Neuroimaging Insights into Insomnia

Insomnia subtypes have differentiating deviations in brain structural connectivity

OBJECTIVE

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. The present study investigated whether structural brain connectivity deviations differ between recently discovered and validated insomnia subtypes.

METHODS

Structural and diffusion weighted 3-Tesla MRI data of four independent studies were harmonized. The sample consisted of 73 controls without sleep complaints and 204 participants with insomnia grouped into five subtypes based on their fingerprint of mood and personality traits assessed with the Insomnia Type Questionnaire. Linear regression correcting for age and sex evaluated group differences in structural connectivity strength, indicated by fractional anisotropy, streamline volume density and mean diffusivity, and evaluated within three different atlases.

RESULTS

Insomnia subtypes showed differentiating profiles of deviating structural connectivity which concentrated in different functional networks. Permutation testing against randomly drawn heterogeneous subsamples indicated significant specificity of deviation profiles in four of the five subtypes: highly distressed, moderately distressed reward sensitive, slightly distressed low reactive and slightly distressed high reactive. Connectivity deviation profile significance ranged from p= 0.001 to p=0.049 for different resolutions of brain parcellation and connectivity weight.

CONCLUSIONS

Our results provide a first indication that different insomnia subtypes exhibit distinct profiles of deviations in structural brain connectivity. Subtyping of insomnia could be essential for a better understanding of brain mechanisms that contribute to insomnia vulnerability.

Insomnia disorder characterized by probabilistic metastable substates using blood-oxygenation-level-dependent (BOLD) phase signals

PURPOSE

From a clinical point of view, how to force a transition from insomnia brain state to healthy brain state by external driven stimulation is of great interest. This needs to define brain state of insomnia disorder as metastable substates. The current study was to identify recurrent substates of insomnia disorder in terms of probability of occurrence, lifetime, and alternation profiles by using leading eigenvector dynamics analysis (LEiDA) method.

METHODS

We enrolled 32 patients with insomnia disorder and 30 healthy subjects. We firstly obtained the BOLD phase coherence matrix from Hilbert transform of BOLD signals and then extracted all the leading eigenvectors from the BOLD phase coherence matrix for all subjects across all time points. Lastly, we clustered the leading eigenvectors using a k-means clustering algorithm to find the probabilistic metastable substates (PMS) and calculate the probability of occurrence and associated lifetime for substates.

RESULTS

The resulting 3 clusters were optimal for brain state of insomnia disorder and healthy brain state, respectively. The occurred probabilities of the PMS were significantly different between the patients with insomnia disorder and healthy subjects, with 0.51 versus 0.44 for PMS-1 (p < 0.001), 0.25 versus 0.27 for PMS-2 (p = 0.051), and 0.24 versus 0.29 for PMS-3 (p < 0.001), as well as the lifetime (in TR) of 36.65 versus 33.15 for PMS-1 (p = 0.068), 14.36 versus 15.43 for PMS-2 (p = 0.117), and 14.80 versus 16.34 for PMS-3 (p = 0.042). The values of the diagonal of the transition matrix were much higher than the probabilities of switching states, indicating the metastable nature of substates.

CONCLUSION

The resulted probabilistic metastable substates hint the characteristic brain dynamics of insomnia disorder. The results may lay a foundation to help determine how to force a transition from insomnia brain state to healthy brain state by external driven stimulation.

Preliminary investigation of the interactive role of physiological arousal and insomnia complaints in gray matter volume alterations in chronic widespread pain

STUDY OBJECTIVES

Brain regions involved in insomnia and chronic pain are overlapping and diffuse. The interactive role of physiological arousal in associations between insomnia symptoms and neural regions is unknown. This preliminary study examined whether arousal interacted with sleep in associations with gray matter volume of frontal (dorsolateral prefrontal cortex, anterior cingulate cortex) and temporal (right/left hippocampus) regions in adults with chronic widespread pain and insomnia complaints.

METHODS

Forty-seven adults with chronic widespread pain and insomnia (mean age = 46.00, standard deviation = 13.88, 89% women) completed 14 daily diaries measuring sleep onset latency (SOL), wake time after sleep onset, and total sleep time (TST), as well as Holter monitor assessments of heart rate variability (measuring physiological arousal), and magnetic resonance imaging. Multiple regressions examined whether average SOL, wake time after sleep onset, or TST were independently or interactively (with arousal/heart rate variability) associated with dorsolateral prefrontal cortex, anterior cingulate cortex, and left/right hippocampus gray matter volumes.

RESULTS

Shorter TST was associated with lower right hippocampus volume. TST also interacted with arousal in its association with right hippocampal volume, Specifically, shorter TST was associated with lower volume at highest and average arousal levels. SOL interacted with arousal in its association with anterior cingulate cortex volume, such that, among individuals with lowest arousal, longer SOL was associated with lower volume.

CONCLUSIONS

Preliminary findings highlight the interactive roles of physiological arousal and insomnia symptoms in associations with neural structure in chronic widespread pain and insomnia. Individuals with the highest physiological arousal may be particularly vulnerable to the impact of shorter TST on hippocampal volume loss. Reducing SOL may only impact anterior cingulate cortex volume in those with lower physiological arousal.

CITATION

Curtis AF, Nair N, Hayse B, et al. Preliminary investigation of the interactive role of physiological arousal and insomnia complaints in gray matter volume alterations in chronic widespread pain. J Clin Sleep Med. 2024;20(2):293-302.

Mechanisms of cognitive behavioural therapy for insomnia

Although much is known now about behavioural, cognitive and physiological consequences of insomnia, little is known about changes after cognitive behavioural therapy for insomnia on these particular factors. We here report baseline findings on each of these factors in insomnia, after which we address findings on their changes after cognitive behavioural therapy. Sleep restriction remains the strongest determinant of insomnia treatment success. Cognitive interventions addressing dysfunctional beliefs and attitudes about sleep, sleep-related selective attention, worry and rumination further drive effectiveness of cognitive behavioural therapy for insomnia. Future studies should focus on physiological changes after cognitive behavioural therapy for insomnia, such as changes in hyperarousal and brain activity, as literature on these changes is sparse. We introduce a detailed clinical research agenda on how to address this topic.

Convergent abnormality in the subgenual anterior cingulate cortex in insomnia disorder: A revisited neuroimaging meta-analysis of 39 studies

The neurobiological underpinnings of insomnia disorder (ID) are still poorly understood. A previous meta-analysis conducted by our research group in 2018 revealed no consistent regional alterations based on the limited number of eligible studies. Given the number of studies published during the last few years, we revisited the meta-analysis to provide an update to the field. Following the best-practice guidelines for conducting neuroimaging meta-analyses, we searched several databases (PubMed, Web of Science, and BrainMap) and identified 39 eligible structural and functional studies, reporting coordinates reflecting significant group differences between ID patients and healthy controls. A significant convergent regional alteration in the subgenual anterior cingulate cortex (sgACC) was observed using the activation likelihood estimation algorithm. Behavioural decoding using the BrainMap database indicated that this region is involved in fear-related emotional and cognitive processing. The sgACC showed robust task-based co-activation in meta-analytic connectivity modelling and task-free functional connectivity in a resting-state functional connectivity analysis with the main hubs of the salience and default mode networks, including the posterior cingulate cortex and dorsal ACC, amygdala, hippocampus, and medial prefrontal cortex. Collectively, the findings from this large-scale meta-analysis suggest a critical role of the sgACC in the pathophysiology of ID.

Associations between sleep health and grey matter volume in the UK Biobank cohort (n = 33 356)

As suggested by previous research, sleep health is assumed to be a key determinant of future morbidity and mortality. In line with this, recent studies have found that poor sleep is associated with impaired cognitive function. However, to date, little is known about brain structural abnormalities underlying this association. Although recent findings link sleep health deficits to specific alterations in grey matter volume, evidence remains inconsistent and reliant on small sample sizes. Addressing this problem, the current preregistered study investigated associations between sleep health and grey matter volume (139 imaging-derived phenotypes) in the UK Biobank cohort (33 356 participants). Drawing on a large sample size and consistent data acquisition, sleep duration, insomnia symptoms, daytime sleepiness, chronotype, sleep medication and sleep apnoea were examined. Our main analyses revealed that long sleep duration was systematically associated with larger grey matter volume of basal ganglia substructures. Insomnia symptoms, sleep medication and sleep apnoea were not associated with any of the 139 imaging-derived phenotypes. Short sleep duration, daytime sleepiness as well as late and early chronotype were associated with solitary imaging-derived phenotypes (no recognizable pattern, small effect sizes). To our knowledge, this is the largest study to test associations between sleep health and grey matter volume. Clinical implications of the association between long sleep duration and larger grey matter volume of basal ganglia are discussed. Insomnia symptoms as operationalized in the UK Biobank do not translate into grey matter volume findings.

Associations between insomnia symptoms and functional connectivity in the UK Biobank cohort (n = 29,423)

An increasing number of studies harness resting-state fMRI functional connectivity analysis to investigate the neurobiological mechanisms of insomnia. The results to date are inconsistent and the detection of minor and widely distributed alterations in functional connectivity requires large sample sizes. The present study investigated associations between insomnia symptoms and resting-state functional connectivity at the whole-brain level in the largest sample to date. This cross-sectional analysis used resting-state imaging data from the UK Biobank, a large scale, population-based biomedical database. The analysis included 29,423 participants (age: 63.1 ± 7.5 years, 54.3% female), comprising 9210 with frequent insomnia symptoms and 20,213 controls without. Linear models were adjusted for relevant clinical, imaging, and socio-demographic variables. The Akaike information criterion was used for model selection. Multiple comparisons were corrected using the false discovery rate with a significance level of q < 0.05. Frequent insomnia symptoms were associated with increased connectivity within the default mode network and frontoparietal network, increased negative connectivity between the default mode network and the frontoparietal network, and decreased connectivity between the salience network and a node of the default mode network. Furthermore, frequent insomnia symptoms were associated with altered functional connectivity between nodes comprising sensory areas and the cerebellum. These functional alterations of brain networks may underlie dysfunctional affective and cognitive processing in insomnia and contribute to subjectively and objectively impaired sleep. However, it must be noted that the item that was used to assess frequent insomnia symptoms in this study did not assess all the characteristics of clinically diagnosed insomnia.

Multisite test-retest reliability and compatibility of brain metrics derived from FreeSurfer versions 7.1, 6.0, and 5.3

Automatic neuroimaging processing tools provide convenient and systematic methods for extracting features from brain magnetic resonance imaging scans. One tool, FreeSurfer, provides an easy-to-use pipeline to extract cortical and subcortical morphometric measures. There have been over 25 stable releases of FreeSurfer, with different versions used across published works. The reliability and compatibility of regional morphometric metrics derived from the most recent version releases have yet to be empirically assessed. Here, we used test-retest data from three public data sets to determine within-version reliability and between-version compatibility across 42 regional outputs from FreeSurfer versions 7.1, 6.0, and 5.3. Cortical thickness from v7.1 was less compatible with that of older versions, particularly along the cingulate gyrus, where the lowest version compatibility was observed (intraclass correlation coefficient 0.37-0.61). Surface area of the temporal pole, frontal pole, and medial orbitofrontal cortex, also showed low to moderate version compatibility. We confirm low compatibility between v6.0 and v5.3 of pallidum and putamen volumes, while those from v7.1 were compatible with v6.0. Replication in an independent sample showed largely similar results for measures of surface area and subcortical volumes, but had lower overall regional thickness reliability and compatibility. Batch effect correction may adjust for some inter-version effects when most sites are run with one version, but results vary when more sites are run with different versions. Age associations in a quality controlled independent sample (N = 106) revealed version differences in results of downstream statistical analysis. We provide a reference to highlight the regional metrics that may yield recent version-related inconsistencies in published findings. An interactive viewer is provided at http://data.brainescience.org/Freesurfer_Reliability/.

Diagnostic identification of chronic insomnia using ALFF and FC features of resting-state functional MRI and logistic regression approach

This study investigated whether the amplitude of low-frequency fluctuation (ALFF) and functional connectivity (FC) features could be used as potentially neurological markers to identify chronic insomnia (CI) using resting-state functional MRI and machine learning method logistic regression (LR). This study included 49 CI patients and 47 healthy controls (HC). Voxel-wise features, including the amplitude of low-frequency fluctuations (ALFF) and functional connectivity (FC), were extracted from resting-state functional magnetic resonance brain images. Then, we divided the data into two independent cohorts for training (44 CI patients and 42 HC patients), and independent validation (5 CI patients and 5 HC patients) by using logistic regression. The model was evaluated using 20 rounds of fivefold cross‑validation for training. In particular, a two-sample t-test (GRF corrected, p-voxel < 0.001, p-cluster < 0.05) was used for feature selection during the model training. Finally, single‑shot testing of the final model was performed on the independent validation cohort. A correlation analysis (Bonferroni correction, p < 0.05/4) was also conducted to determine whether the features contributing to the prediction were correlated with clinical characteristics, including the Insomnia Severity Index (ISI), Pittsburgh sleep quality index (PSQI), self-rating anxiety scale (SAS), and self-rating depression scale (SDS). Results showed that resting-state features had a discrimination accuracy of 86.40%, with a sensitivity of 93.00% and specificity of 79.80%. The area under the curve (AUC) was 0.89 (all [Formula: see text]< 0.001). The ALFF and FC features showed significant differences between the CI patients and HC. The regions contributing to the prediction mainly included the anterior cingulate, prefrontal cortex, orbital part of the frontal lobe, angular gyrus, cingulate gyrus, praecuneus, parietal lobe, temporal gyrus, superior temporal gyrus, and middle temporal gyrus. Furthermore, some specific functional connectivity among related regions was positively correlated with the ISI, and also negatively related to the SDS in correlation analysis. Our current study suggested that ALFF and FC in the regions contributing to diagnostic identification might serve as potential neuromarkers for CI.

Functional connectivity changes are correlated with sleep improvement in chronic insomnia patients after rTMS treatment

Background

Repetitive transcranial magnetic stimulation (rTMS) has been increasingly used as a treatment modality for chronic insomnia disorder (CID). However, our understanding of the mechanisms underlying the efficacy of rTMS is limited.

Objective

This study aimed to investigate rTMS-induced alterations in resting-state functional connectivity and to find potential connectivity biomarkers for predicting and tracking clinical outcomes after rTMS.

Methods

Thirty-seven patients with CID received a 10-session low frequency rTMS treatment applied to the right dorsolateral prefrontal cortex. Before and after treatment, the patients underwent resting-state electroencephalography recordings and a sleep quality assessment using the Pittsburgh Sleep Quality Index (PSQI).

Results

After treatment, rTMS significantly increased the connectivity of 34 connectomes in the lower alpha frequency band (8-10 Hz). Additionally, alterations in functional connectivity between the left insula and the left inferior eye junction, as well as between the left insula and medial prefrontal cortex, were associated with a decrease in PSQI score. Further, the correlation between the functional connectivity and PSQI persisted 1 month after the completion of rTMS as evidenced by subsequent electroencephalography (EEG) recordings and the PSQI assessment.

Conclusion

Based on these results, we established a link between alterations in functional connectivity and clinical outcomes of rTMS, which suggested that EEG-derived functional connectivity changes were associated with clinical improvement of rTMS in treating CID. These findings provide preliminary evidence that rTMS may improve insomnia symptoms by modifying functional connectivity, which can be used to inform prospective clinical trials and potentially for treatment optimization.

Associations Between Sleep Health and Amygdala Reactivity to Negative Facial Expressions in the UK Biobank Cohort

BACKGROUND

Sleep health (SH) is considered a key determinant of human physiological and psychological well-being. In line with this, previous studies have found that poor sleep is associated with various psychiatric disorders, in particular, with anxiety and depression. Although little is known about the neural mechanisms underlying these associations, recent findings suggest that essential dimensions of SH are associated with altered amygdala reactivity (AR); however, evidence to date is inconsistent and reliant on small sample sizes.

METHODS

To address this problem, the current preregistered study investigated associations between SH and AR to negative facial expressions in the UK Biobank cohort (25,758 participants). Drawing on a large sample size and consistent data acquisition, 5 dimensions of SH (insomnia symptoms, sleep duration, daytime sleepiness, chronotype, and sleep medication) were examined.

RESULTS

Exploratory analyses revealed that short sleep duration was associated with decreased AR. The remaining SH dimensions and a composite measure of all SH dimensions were not associated with AR.

CONCLUSIONS

To our knowledge, this is the largest study to test associations between SH and AR. Habitual short sleep duration may be associated with decreased AR, possibly indicating compensation for impaired prefrontal processes and hampered emotion regulation.

Genome-wide meta-analysis of insomnia prioritizes genes associated with metabolic and psychiatric pathways

Insomnia is a heritable, highly prevalent sleep disorder for which no sufficient treatment currently exists. Previous genome-wide association studies with up to 1.3 million subjects identified over 200 associated loci. This extreme polygenicity suggested that many more loci remain to be discovered. The current study almost doubled the sample size to 593,724 cases and 1,771,286 controls, thereby increasing statistical power, and identified 554 risk loci (including 364 novel loci). To capitalize on this large number of loci, we propose a novel strategy to prioritize genes using external biological resources and functional interactions between genes across risk loci. Of all 3,898 genes naively implicated from the risk loci, we prioritize 289 and find brain-tissue expression specificity and enrichment in specific gene sets of synaptic signaling functions and neuronal differentiation. We show that this novel gene prioritization strategy yields specific hypotheses on underlying mechanisms of insomnia that would have been missed by traditional approaches.

Topologically Disrupted Gray Matter Networks in Drug-Naïve Essential Tremor Patients With Poor Sleep Quality

Background

Sleep disturbances are widespread among patients with essential tremor (ET) and may have adverse effects on patients' quality of life. However, the pathophysiology underlying poor quality of sleep (QoS) in patients with ET remains unclear. Our study aimed to identify gray matter (GM) network alterations in the topological properties of structural MRI related to QoS in patients with ET.

Method

We enrolled 45 ET patients with poor QoS (SleET), 59 ET patients with normal QoS (NorET), and 66 healthy controls (HC), and they all underwent a three-dimensional T1-weighted MRI scan. We used a graph-theoretical approach to investigate the topological organization of GM morphological networks, and individual morphological brain networks were constructed according to the interregional similarity of GM volume distributions. Furthermore, we performed network-based statistics, and partial correlation analyses between topographic features and clinical characteristics were conducted.

Results

Global network organization was disrupted in patients with ET. Compared with the NorET group, the SleET group exhibited disrupted topological GM network organization with a shift toward randomization. Moreover, they showed altered nodal centralities in mainly the frontal, temporal, parietal, and cerebellar lobes. Morphological connection alterations within the default mode network (DMN), salience, and basal ganglia networks were observed in the SleET group and were generally more extensive than those in the NorET and HC groups. Alterations within the cerebello-thalamo-(cortical) network were only detected in the SleET group. The nodal degree of the left thalamus was negatively correlated with the Fahn-Tolosa-Marin Tremor Rating Scale score (r = −0.354, p =0.027).

Conclusion

Our findings suggest that potential complex interactions underlie tremor and sleep disruptions in patients with ET. Disruptions within the DMN and the cerebello-thalamo-(cortical) network may have a broader impact on sleep quality in patients with ET. Our results offer valuable insight into the neural mechanisms underlying poor QoS in patients with ET.

Disrupted Brain Functional Network Topology in Essential Tremor Patients With Poor Sleep Quality

Sleep disturbances, especially poor quality of sleep (QoS), are common among essential tremor (ET) patients and may have adverse effects on their quality of life, but the etiology driving the poor QoS in these individuals remains inadequately understood. Few data are available on the neuroimaging alterations of ET with poor QoS. Thirty-eight ET patients with poor QoS (SleET), 48 ET patients with normal QoS (NorET), and 80 healthy controls (HCs) participated in this study. All subjects underwent a 3.0-T magnetic resonance imaging (MRI) scan for resting-state functional MRI data collection. Then, the whole-brain functional connectome was constructed by thresholding the partial correlation matrices of 116 brain regions. Graph theory and network-based statistical analyses were performed. We used a non-parametric permutation test for group comparisons of topological metrics. Partial correlation analyses between the topographical features and clinical characteristics were conducted. The SleET and NorET groups exhibited decreased clustering coefficients, global efficiency, and local efficiency and increased the characteristic path length. Both of these groups also showed reduced nodal degree and nodal efficiency in the left superior dorsolateral frontal gyrus, superior frontal medial gyrus (SFGmed), posterior cingulate gyrus (PCG), lingual gyrus, superior occipital gyrus, right middle occipital gyrus, and right fusiform gyrus. The SleET group additionally presented reduced nodal degrees and nodal efficiency in the right SFGmed relative to the NorET and HC groups, and nodal efficiency in the right SFGmed was negatively correlated with the Pittsburgh Sleep Quality Index score. The observed impaired topographical organizations of functional brain networks within the central executive network (CEN), default mode network (DMN), and visual network serve to further our knowledge of the complex interactions between tremor and sleep, adding to our understanding of the underlying neural mechanisms of ET with poor QoS.

Real-Time fMRI Neurofeedback Training Changes Brain Degree Centrality and Improves Sleep in Chronic Insomnia Disorder: A Resting-State fMRI Study

Background

Chronic insomnia disorder (CID) is considered a major public health problem worldwide. Therefore, innovative and effective technical methods for studying the pathogenesis and clinical comprehensive treatment of CID are urgently needed.

Methods

Real-time fMRI neurofeedback (rtfMRI-NF), a new intervention, was used to train 28 patients with CID to regulate their amygdala activity for three sessions in 6 weeks. Resting-state fMRI data were collected before and after training. Then, voxel-based degree centrality (DC) method was used to explore the effect of rtfMRI-NF training. For regions with altered DC, we determined the specific connections to other regions that most strongly contributed to altered functional networks based on DC. Furthermore, the relationships between the DC value of the altered regions and changes in clinical variables were determined.

Results

Patients with CID showed increased DC in the right postcentral gyrus, Rolandic operculum, insula, and superior parietal gyrus and decreased DC in the right supramarginal gyrus, inferior parietal gyrus, angular gyrus, middle occipital gyrus, and middle temporal gyrus. Seed-based functional connectivity analyses based on the altered DC regions showed more details about the altered functional networks. Clinical scores in Pittsburgh sleep quality index, insomnia severity index (ISI), Beck depression inventory, and Hamilton anxiety scale decreased. Furthermore, a remarkable positive correlation was found between the changed ISI score and DC values of the right insula.

Conclusions

This study confirmed that amygdala-based rtfMRI-NF training altered the intrinsic functional hubs, which reshaped the abnormal functional connections caused by insomnia and improved the sleep of patients with CID. These findings contribute to our understanding of the neurobiological mechanism of rtfMRI-NF in insomnia treatment. However, additional double-blinded controlled clinical trials with larger sample sizes need to be conducted to confirm the effect of rtfMRI-NF from this initial study.

Self-Reported Sleep Quality Across Age Modulates Resting-State Functional Connectivity in Limbic and Fronto-Temporo-Parietal Networks: An Exploratory Cross-Sectional fMRI Study

Sleep problems are increasingly present in the general population at any age, and they are frequently concurrent with—or predictive of—memory disturbances, anxiety, and depression. In this exploratory cross-sectional study, 54 healthy participants recruited in Naples (Italy; 23 females; mean age = 37.1 years, range = 20–68) completed the Pittsburgh Sleep Quality Index (PSQI) and a neurocognitive assessment concerning both verbal and visuospatial working memory as well as subjective measures of anxiety and depression. Then, 3T fMRI images with structural and resting-state functional sequences were acquired. A whole-brain seed-to-seed functional connectivity (FC) analysis was conducted by contrasting good (PSQI score <5) vs. bad (PSQI score ≥5) sleepers. Results highlighted FC differences in limbic and fronto-temporo-parietal brain areas. Also, bad sleepers showed an anxious/depressive behavioural phenotype and performed worse than good sleepers at visuospatial working-memory tasks. These findings may help to reveal the effects of sleep quality on daily-life cognitive functioning and further elucidate pathophysiological mechanisms of sleep disorders.

Improved Regional Homogeneity in Chronic Insomnia Disorder After Amygdala-Based Real-Time fMRI Neurofeedback Training

BACKGROUND

Chronic insomnia disorder (CID) is a highly prevalent sleep disorder, which influences people's daily life and is even life threatening. However, whether the resting-state regional homogeneity (ReHo) of disrupted brain regions in CID can be reshaped to normal after treatment remains unclear.

METHODS

A novel intervention real-time functional magnetic resonance imaging neurofeedback (rtfMRI-NF) was used to train 28 CID patients to regulate the activity of the left amygdala for three sessions in 6 weeks. The ReHo methodology was adopted to explore its role on resting-state fMRI data, which were collected before and after training. Moreover, the relationships between changes of clinical variables and ReHo value of altered regions were determined.

RESULTS

Results showed that the bilateral dorsal medial pre-frontal cortex, supplementary motor area (SMA), and left dorsal lateral pre-frontal cortex had decreased ReHo values, whereas the bilateral cerebellum anterior lobe (CAL) had increased ReHo values after training. Some clinical scores markedly decreased, including Pittsburgh Sleep Quality Index, Insomnia Severity Index, Beck Depression Inventory, and Hamilton Anxiety Scale (HAMA). Additionally, the ReHo values of the left CAL were positively correlated with the change in the Hamilton depression scale score, and a remarkable positive correlation was found between the ReHo values of the right SMA and the HAMA score.

CONCLUSION

Our study provided an objective evidence that amygdala-based rtfMRI-NF training could reshape abnormal ReHo and improve sleep in patients with CID. The improved ReHo in CID provides insights into the neurobiological mechanism for the effectiveness of this intervention. However, larger double-blinded sham-controlled trials are needed to confirm our results from this initial study.

Functional Connectivity Disturbances of the Locus Coeruleus in Chronic Insomnia Disorder

INTRODUCTION

In recent years, people have gained a profound understanding of chronic insomnia disorder (CID), but the pathophysiological mechanism of CID is still unclear. There is some evidence that the locus coeruleus (LC) is involved in the regulation of wakefulness in CID, but there have been few studies using brain functional imaging. The purpose of this study was to evaluate the resting-state functional connectivity (FC) between the LC and other brain voxels in CID and whether these abnormal FC are involved in the regulation of wakefulness.

METHODS

A total of 49 patients with chronic insomnia disorder and 47 healthy controls (HC) matched for gender, age, and education were examined with rs-fMRI in this study. The LC was selected as the region of interest, and then seed-based analysis was conducted on the LC and other voxels to obtain the brain regions with abnormal FC. The correlation between the FC value of the abnormal connection area and the clinical scale score was analyzed.

RESULTS

Compared with the HC, the FC between the LC and right precuneus, right posterior cingulate cortex, left middle temporal gyrus, left calcarine, and right superior orbitofrontal cortex was significantly enhanced (p < 0.05, FDR correction), and the functional connectivity signal value between the locus coeruleus and left middle temporal gyrus was positively correlated with the Self-Rating Depression Scale (p = 0.021).

CONCLUSION

The abnormal FC between the LC and multiple brain regions may contribute to a better understanding of the neurobiological mechanism of CID.

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.

Presleep physiological stress is associated with a higher cortical arousal in sleep and more consolidated REM sleep

How sleep regulates physiological stress in healthy individuals is not well understood. We explored the associations between naturally occurring pre-sleep physiological arousal and EEG power spectral density together with rapid eye movement sleep (REMS) continuity. One hundred and fifty-four individuals (mean age 16.9, SD 0.1 years) collected five samples of saliva between the evening (mean time 18:20) and bedtime (mean 23:00) by using swabs, and underwent an overnight in-home polysomnography. We calculated spectral density for REMS and non-rapid eye movement sleep (non-REMS), and the number and duration of REMS arousals (<15 s) during sleep. An observational design allowed for measurement of natural variation in physiological and sleep arousal. Increasing cortisol levels toward bedtime were associated with higher EEG power spectral density at all frequency ranges in frontal locations, the highest association being for the beta1 frequency band. In central locations, the associations were pronounced for beta1 and beta2 bands. Higher overall cortisol levels in the evening were associated with less fragmented REMS. Presleep arousal was not associated with sleep staging. Physiological arousal toward bedtime was associated with EEG power spectral density values during sleep specifically at high EEG frequencies. This may represent a compensatory mechanism that serves as an adaptation to stress, since the REMS was more continuous along a higher physiological arousal level in the evening. Although causality cannot be inferred, a design with nonmanipulated physiological stress followed by naturally timed sleep at home provides new insights into stress regulation homeostasis.

Revisiting nocturnal heart rate and heart rate variability in insomnia: A polysomnography-based comparison of young self-reported good and poor sleepers

Primary insomnia is often considered a disorder of 24-hr hyperarousal. Numerous attempts have been made to investigate nocturnal heart rate (HR) and its variability (HRV) as potential pathophysiological hallmarks of altered arousal levels in insomnia, with mixed results. We have aimed to overcome some of the pitfalls of previous studies by using a young, medication-free, age- and gender-matched population consisting of 43 students aged 18-30 years half with a subthreshold insomnia complaint. We employed at-home ambulatory polysomnography and compared this attenuated insomnia group to a good sleeping group. The poor sleepers had significantly higher wake after sleep onset, arousal count, mean HR in all sleep stages (with the exception of Stage 1) and lower sleep efficiency. Consistent with previous research, we also found a significant group-by-sleep stage interaction in the prediction of nocturnal HR, highlighting the insomnia group to have a lower wake-sleep HR reduction compared to good sleepers. When restricting our analyses to insomnia with objectively determined short sleep duration, we found significantly lower standard deviation of RR intervals (SDNN; a measure of HRV) compared to good sleepers. Taken together, this lends credence to the hyperarousal model of insomnia and may at least partially explain the increased prevalence of cardiovascular morbidity and mortality observed in patients with insomnia.

Gray matter hypertrophy in primary insomnia: a surface-based morphometric study

Studies have explored brain structural abnormalities in patients with primary insomnia (PI). However, most of them are based on volumetric measures, in a specific region of interest, and have small sample sizes. Here, we investigated changes in cortical morphology (thickness and volume) in PI using an advanced surface-based morphometric method. Sixty-seven patients with PI and 55 matched healthy controls were recruited for this study and underwent a structural magnetic resonance imaging scan. The reconstructed cortical surface was processed by Freesurfer 6.0. A general linear model was used to explore group differences in surface-based morphometric features. Furthermore, the association between these cortical features and clinical characteristics were assessed in the PI group. Compared to controls, PI patients showed cortical thickening in the left orbital frontal cortex (OFC), right rostral anterior cingulate cortex (rACC), left middle cingulate cortex (MCC), bilateral insula, left superior parietal lobule (SPL), and right fusiform area (FFA), and showed increased cortical volume in the left OFC, right rACC, bilateral rostral middle frontal gyrus, and right FFA. Cortical thickness in the right OFC and FFA was positively correlated with the severity of insomnia in the PI group, suggesting a right-lateralized relationship. This study was the first to explore multiple-scale cortical morphometric changes in a relatively large sample of PI patients. Our results suggest that hypertrophic cortical morphology may underlie the neuropathology of primary insomnia.

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 (β = -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 (β = -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.

[Small-world network of patients with primary insomnia: a resting-state functional magnetic resonance imaging study]

OBJECTIVE

To explore the changes of small-world network properties in patients with primary insomnia based on resting-state functional magnetic resonance imaging (rs-fMRI).

OBJECTIVE

The rs-MRI data and neurological scale data of 65 patients and 60 matched healthy controls were collected. The brain network was constructed using GRENTA software. SPSS software and network-based statistical analysis methods were used for statistical analysis.

OBJECTIVE

There was no significant difference between the two groups in terms of age, gender or education level (P > 0.05), but PSQI, HAMA and HAMD scale scores differed significantly between the two groups (P < 0.05). Both of the groups showed attributes of the small-world network. Compared with the control group, the patients with insomnia showed lower Cp, γ, Eloc, λ, connectivity, and σ of the small world network (P < 0.05).

OBJECTIVE

Patients with primary insomnia have lower global and local efficiencies than healthy individuals, and their ability to transmit information on the surface topology is impaired. Our data provide objective imaging evidences for the neuropathological mechanism of patients with primary insomnia.

Alterations of Subcortical Brain Structures in Paradoxical and Psychophysiological Insomnia Disorder

Insomnia disorder (ID) is a common illness associated with mood and cognitive impairments. Subtyping ID is an ongoing debate in sleep medicine, but the underlying mechanisms of each subtype is poorly understood. Growing evidence suggests that subcortical brain structures play the key roles in pathophysiology of ID and its subtypes. Here, we aimed to investigate structural alteration of subcortical regions in patients with two common ID subtypes i.e., paradoxical and psychophysiological insomnia. Fifty-five patients and 49 healthy controls were recruited for this study and T1-weighted images and subjective and objective sleep parameters (i.e., Pittsburgh Sleep Quality Index and polysomnography) were collected from participants. Subcortical structures including the hippocampus, amygdala, caudate, putamen, globus pallidus, nucleus accumbens, and thalamus were automatically segmented in FSL. Volume and shape (using surface vertices) of each structure were compared between the groups, controlled for covariates, and corrected for multiple comparisons. In addition, correlations of sleep parameters and surface vertices or volumes were calculated. The caudate's volume was smaller in patients than controls. Compared with controls, we found regional shrinkage in the caudate, nucleus accumbens, posterior putamen, hippocampus, thalamus, and amygdala in paradoxical insomnia and shrinkage in the amygdala, caudate, hippocampus, and putamen in psychophysiological insomnia. Interestingly, comparing two patients groups, shape alteration in the caudate, putamen, and nucleus accumbens in paradoxical insomnia and shrinkage in the thalamus, amygdala, and hippocampus in psychophysiological insomnia were observed. Both subjective and objective sleep parameters were associated with these regional shape alterations in patients. Our results support the differential role of subcortical brain structures in pathophysiology of paradoxical and psychophysiological insomnia.

Cost-effectiveness of neuroimaging technologies in management of psychiatric and insomnia disorders: A meta-analysis and prospective cost analysis

BACKGROUND

The optimal diagnostic strategy for patients with psychiatric and insomnia disorders has not been established yet.

PURPOSE

The purpose of this study was to perform cost-effectiveness analysis of six neuroimaging technologies in diagnosis of patients with psychiatric and insomnia disorders.

METHODS

An economic evaluation study was conducted in three parts, including a systematic review for determining diagnostic accuracy, a descriptive cross-sectional study with Activity-Based Costing (ABC) technique for tracing resource consumption, and a cost-effectiveness analysis using a short-term decision-analytic model.

RESULTS

In the first phase, 93 diagnostic accuracy studies were included in the systematic review. The accumulated results (meta-analysis) showed that the highest diagnostic accuracy for psychiatric and insomnia disorders was attributed to PET (sensitivity of 90% and specificity of 80%) and MRI (sensitivity of 76% and specificity of 78%) respectively. In the second phase of the study, we calculated the cost of each technology. The results showed that MRI has the lowest cost. Based on the results in the model of cost-effectiveness sMRI ($ 50.08 per accurate diagnosis) and MRI ($ 58.54 per accurate diagnosis) were more cost-effective neuroimaging technologies.

CONCLUSION

In psychiatric disorders, no single strategy was characterized by both low cost and high accuracy. However, MRI and PET scan had lower cost and higher accuracy for psychiatric disorders, respectively. MRI was the least costly with the highest diagnostic accuracy in insomnia disorders. Based on our model, sMRI in psychiatric disorders and MRI in insomnia disorders were the most cost-effective technologies.

Altered thalamic connectivity in insomnia disorder during wakefulness and sleep

Insomnia disorder is the most common sleep disorder and has drawn increasing attention. Many studies have shown that hyperarousal plays a key role in the pathophysiology of insomnia disorder. However, the specific brain mechanisms underlying insomnia disorder remain unclear. To elucidate the neuropathophysiology of insomnia disorder, we investigated the brain functional networks of patients with insomnia disorder and healthy controls across the sleep–wake cycle. EEG‐fMRI data from 33 patients with insomnia disorder and 31 well‐matched healthy controls during wakefulness and nonrapid eye movement sleep, including N1, N2 and N3 stages, were analyzed. A medial and anterior thalamic region was selected as the seed considering its role in sleep–wake regulation. The functional connectivity between the thalamic seed and voxels across the brain was calculated. ANOVA with factors “group” and “stage” was performed on thalamus‐based functional connectivity. Correlations between the misperception index and altered functional connectivity were explored. A group‐by‐stage interaction was observed at widespread cortical regions. Regarding the main effect of group, patients with insomnia disorder demonstrated decreased thalamic connectivity with the left amygdala, parahippocampal gyrus, putamen, pallidum and hippocampus across wakefulness and all three nonrapid eye movement sleep stages. The thalamic connectivity in the subcortical cluster and the right temporal cluster in N1 was significantly correlated with the misperception index. This study demonstrated the brain functional basis in insomnia disorder and illustrated its relationship with sleep misperception, shedding new light on the brain mechanisms of insomnia disorder and indicating potential therapeutic targets for its treatment.

What Is the Link Between Attention-Deficit/Hyperactivity Disorder and Sleep Disturbance? A Multimodal Examination of Longitudinal Relationships and Brain Structure Using Large-Scale Population-Based Cohorts

BACKGROUND

Attention-deficit/hyperactivity disorder (ADHD) comorbid with sleep disturbances can produce profound disruption in daily life and negatively impact quality of life of both the child and the family. However, the temporal relationship between ADHD and sleep impairment is unclear, as are underlying common brain mechanisms.

METHODS

This study used data from the Quebec Longitudinal Study of Child Development (n = 1601, 52% female) and the Adolescent Brain Cognitive Development Study (n = 3515, 48% female). Longitudinal relationships between symptoms were examined using cross-lagged panel models. Gray matter volume neural correlates were identified using linear regression. The transcriptomic signature of the identified brain-ADHD-sleep relationship was characterized by gene enrichment analysis. Confounding factors, such as stimulant drugs for ADHD and socioeconomic status, were controlled for.

RESULTS

ADHD symptoms contributed to sleep disturbances at one or more subsequent time points in both cohorts. Lower gray matter volumes in the middle frontal gyrus and inferior frontal gyrus, amygdala, striatum, and insula were associated with both ADHD symptoms and sleep disturbances. ADHD symptoms significantly mediated the link between these structural brain abnormalities and sleep dysregulation, and genes were differentially expressed in the implicated brain regions, including those involved in neurotransmission and circadian entrainment.

CONCLUSIONS

This study indicates that ADHD symptoms and sleep disturbances have common neural correlates, including structural changes of the ventral attention system and frontostriatal circuitry. Leveraging data from large datasets, these results offer new mechanistic insights into this clinically important relationship between ADHD and sleep impairment, with potential implications for neurobiological models and future therapeutic directions.

Brain mechanisms of insomnia: new perspectives on causes and consequences

While insomnia is the second most common mental disorder, progress in our understanding of underlying neurobiological mechanisms has been limited. The present review addresses the definition and prevalence of insomnia and explores its subjective and objective characteristics across the 24-hour day. Subsequently, the review extensively addresses how the vulnerability to develop insomnia is affected by genetic variants, early life stress, major life events, and brain structure and function. Further supported by the clear mental health risks conveyed by insomnia, the integrated findings suggest that the vulnerability to develop insomnia could rather be found in brain circuits regulating emotion and arousal than in circuits involved in circadian and homeostatic sleep regulation. Finally, a testable model is presented. The model proposes that in people with a vulnerability to develop insomnia, the locus coeruleus is more sensitive to-or receives more input from-the salience network and related circuits, even during rapid eye movement sleep, when it should normally be sound asleep. This vulnerability may ignite a downward spiral of insufficient overnight adaptation to distress, resulting in accumulating hyperarousal, which, in turn, impedes restful sleep and moreover increases the risk of other mental health adversity. Sensitized brain circuits are likely to be subjectively experienced as "sleeping with one eye open". The proposed model opens up the possibility for novel intervention studies and animal studies, thus accelerating the ignition of a neuroscience of insomnia, which is direly needed for better treatment.

Cognitive behavioural therapy for insomnia does not appear to have a substantial impact on early markers of cardiovascular disease: A preliminary randomized controlled trial

According to the World Health Organization, cardiovascular diseases are the leading cause of death in the world. Therefore, early prevention of these diseases is a public health priority. Epidemiological data suggest that insomnia may be a modifiable risk factor for cardiovascular diseases. A randomized controlled trial in a sample of insomnia patients without cardiovascular disease was conducted to investigate the effects of insomnia treatment on early markers of cardiovascular diseases assessed by 24-hr ambulatory blood pressure, heart rate and heart rate variability monitoring, and morning fasting blood samples. Forty-six patients with insomnia disorder were randomized to cognitive behavioural therapy for insomnia (CBT-I; n = 23) or a waitlist control condition (n = 23). Contrary to the hypothesis, intention-to-treat analyses did not show any significant treatment effects on early markers of cardiovascular disease (d = 0.0-0.6) despite successful insomnia treatment (d = 1.3). Potential methodological and conceptual reasons for these negative findings are discussed. Future studies might include larger sample sizes that are at risk of cardiovascular diseases and focus on other cardiovascular markers.

The effects of digital cognitive behavioral therapy for insomnia on cognitive function: a randomized controlled trial

Study Objectives

We sought to examine the impact of digital cognitive behavioral therapy (dCBT) for insomnia on both self-reported cognitive impairment and objective cognitive performance.

Methods

The Defining the Impact of Sleep improvement on Cognitive Outcomes (DISCO) trial was an online, two-arm, single-blind, randomized clinical trial of dCBT versus wait-list control. Participants were aged 25 years and older, met DSM-5 diagnostic criteria for insomnia disorder, and reported difficulties with concentration or memory. Assessments were carried out online at baseline, and 10 and 24 weeks post-randomization. The primary outcome measure was self-reported cognitive impairment, assessed with the British Columbia Cognitive Complaints Inventory (BC-CCI). Secondary outcomes included tests of cognitive performance, insomnia symptoms, cognitive failures, fatigue, sleepiness, depression, and anxiety.

Results

Four hundred and ten participants with insomnia were recruited and assigned to dCBT (N = 205) or wait-list control (N = 205). At 10 weeks post-randomization the estimated adjusted mean difference for the BC-CCI was −3.03 (95% CI: −3.60, −2.47; p &lt; 0.0001, d = −0.86), indicating that participants in the dCBT group reported less cognitive impairment than the control group. These effects were maintained at 24 weeks (d = −0.96) and were mediated, in part, via reductions in insomnia severity and increased sleep efficiency. Treatment effects in favor of dCBT, at both 10 and 24 weeks, were found for insomnia severity, sleep efficiency, cognitive failures, fatigue, sleepiness, depression, and anxiety. We found no between-group differences in objective tests of cognitive performance.

Conclusions

Our study shows that dCBT robustly decreases self-reported cognitive impairment at post-treatment and these effects are maintained at 6 months.

Neuroimaging insights into the link between depression and Insomnia: A systematic review

BACKGROUND

Insomnia is a common symptom of Major Depressive Disorder (MDD) and genome-wide association studies pointed to their strong genetic association. Although the prevalence of insomnia symptoms in MDD is noticeable and evidence supports their strong bidirectional association, the number of available neuroimaging findings on patients of MDD with insomnia symptoms is limited. However, such neuroimaging studies could verily improve our understanding of their shared pathophysiology and advance corresponding theories.

METHODS

Based on the preferred reporting items for systematic reviews and meta-analysis (PRISMA) guideline, we have conducted a literature search using PubMed, EMBASE, and Scopus databases and systematically explored 640 studies using various neuroimaging modalities in MDD patients with different degrees of insomnia symptoms.

RESULTS

Despite inconsistencies, current findings from eight studies suggested structural and functional disturbances in several brain regions including the amygdala, prefrontal cortex and anterior cingulate cortex and insula. The aberrant functional connectivity within and between the main hubs of the salience and default mode networks could potentially yield new insights into the link between MDD and insomnia, which needs further assessment.

LIMITATIONS

The number of studies reviewed herein is limited. The applied methods for assessing structural and functional neural mechanisms of insomnia and depression were variable.

CONCLUSION

Neuroimaging methods demonstrated the overlapping underlying neural mechanisms between MDD and insomnia. Future studies may facilitate better understanding of their pathophysiology to allow development of specific treatment.

Sleep and brain morphological changes in the eighth decade of life

OBJECTIVE

Sleep is important for brain health. We analysed associations between usual sleep habits and magnetic resonance imaging (MRI) markers of neurodegeneration (brain atrophy), vascular damage (white matter hyperintensities, WMH) and waste clearance (perivascular spaces, PVS) in older community-dwelling adults.

METHOD

We collected self-reported usual sleep duration, quality and medical histories from the Lothian Birth Cohort 1936 (LBC1936) age 76 years and performed brain MRI. We calculated sleep efficiency, measured WMH and brain volumes, quantified PVS, and assessed associations between sleep measures and brain markers in multivariate models adjusted for demographic and medical history variables.

RESULTS

In 457 subjects (53% males, mean age 76 ± 0.65 years), we found: brain and white matter loss with increased weekend daytime sleep (β = -0.114, P = 0.03; β = -0.122, P = 0.007 respectively), white matter loss with less efficient sleep (β = 0.132, P = 0.011) and PVS increased with interrupted sleep (OR 1.84 95% CI, P = 0.025).

CONCLUSION

Cross-sectional associations of sleep parameters with brain atrophy and more PVS suggest adverse relationships between usual sleep habits and brain health in older people that should be evaluated longitudinally.

Non-pharmacological and pharmacological interventions relieve insomnia symptoms by modulating a shared network: A controlled longitudinal study

BACKGROUND

Primary insomnia (PI) is one of the most common complaints among the general population. Both non-pharmacological and pharmacological therapies have proven effective in treating primary insomnia. However, the underlying mechanism of treatment remains unclear, and no studies have compared the underlying mechanisms of different treatments.

METHODS

In this study, we investigated gray matter volume (GMV) and resting-state functional connectivity (rsFC) changes following both pharmacological and non-pharmacological treatments in patients with PI. A total of 67 PI patients were randomized into benzodiazepine treatment, cupping treatment, or a wait-list control group for 4 weeks. The Pittsburgh Sleep Quality Index (PSQI), gray matter volume (GMV), and resting-state functional connectivity (rsFC) of the hippocampus were measured at the beginning and end of the experiment.

RESULTS

We found 1) significantly decreased PSQI scores in the cupping and benzodiazepine treatment groups compared to the control group with no significant differences between the two treatment groups; 2) significant GMV increases in the cupping group compared to the control group at the right hippocampus after 4 weeks of treatment; 3) significantly increased rsFC between the right hippocampus and left rostral anterior cingulate cortex/medial prefrontal cortex (rACC/mPFC) in the two treatment groups, which was significantly associated with PSQI score decreases.

DISCUSSION

Our findings suggest that benzodiazepine and cupping may share a common mechanism to relieve the symptoms of patients with PI.

A lack of consistent brain alterations in insomnia disorder: An activation likelihood estimation meta-analysis

Insomnia disorder is a prevalent sleep disorder, which affects about 10% of general population. However, its neural mechanisms are poorly understood. Recently, several structural and functional neuroimaging studies have been conducted in patients with insomnia disorder, but these studies have yielded diverse findings. Here, we aimed to identify consistent patterns of abnormal brain alterations in insomnia disorder by performing a quantitative coordinate-based meta-analysis. Following the preferred reporting for systematic reviews and meta-analyses statement, we searched PubMed database and used reference tracking and finally retrieved 19 eligible studies (six task-based functional magnetic resonance imaging, eight resting-state functional magnetic resonance imaging, three voxel-based morphometry, and two positron emission tomography). We extracted peak coordinates from these studies and tested for convergence using the activation likelihood estimation method. Using this method, we found no significant convergent evidence for combination of structural atrophy and functional disturbances across previous studies (p = 0.914). Inconsistencies across these studies might be related to heterogonous clinical populations, the explorative nature of these studies in combination with small sample sizes, different experimental designs, and various preprocessing and statistical approaches. Future neuroimaging studies on insomnia disorder should include larger well-characterized samples, as well as standard imaging and analysis protocols.

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 ± 14.0, 17 males) and 65 good sleepers (mean age = 44.1 y ± 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.

Increased Posterior Insula-Sensorimotor Connectivity Is Associated with Cognitive Function in Healthy Participants with Sleep Complaints

Insomnia is characterized by sensory hypersensitivity and cognitive impairments. Recent work has identified the insula as a central brain region involved in both bottom-up gating of sensory information and top-down cognitive control. However, the specific relationships between insular subregion connectivity and emotional and cognitive functions remain unclear. In this study, resting-state functional magnetic resonance imaging data were obtained from 25 healthy participants with sleep complaints (HPS) and 25 age-, gender- and educational level-matched healthy participants without insomnia complaints (HP). We performed insular subregion (ventral anterior, dorsal anterior and posterior) functional connectivity (FC) analyses, and cognitive function was measured with several validated test procedures (e.g., the Wisconsin Card Sorting Test [WCST], Continuous Performance Test [CPT] and Trail making Test [TMT]). There were no significant differences between the two groups for WCST, CPT and TMT scores. The HPS group showed enhanced connectivity from the right posterior insula (R-PI) to the left postcentral gyrus (L-postCG) compared to HP group. WCST random errors (RE), sleep disturbance scores and HAMA scores correlated with this connectivity measurement in both HP and HPS groups. Our results provide direct evidence that the posterior insula (PI) synchronizes with sensorimotor areas to detect homeostatic changes and suggest that alteration of the latter is related to executive dysfunction in subjects with insomnia.

Disrupted brain network topology in chronic insomnia disorder: A resting-state fMRI study

This study investigated the topological characteristics of brain functional networks in chronic insomnia disorder (CID) patients. The resting-state functional magnetic resonance imaging and graph theory analysis method were applied to investigate the brain functional connectome patterns among 45 CID patients and 32 healthy controls. The brain functional connectome was constructed by thresholding partial correlation matrices of 90 brain regions from an automated anatomical labeling atlas. The topologic properties of brain functional connectomes at both global and nodal levels were tested. The CID patients had decreased number of module (p = .014) and hierarchy (p = .038), and increased assortativity (p = .035). Furthermore, some brain regions located in the default mode network, dorsal attention network, and sensory-motor network in these patients showed altered nodal centralities. Within these areas, the node betweenness of right central paracentral lobule had positive correlation with the Pittsburgh Sleep Quality Index score (R = 0.319, p = .039). The results imply that functional disruptions of CID patients may be related to disruptions in global and regional topological organization of the brain functional connectome, and provide new and important insights to understand the pathophysiological mechanisms of CID.

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Chronic insomnia disorder (CID) patients had disrupted global topological properties.

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Many brain regions of CID patients showed altered nodal centralities involving three different resting networks.

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Functional disruption of right central paracentral lobule may be a target for therapeutic intervention in pediatric CID.

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The disruption of topological organization might be explain the mechanism/reason of functional disruptions of CID.

Increased Salience Network Activity in Patients With Insomnia Complaints in Major Depressive Disorder

BACKGROUND

Insomnia is one of the main symptom correlates of major depressive disorder (MDD), but the neural mechanisms underlying the multifaceted interplay between insomnia and depression are not fully understood.

MATERIALS AND METHODS

Patients with MDD and high insomnia (MDD-HI, n = 24), patients with MDD and low insomnia (MDD-LI, n = 37), and healthy controls (HCs, n = 51) were recruited to participate in the present study. The amplitude of low-frequency fluctuations (ALFF) during the resting state were compared among the three groups.

RESULTS

We observed ALFF differences between the three groups in the right inferior frontal gyrus/anterior insula (IFG/AI), right middle temporal gyrus, left calcarine, and bilateral dorsolateral prefrontal cortex (dlPFC). Further region of interest (ROI) comparisons showed that the increases in the right IFG/AI reflected an abnormality specific to insomnia in MDD, while increases in the bilateral dlPFC reflected an abnormality specific to MDD generally. Increased ALFF in the right IFG/AI was also found to be correlated with sleep disturbance scores when regressing out the influence of the severity of anxiety and depression.

CONCLUSION

Our findings suggest that increased resting state ALLF in IFG/AI may be specifically related to hyperarousal state of insomnia in patients with MDD, independently of the effects of anxiety and depression.

Diffusion Tensor Imaging Tractography Reveals Disrupted White Matter Structural Connectivity Network in Healthy Adults with Insomnia Symptoms

Neuroimaging studies have revealed that insomnia is characterized by aberrant neuronal connectivity in specific brain regions, but the topological disruptions in the white matter (WM) structural connectivity networks remain largely unknown in insomnia. The current study uses diffusion tensor imaging (DTI) tractography to construct the WM structural networks and graph theory analysis to detect alterations of the brain structural networks. The study participants comprised 30 healthy subjects with insomnia symptoms (IS) and 62 healthy subjects without IS. Both the two groups showed small-world properties regarding their WM structural connectivity networks. By contrast, increased local efficiency and decreased global efficiency were identified in the IS group, indicating an insomnia-related shift in topology away from regular networks. In addition, the IS group exhibited disrupted nodal topological characteristics in regions involving the fronto-limbic and the default-mode systems. To our knowledge, this is the first study to explore the topological organization of WM structural network connectivity in insomnia. More importantly, the dysfunctions of large-scale brain systems including the fronto-limbic pathways, salience network and default-mode network in insomnia were identified, which provides new insights into the insomnia connectome. Topology-based brain network analysis thus could be a potential biomarker for IS.

Depressive symptoms account for differences between self-reported versus polysomnographic assessment of sleep quality in women with myofascial TMD

Patients with temporomandibular disorder (TMD) report poor sleep quality on the Pittsburgh Sleep Quality Index (PSQI). However, polysomnographic (PSG) studies show meagre evidence of sleep disturbance on standard physiological measures. The present aim was to analyse self-reported sleep quality in TMD as a function of myofascial pain, PSG parameters and depressive symptomatology. PSQI scores from 124 women with myofascial TMD and 46 matched controls were hierarchically regressed onto TMD presence, ratings of pain intensity and pain-related disability, in-laboratory PSG variables and depressive symptoms (Symptoms Checklist-90). Relative to controls, TMD cases had higher PSQI scores, representing poorer subjective sleep and more depressive symptoms (both P < 0·001). Higher PSQI scores were strongly predicted by more depressive symptoms (P < 0·001, R² = 26%). Of 19 PSG variables, two had modest contributions to higher PSQI scores: longer rapid eye movement latency in TMD cases (P = 0·01, R² = 3%) and more awakenings in all participants (P = 0·03, R² = 2%). After accounting for these factors, TMD presence and pain ratings were not significantly related to PSQI scores. These results show that reported poor sleep quality in TMD is better explained by depressive symptoms than by PSG-assessed sleep disturbances or myofascial pain. As TMD cases lacked typical PSG features of clinical depression, the results suggest a negative cognitive bias in TMD and caution against interpreting self-report sleep measures as accurate indicators of PSG sleep disturbance. Future investigations should take account of depressive symptomatology when interpreting reports of poor sleep.

Increased interhemispheric resting-state functional connectivity in healthy participants with insomnia symptoms: A randomized clinical consort study

BACKGROUND

Abnormalities within the insular cortex of the salience and thalamus of the hyperarousal network have been increasingly reported in healthy participants with insomnia symptoms by recent resting-state functional magnetic resonance imaging (rsfMRI) studies. However, little is known about the changes in functional interaction between the bilateral cerebral hemispheres in healthy participants with insomnia symptoms.

METHODS

In a randomized trial, 27 healthy participants with insomnia symptoms and 27 age-, gender-, and educational level-matched healthy participants without insomnia symptoms underwent rsfMRI. Voxel-mirrored homotopic connectivity (VMHC) was used to measure functional connectivity between any pair of symmetrical interhemispheric voxels (i.e., functional homotopy).

RESULTS

The healthy participants with insomnia symptoms displayed significantly increased VMHC compared to healthy participants without insomnia symptoms in the bilateral thalamus/posterior insula (including anterior insula), fusiform, middle cingulate gyrus, inferior parietal lobe, and postcentral gyrus. No regions of decreased VMHC were detected in healthy participants with insomnia symptoms. There were significantly positive correlations between the VMHC values in the anterior cingulate cortex (ACC) and sleep disturbance scores in all healthy participants.

CONCLUSIONS

Insomnia is associated with substantial impairment of interhemispheric coordination within the default mode (ACC), salience (insula), hyperarousal (thalamus/posterior insula), and visual (fusiform) networks.

Effects of digital Cognitive Behavioural Therapy for Insomnia on cognitive function: study protocol for a randomised controlled trial

BACKGROUND

The daytime effects of insomnia pose a significant burden to patients and drive treatment seeking. In addition to subjective deficits, meta-analytic data show that patients experience reliable objective impairments across several cognitive domains. While Cognitive Behavioural Therapy for Insomnia (CBT-I) is an effective and scalable treatment, we know little about its impact upon cognitive function. Trials of CBT-I have typically used proxy measures for cognitive functioning, such as fatigue or work performance scales, and no study has assessed self-reported impairment in cognitive function as a primary outcome. Moreover, only a small number of studies have assessed objective cognitive performance, pre-to-post CBT-I, with mixed results. This study specifically aims to (1) investigate the impact of CBT-I on cognitive functioning, assessed through both self-reported impairment and objective performance measures, and (2) examine whether change in sleep mediates this impact.

METHODS/DESIGN

We propose a randomised controlled trial of 404 community participants meeting criteria for Insomnia Disorder. In the DISCO trial (D efining the I mpact of improved S leep on CO gnitive function (DISCO)) participants will be randomised to digital automated CBT-I delivered by a web and/or mobile platform (in addition to treatment as usual (TAU)) or to a wait-list control (in addition to TAU). Online assessments will take place at 0 (baseline), 10 (post-treatment), and 24 (follow-up) weeks. At week 25, all participants allocated to the wait-list group will be offered digital CBT-I, at which point the controlled element of the trial will be complete. The primary outcome is self-reported cognitive impairment at post-treatment (10 weeks). Secondary outcomes include objective cognitive performance, insomnia severity, sleepiness, fatigue, and self-reported cognitive failures and emotional distress. All main analyses will be carried out on completion of follow-up assessments and will be based on the intention-to-treat principle. Further analyses will determine to what extent observed changes in self-reported cognitive impairment and objective cognitive performance are mediated by changes in sleep. The trial is supported by the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC) based at Oxford University Hospitals NHS Trust and University of Oxford, and by the NIHR Oxford Health BRC.

DISCUSSION

This study will be the first large-scale examination of the impact of digital CBT-I on self-reported cognitive impairment and objective cognitive performance.

TRIAL REGISTRATION

ISRCTN, ID: ISRCTN89237370 . Registered on 17 October 2016.