex was used to evaluate group differences in structural connectivity strength, indicated by fractional anisotropy, streamline volume density, and mean diffusivity and evaluated within 3 different atlases. RESULTS: Insomnia subtypes showed differentiating profiles of deviating structural connectivity that were concentrated in different functional networks. Permutation testing against randomly drawn heterogeneous subsamples indicated significant specificity of deviation profiles in 4 of the 5 subtypes: highly distressed, moderately distressed reward sensitive, slightly distressed low reactive, and slightly distressed high reactive. Connectivity deviation profile significance ranged from p = .001 to p = .049 for different resolutions of brain parcellation and connectivity weight. CONCLUSIONS: Our results provide an initial indication that different insomnia subtypes exhibit distinct profiles of deviations in structural brain connectivity. Subtyping insomnia may be essential for a better understanding of brain mechanisms that contribute to insomnia vulnerability.

Combining cardiac monitoring with actigraphy aids nocturnal arousal detection during ambulatory sleep assessment in insomnia.

STUDY OBJECTIVES: The objective assessment of insomnia has remained difficult. Multisensory devices collecting heart rate (HR) and motion are regarded as the future of ambulatory sleep monitoring. Unfortunately, reports on altered average HR or heart rate variability (HRV) during sleep in insomnia are equivocal. Here, we evaluated whether the objective quantification of insomnia improves by assessing state-related changes in cardiac measures. METHODS: We recorded electrocardiography, posture, and actigraphy in 33 people without sleep complaints and 158 patients with mild to severe insomnia over 4 d in their home environment. At the microscale, we investigated whether HR changed with proximity to gross (body) and small (wrist) movements at nighttime. At the macroscale, we calculated day-night differences in HR and HRV measures. For both timescales, we tested whether outcome measures were related to insomnia diagnosis and severity. RESULTS: At the microscale, an increase in HR was often detectable already 60 s prior to as well as following a nocturnal chest, but not wrist, movement. This increase was slightly steeper in insomnia and was associated with insomnia severity, but future EEG recordings are necessary to elucidate whether these changes occur prior to or simultaneously with PSG-indicators of wakefulness. At the macroscale, we found an attenuated cardiac response to sleep in insomnia: patients consistently showed smaller day-night differences in HR and HRV. CONCLUSIONS: Incorporating state-related changes in cardiac features in the ambulatory monitoring of sleep might provide a more sensitive biomarker of insomnia than the use of cardiac activity averages or actigraphy alone.

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.

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.

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.