Abnormal Topology of the Structural Connectome in the Limbic Cortico-Basal-Ganglia Circuit and Default-Mode Network Among Primary Insomnia Patients

The abnormalities of brain function in females with primary insomnia: a resting-state functional magnetic resonance imaging study

Background

The neuropathologic mechanism of primary insomnia (PI) of females remains unclear. This study aims to investigate the features of amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo) in females with PI using functional magnetic resonance imaging (fMRI), and then explore the abnormalities of functional connectivity (FC).

Materials and methods

A total of 39 female PI patients and 31 female healthy controls (HC) were enrolled in the study. The sleep condition was assessed using the Pittsburgh Sleep Quality Index (PSQI), and Insomnia Severity Index (ISI), and their depressive symptom was evaluated using the Hamilton Depression Scale (HAMD-24). The rs-fMRI was once conducted for every subject. ReHo, ALFF, and ROI-based FC were used to analyze the changes of brain function.

Results

ALFF values were increased in the Cerebelum_4_5_L, as well as decreased ALFF in the bilateral Frontal_Sup_Medial (SFGmed), Angular_L (ANG.L), Parietal_Inf_R (IPL.R), SupraMarginal_R (SMG.R), and Postcentral_R (PoCG.R). ReHo values were increased in the Temporal_Pole_Mid_R (TPOsup.R), as well as decreased ReHo in the Insula_R (INS.R), Frontal_Inf_Oper_R (ORBinf.R), Putamen_R (PUT.R), Rolandic_Oper_R (ROL.R), bilateral Cingulum_Post (PCG), bilateral Frontal_Sup_Medial (SFGmed), bilateral anterior cingulate and paracingulate gyri (ACG), and the bilateral precuneus (PCUN). Across the entire brain, there was a decline in the FC between Angular_R and Frontal_Sup_Medial_L.

Conclusion

Alterations in brain regions of female patients with PI involved multiple functional networks, including the default mode network, the salience network, the central executive network, and the limbic network. Reduced coordination between functional networks may be an important mechanism for insomnia and may lead to reduced cognitive function and decision-making ability.

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.

Lateralized brunt of sleep deprivation on white matter injury in a rat model of Alzheimer's disease

Sleep disturbance is a recognized risk factor for Alzheimer's disease (AD), but the underlying micro-pathological evidence remains limited. To bridge this gap, we established an amyloid-β oligomers (AβO)-induced rat model of AD and subjected it to intermittent sleep deprivation (SD). Diffusion tensor imaging (DTI) and transmission electron microscopy were employed to assess white matter (WM) integrity and ultrastructural changes in myelin sheaths. Our findings demonstrated that SD exacerbated AβO-induced cognitive decline. Furthermore, we found SD aggravated AβO-induced asymmetrical impairments in WM, presenting with reductions in tract integrity observed in commissural fibers and association fasciculi, particularly the right anterior commissure, right corpus callosum, and left cingulum. Ultrastructural changes in myelin sheaths within the hippocampus and corpus callosum further confirmed a lateralized effect. Moreover, SD worsened AβO-induced lateralized disruption of the brain structural network, with impairments in critical nodes of the left hemisphere strongly correlated with cognitive dysfunction. This work represents the first identification of a lateralized impact of SD on the mesoscopic network and cognitive deficits in an AD rat model. These findings could deepen our understanding of the complex interplay between sleep disturbance and AD pathology, providing valuable insights into the early progression of the disease, as well as the development of neuroimaging biomarkers for screening early AD patients with self-reported sleep disturbances. Enhanced understanding of these mechanisms may pave the way for targeted interventions to alleviate cognitive decline and improve the quality of life for individuals at risk of or affected by AD.

Study of structural network connectivity using DTI tractography in insomnia disorder

Most of tractography studies on insomnia disorder (ID) have reported decreased structural connectivity between cortical and subcortical structures. Tractography based on standard diffusion tensor imaging (DTI) can generate high number of false-positive streamlines connections between gray matter regions. In the present study, we employed the convex optimization modeling for microstructure informed tractography-2 (COMMIT2) to improve the accuracy of the reconstructed whole-brain connectome and filter implausible brain connections in 28 patients with ID and compared with 27 healthy controls. Then, we used NBS-predict (a prediction-based extension to the network-based statistic method) in the COMMIT2-weighted connectome. Our results revealed decreased structural connectivity between subregions of the left somatomotor, ventral attention, frontoparietal, dorsal attention and default mode networks in the insomnia group. Moreover, there is a negative correlation between sleep efficiency and structural connectivity within the left frontoparietal, visual, default mode network, limbic, dorsal attention, right dorsal attention as well as right default mode networks. By comparing with standard connectivity analysis, we showed that by removing of false-positive streamlines connections after COMMIT2 filtering, abnormal structural connectivity was reduced in patients with ID compared to controls. Our results demonstrate the importance of improving the accuracy of tractography for understanding structural connectivity networks in ID.

Abnormal Topological Organization of White Matter Structural Networks in Normal Tension Glaucoma Revealed via Diffusion Tensor Tractography

BACKGROUND

Normal tension glaucoma (NTG) is considered a neurodegenerative disease with glaucomatous damage extending to diffuse brain areas. Therefore, this study aims to explore the abnormalities in the NTG structural network to help in the early diagnosis and course evaluation of NTG.

METHODS

The structural networks of 46 NTG patients and 19 age- and sex-matched healthy controls were constructed using diffusion tensor imaging, followed by graph theory analysis and correlation analysis of small-world properties with glaucoma clinical indicators. In addition, the network-based statistical analysis (NBS) method was used to compare structural network connectivity differences between NTG patients and healthy controls.

RESULTS

Structural brain networks in both NTG and NC groups exhibited small-world properties. However, the small-world index in the severe NTG group was reduced and correlated with a mean deviation of the visual field (MDVF) and retinal nerve fiber layer (RNFL) thickness. When compared to healthy controls, degree centrality and nodal efficiency in visual brain areas were significantly decreased, and betweenness centrality and nodal local efficiency in both visual and nonvisual brain areas were also significantly altered in NTG patients (all p < 0.05, FDR corrected). Furthermore, NTG patients exhibited increased structural connectivity in the occipitotemporal area, with the left fusiform gyrus (FFG.L) as the hub (p < 0.05).

CONCLUSIONS

NTG exhibited altered global properties and local properties of visual and cognitive-emotional brain areas, with enhanced structural connections within the occipitotemporal area. Moreover, the disrupted small-world properties of white matter might be imaging biomarkers for assessing NTG progression.

Sleep disorders and white matter integrity in patients with sporadic amyotrophic lateral sclerosis

This study aimed to explore the characteristics of sleep disorders and their relationship with abnormal white-matter integrity in patients with sporadic amyotrophic lateral sclerosis. One hundred and thirty-six patients and 80 healthy controls were screened consecutively, and 56 patients and 43 healthy controls were ultimately analyzed. Sleep disorders were confirmed using the Pittsburgh sleep quality index, the Epworth sleepiness scale, and polysomnography; patients were classified into those with poor and good sleep quality. White-matter integrity was assessed using diffusion tensor imaging and compared between groups to identify the white-matter tracts associated with sleep disorders. The relationship between scores on the Pittsburgh sleep quality index and impaired white-matter tracts was analyzed using multiple regression. Poor sleep quality was more common in patients (adjusted odds ratio, 4.26; p = 0.005). Compared to patients with good sleep quality (n = 30), patients with poor sleep quality (n = 26; 46.4%) showed decreased fractional anisotropy, increased mean diffusivity, and increased radial diffusivity of projection and commissural fibers, and increased radial diffusivity of the right thalamus. The Pittsburgh score showed the best fit with the mean fractional anisotropy of the right anterior limb of the internal capsule (r = - 0.355, p = 0.011) and the mean radial diffusivity of the right thalamus (r = 0.309, p = 0.028). We conclude that sleep disorders are common in patients with sporadic amyotrophic lateral sclerosis and are associated with reduced white-matter integrity. The pathophysiology of amyotrophic lateral sclerosis may contribute directly to sleep disorders.

Differences in Gray Matter Volume in Cerebral Small Vessel Disease Patients with and without Sleep Disturbance

Recently, there has been increased interest in the relationship between cerebral small vessel disease (CSVD) and circadian rhythm disruption, particularly sleep disturbance. However, the neural mechanism of sleep disturbance in CSVD patients remains poorly understood. The purpose of this study is to explore the gray matter alterations in CSVD patients with and without sleep disturbance. 59 patients with CSVD and 40 healthy controls (HC) were recruited for the present study. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) questionnaire. CSVD patients were categorized into either the good sleepers group (CSVD-GS, n = 23) or the poor sleepers group (CSVD-PS, n = 36) based on PSQI score. Voxel-based morphometry (VBM) analysis was used to assess differences in gray matter volume (GMV) between groups. Multivariate regression analyses were performed to investigate the relationships between sleep quality, GMV, and white matter hyperintensities (WMH). We observed GMV differences between the three groups in the bilateral caudate, right thalamus, bilateral calcarine cortex, left precentral gyrus, right orbitofrontal cortex, left cingulate gyrus, and right sub-gyral temporal lobe. Additionally, the CSVD-PS group exhibited decreased GMV in the bilateral calcarine cortex yet increased GMV in the right caudate compared to the CSVD-GS group. In fully adjusted models, GMV of the right caudate and bilateral calcarine cortex was associated with sleep quality in CSVD patients. The present study revealed structural brain alterations in CSVD patients with sleep disturbance. These findings may provide novel insights into the neural mechanisms of sleep disturbance in CSVD.

Preliminary Evidence for the Sequentially Mediated Effect of Racism-Related Stress on Pain Sensitivity Through Sleep Disturbance and Corticolimbic Opioid Receptor Function

Sleep disturbance predicts worse pain outcomes. Because sleep disturbance inequitably impacts Black adults - with racism as the upstream cause - understanding how racism-related stress impacts pain through sleep might help minimize racialized pain inequities. This preliminary study examined sequential mediation of the effect of racism-related stress on experimental pain through sleep disturbance and corticolimbic μOR function in pain-free non-Hispanic Black (NHB) and White (NHW) adults. Participants completed questionnaires, actigraphy, positron emission tomography, and sensory testing. We reproduced findings showing greater sleep disturbance and pain sensitivity among NHB participants; greater sleep disturbance (r = .35) and lower pain tolerance (r=-.37) were significantly associated with greater racism-related stress. In a sequential mediation model, the total effect of racism-related stress on pain tolerance (β=-.38, P = .005) weakened after adding sleep disturbance and ventromedial prefrontal cortex (vmPFC) μOR binding potential (BPND) as mediators (β = -.18, P = .16). The indirect effect was statistically significant [point estimate = -.003, (-.007, -.0003). Findings showed a potential sequentially mediated effect of racism-related stress on pain sensitivity through sleep disturbance and vmPFC μOR BPND. As policy efforts are enacted to eliminate the upstream cause of systemic racism, these results cautiously suggest that sleep interventions within racism-based trauma informed therapy might help prevent downstream effects on pain. PERSPECTIVE: This preliminary study identified the effect of racism-related stress on pain through sleep disturbance and mu-opioid receptor binding potential in the ventromedial prefrontal cortex. Findings cautiously support the application of sleep interventions within racism-based trauma-informed therapy to prevent pain inequities as policy changes function to eliminate all levels of racism.

Sleep disturbance-related neuroimaging features as potential biomarkers for the diagnosis of major depressive disorder: A multicenter study based on machine learning

BACKGROUND

Objective biomarkers are crucial for overcoming the clinical dilemma in major depressive disorder (MDD), and the individualized diagnosis is essential to facilitate the precise medicine for MDD.

METHODS

Sleep disturbance-related magnetic resonance imaging (MRI) features was identified in the internal dataset (92 MDD patients) using the relevance vector regression algorithm, which was further verified in 460 MDD patients of an independent, multicenter dataset. Subsequently, using these MRI features, the eXtreme Gradient Boosting classification model was constructed in the current multicenter dataset (460 MDD patients and 470 normal controls). Meanwhile, the association between classification outputs and the severity of depressive symptoms was also investigated.

RESULTS

In MDD patients, the combination of gray matter density and fractional amplitude of low-frequency fluctuation can accurately predict individual sleep disturbance score that was calculated by the sum of item 4 score, item 5 score, and item 6 score of the 17-Item Hamilton Rating Scale for Depression (HAMD-17) (R² = 0.158 in the internal dataset; R² = 0.110 in multicenter dataset). Furthermore, the classification model based on these MRI features distinguished MDD patients from normal controls with 86.3% accuracy (area under the curve = 0.937). Importantly, the classification outputs significantly correlated with HAMD-17 scores in MDD patients.

LIMITATION

Lacking some specialized tools to assess the personal sleep quality, e.g. Pittsburgh Sleep Quality Index.

CONCLUSION

Neuroimaging features can reflect accurately individual sleep disturbance manifestation and serve as potential diagnostic biomarkers of MDD.

Asymmetric alterations of white matter integrity in patients with insomnia disorder

Despite the adverse consequences of insomnia disorder for both individuals and society, the underlying neurobiological processes are poorly understood. The purpose was to further understand the alterations of white matter tracts in patients with insomnia and their association with sleep variables and also to determine if diffusion tensor imaging measures would be a useful disease marker. Twenty-six patients with insomnia and 26 age-matched healthy volunteers underwent diffusion tensor imaging. We employed an automated probabilistic tractography analysis approach using TRActs Constrained by UnderLying Anatomy (TRACULA) to quantify diffusion measures in major white matter tracts. We found significantly increased fractional anisotropy in the right cingulum-angular bundle and uncinate fasciculus in patients group compared to controls. Moreover, the mean diffusivity and radial diffusivity were reduced in the right cingulum-angular bundle in patients group in comparison with controls. We also found significantly increased fractional anisotropy along the bilateral cingulum-angular bundle and right uncinate fasciculus in patients. Also, mean and radial diffusivity were reduced along the right cingulum-angular bundle in patients group compared to controls. There is a significant positive correlation between fractional anisotropy and Epworth Sleepiness Scale scores. Moreover, there are negative correlations between mean, radial and axial diffusivity and total sleep time and sleep efficiency and also positive correlations between mean, radial and axial diffusivity and duration of disease and Pittsburgh Sleep Quality Index scores. This study showed the importance of examining whole-tract and waypoint white matter integrity in insomnia disorder. We found asymmetric widespread white matter integrity changes in patients with insomnia.

Abnormal white matter within brain structural networks is associated with high-impulse behaviour in codeine-containing cough syrup dependent users

Codeine-containing cough syrup (CCS) is considered as one of the most popular drug of dependence among adolescents because of its inexpensiveness and easy availability. However, its relationship with neurobiological effects remains sparsely explored. Herein, we examined how high-impulse behaviours relate to changes in the brain structural networks. Forty codeine-containing cough syrup dependent (CCSD) users and age-, gender-, and number of cigarettes smoked per day -matched forty healthy control (HC) subjects underwent structural brain imaging via MRI. High-impulse behaviour was assessed using the 30-item self-rated Barratt Impulsiveness Scale (BIS-11), and structural networks were constructed using diffusion tensor imaging and AAL-90 template. Between-group topological metrics were compared using nonparametric permutations. Benjamin-Hochberg false discovery rate correction was used to correct for multiple comparisons (P < 0.05). The relationships between abnormal network metrics and clinical characteristics of CCS dependent (BIS-11 total score, CCS- dependent duration and mean dose) were examined by Spearman's correlation. Structural networks of the CCSD group demonstrated lower small-world properties than those of the HC group. Abnormal changes in nodal properties among CCSD users were located mainly in the frontal gyrus, inferior parietal lobe and olfactory cortex. NBS analysis further indicated disrupted structural connections between the frontal gyrus and multiple brain regions. There were significant correlations between abnormal nodal properties of the frontal gyrus and clinical characteristics (BIS-11 total score, CCS dependent duration and mean dose) in the CCSD group. These findings suggest that the high-impulse behavioural expression in CCS addiction is associated with widespread brain regions, particularly within those in the frontal cortex. Aberrant brain regions and disrupted connectivity of structural network may be the bases of neuropathology for underlying symptoms of high-impulse behaviours in CCSD users, which may provide a novel sight to better treat and prevent codeine dependency in adolescents.

Alterations of core structural network connectome associated with suicidal ideation in major depressive disorder patients

Suicide ideation (SI) is a most high-risk clinical sign for major depressive disorder (MDD). However, whether the rich-club network organization as a core structural network is associated with SI and how the related neural circuits are distributed in MDD patients remain unknown. Total 177 participants including 69 MDD patients with SI (MDDSI), 58 MDD without SI (MDDNSI) and 50 cognitively normal (CN) subjects were recruited and completed neuropsychological tests and diffusion-tensor imaging scan. The rich-club organization was identified and the global and regional topological properties of structural networks, together with the brain connectivity of specific neural circuit architectures, were analyzed. Further, the support vector machine (SVM) learning was applied in classifying MDDSI or MDDNSI from CN subjects. MDDSI and MDDNSI patients both exhibited disrupted rich-club organizations. However, MDDSI patients showed that the differential network was concentrated on the non-core low-level network and significantly destroyed betweeness centrality was primarily located in the regional non-hub regions relative to MDDNSI patients. The differential structural network connections involved the superior longitudinal fasciculus and the corpus callosum were incorporated in the cognitive control circuit and default mode network. Finally, the feeder serves as a potentially powerful indicator for distinguishing MDDSI patients from MDDNSI or CN subjects. The altered rich-club organization provides new clues to understand the underlying pathogenesis of MDD patients, and the feeder was useful as a diagnostic neuroimaging biomarker for differentiating MDD patients with or without SI.

White matter microstructural abnormalities in primary insomnia: A systematic review of diffusion tensor imaging studies

Primary insomnia (PI), the most common sleep disorder, is primarily characterized by difficulties in initiating and maintaining sleep and deficits in daytime functioning. Study of white matter (WM) connections of the brain might provide valuable information regarding the underlying neural mechanism of PI. Diffusion tensor imaging (DTI) provides non-invasive access to the microstructural and network properties of brain WM, and thus, a great opportunity to quantitatively and sensitively study the human brain. The current literature of PI does not provide a consistent explanation of the etiology and pathology of the disorder; thus, we searched PubMed, EMBASE, and SCOPUS for DTI studies that compared WM integrity or network organization between PI patients and healthy controls to integrate all existing literature as an insight for further studies, and, hopefully, effective prevention and management of the disorder. English peer-reviewed full-text publications that investigated the diffusion indices of PI patients or those with insomnia symptoms compared with a group of healthy controls were included. We included 11 studies and extracted the data for qualitative synthesis. Except for one study, all studies were rated as high-quality, based on quality assessment. In aggregation, a total of 541 patients with PI and 679 healthy controls were included in this study. Our review of DTI studies suggests that WM disruptions in PI are better characterized in the context of neural networks. Frontostriatal, frontothalamic, and corticocortiscal networks, as well as the limbic system, seem to be the main neural networks with microstructural and network alterations in patients with PI. To illustrate, different parts of corona radiate and internal capsule within the corticosubcortical networks and superior longitudinal fasciculus within the corticocortical networks showed altered microstructural properties in PI patients. In view of the fact that the findings from individual studies are heterogeneous, it is difficult to derive consistent findings from the results, and the divergence of the findings must not be disregarded. Thus, this study is a starting point for future studies, and its implications for etiology and pathogenesis of insomnia should be regarded cautiously.

Disrupted frontostriatal connectivity in primary insomnia: a DTI study

Dysfunction of the sleep-wake transition is considered to be associated with the pathology of patients with primary insomnia (PI). Previous animal study had reported that brain circuits between the striatum and cortex can regulate sleep-wake transitions. So far, few studies have systematically explored the structural connectivity of the striatum-centered circuits and their potential roles in patients with PI. In this study, we chosen the striatum as the seed and 10 priori target regions as masks to assess the structural connectivity by using seed-based classification with a diffusion tensor imaging (DTI) probabilistic tractography method. Track strengths of the striatum-centered circuits were compared between 22 patients with PI (41.27 ± 9.21 years) and 30 healthy controls (HC) (35.2 ± 8.14 years). Pittsburgh Sleep Quality Index (PSQI) was used to measure the sleep quality in all participants. Lower track strengths (left striatum- anterior cingulate cortex (ACC), left striatum- dorsal anterior cingulate cortex (dACC), left striatum-Hippocampus, and right striatum-Hippocampus) were observed in patients with PI compared to HC. Additionally, the lower track strengths of brain circuits mentioned above were negatively correlated with PSQI. Taken together, our findings revealed the lower tract strength of frontostriatal circuits in patients with PI and HC, which provided the implications of the system-level structural connections of frontostriatal circuits in the pathology of PI. We suggested that the track strengths of the frontostriatal circuits calculated from DTI can be the potential neuroimaging biomarkers of the sleep quality in patients with PI.

Presence of Allergies and Their Impact on Sleep in Children Who Stutter

Purpose

Population-based research has identified insomnia or trouble sleeping, sleepiness during the day, and fatigue during the day as frequent coexisting conditions in children who stutter (CWS). Considering that allergies are well known to disturb sleep, the purpose of this study was to explore if there is an association between the presence of allergies and sleep issues among CWS, as well as if allergies are frequent in CWS.

Method

Data from the 2012 National Health Interview Survey were used. Children used in this sample were those whose caregivers answered definitively whether or not the child stuttered within the past 12 months. Additionally, caregivers identified the presence of allergies and/or asthma and the presence of insomnia or trouble sleeping in the sample child.

Results

The sample included 200 CWS and 9,951 children who do not stutter (CWNS). The odds of insomnia/trouble sleeping were greater in CWS who present with allergies and/or asthma, with the exception of food allergy, compared to CWS who do not present with with allergies and/or asthma. Additionally, the odds of insomnia/trouble sleeping were greater in CWS without any allergy, asthma, and coexisting disability ( OR = 7.48, p < .001) as compared to CWNS without any allergy, asthma, and coexisting disability. The presence of either any allergy or an asthma attack was higher among CWS (46.4%) compared to CWNS (29.5%), p < .001. Specifically, CWS were found to be at greater odds of presenting with any kind of respiratory allergy ( OR = 1.72, p = .034), food allergy ( OR = 2.32, p = .002), and skin allergy ( OR = 1.84, p = .009) than CWNS.

Conclusions

CWS were found to be at greater odds of allergies and asthma, conditions that also impair sleep. Interestingly, insomnia/trouble sleeping was prevalent among CWS, even when allergies, asthma, and coexisting disabilities were not present. The possible implications of these findings are discussed.

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.

Right arcuate fasciculus and superior longitudinal fasciculus abnormalities in primary insomnia

Primary insomnia (PI) is a very common phenomenon and associated with functional impairments of attention, memory and mood regulation. However, its neurobiology is poorly understood. To date, the studies about integrity of white matter (WM) tracts in PI patients have been still rare. In the present study, we used Automated Fiber Quantification (AFQ), which reliably and efficiently quantified diffusion measurements at multiple locations along the WM trajectory based on diffusion tensor imaging (DTI), to assess WM diffusion properties differences between 23 PI patients and 32 matched healthy controls in 18 tracts. The relationships between neuroimaging differences and sleep behaviors were explored, including Pittsburgh Sleep Quality Index (PSQI) and Insomnia Severity Index Scale (ISI). Compared with healthy control group, right arcuate fasciculus (Arc) and superior longitudinal fasciculus (SLF) showed significant higher fractional anisotropy (FA), mean diffusivity (MD) and radial diffusivity (RD) along tract length in PI patients (FWE corrected, p < 0.01). Axial diffusivity (AD) for PI patients was higher in right Arc and lower in right SLF. Correlation analyses revealed that FA of right Arc and MD of right SLF were negatively correlated with PSQI score in PI patients, and AD of right Arc and FA of right SLF were positively correlated with PSQI score. Negative correlation was observed between FA of right Arc and AD of right SLF and ISI score in PI patients. Our findings can help us to improve the understanding of the neural mechanisms of primary insomnia at abnormalities in WM microstructure.

Abnormal Rich Club Organization of Structural Network as a Neuroimaging Feature in Relation With the Severity of Primary Insomnia

PURPOSE

Insomnia is the most prevalent sleep complaint in the general population but is often intractable due to uncertainty regarding the underlying pathomechanisms. Sleep is regulated by a network of neural structures interconnected with the core nodes of the brain connectome referred to as the "rich club". We examined alterations in brain rich-club organization as revealed by diffusion tensor imaging (DTI) and the statistical relationships between abnormalities in rich-club metrics and the clinical features of primary insomnia (PI).

METHODS

This study recruited 43 primary insomnia (PI) patients and 42 age-, sex-, and education level-matched healthy controls (HCs). Differences in global and regional network parameters between PI and healthy control groups were compared by nonparametric tests, and Spearman's correlations were calculated to assess associations of these network metrics with PI-related clinical features, including disease duration and scores on the Pittsburgh Sleep Quality Index, Insomnia Severity Index, Self-Rating Anxiety Scale, and Self-Rating Depression Scale.

RESULTS

Weighted white matter networks exhibited weaker rich-club organization in PI patients than HCs across different thresholds (50%, 75%, and 90%) and parcellation schemes [automated anatomical labeling (AAL)-90 and AAL-1024]. Aberrant rich-club organization was found mainly in limbic-cortical-basal ganglia circuits and the default-mode network.

CONCLUSIONS

Abnormal rich-club metrics are a characteristic feature of PI-related to disease severity. These metrics provide potential clues to PI pathogenesis and may be useful as diagnostic markers and for assessment of treatment response.

Integrating sleep, neuroimaging, and computational approaches for precision psychiatry

In advancing precision psychiatry, we focus on what imaging technology and computational approaches offer for the future of diagnostic subtyping and personalized tailoring of interventions for sleep impairment in mood and anxiety disorders. Current diagnostic criteria for mood and anxiety tend to lump different forms of sleep disturbance together. Parsing the biological features of sleep impairment and brain circuit dysfunction is one approach to identifying subtypes within these disorders that are mechanistically coherent and offer targets for intervention. We focus on two large-scale neural circuits implicated in sleep impairment and in mood and anxiety disorders: the default mode network and negative affective network. Through a synthesis of existing knowledge about these networks, we pose a testable framework for understanding how hyper- versus hypo-engagement of these networks may underlie distinct features of mood and sleep impairment. Within this framework we consider whether poor sleep quality may have an explanatory role in previously observed associations between network dysfunction and mood symptoms. We expand this framework to future directions including the potential for connecting circuit-defined subtypes to more distal features derived from digital phenotyping and wearable technologies, and how new discovery may be advanced through machine learning approaches.

Brain structural connectivity network alterations in insomnia disorder reveal a central role of the right angular gyrus

•

People with insomnia show widespread brain structural hyperconnectivity.

•

The right angular gyrus is central to the structural connectivity alterations.

•

Connectivity of this angular gyrus subnetwork correlates with reactive hyperarousal.

•

Brain structural hyperconnectivity may mark vulnerability to insomnia.

Insomnia Disorder (ID) is a prevalent and persistent condition, yet its neural substrate is not well understood. The cognitive, emotional, and behavioral characteristics of ID suggest that vulnerability involves distributed brain networks rather than a single brain area or connection. The present study utilized probabilistic diffusion tractography to compare the whole-brain structural connectivity networks of people with ID and those of matched controls without sleep complaints.

Diffusion-weighted images and T1-weighed images were acquired in 51 people diagnosed with ID (21–69 years of age, 37 female) and 48 matched controls without sleep complaints (22–70 years of age, 31 female). Probabilistic tractography was performed to construct the whole-brain structural connectivity network of each participant. Case–control differences in connectivity strength and network efficiency were evaluated with permutation tests.

People with ID showed structural hyperconnectivity within a subnetwork that spread over frontal, parietal, temporal, and subcortical regions and was anchored at the right angular gyrus. The result was robust across different edge-weighting strategies. Moreover, converging support was given by the finding of heightened right angular gyrus nodal efficiency (harmonic centrality) across varying graph density in people with ID. Follow-up correlation analyses revealed that subnetwork connectivity was associated with self-reported reactive hyperarousal.

The findings demonstrate that the right angular gyrus is a hub of enhanced structural connectivity in ID. Hyperconnectivity within the identified subnetwork may contribute to increased reactivity to stimuli and may signify vulnerability to ID.

Auriculotherapy for sleep quality in people with primary insomnia: A protocol for a systematic review and meta-analysis

BACKGROUND

Primary insomnia is one of the common sleep disorders. Auriculotherapy originated from traditional Chinese medicine, has been thought as a promising treatment for primary insomnia. We aim to evaluate the efficacy and safety of auriculotherapy for patients with primary insomnia through this systematic review.

METHODS

Five English databases (Cochrane Central Register of Controlled Trials, MEDLINE, EMBASE, AMED, and CINAHL), 4 Chinese databases (CBM, CNKI, CQVIP, and Wanfang), and 5 clinical trial registration databases (ClinicalTrials.gov, ANZCTR, EU-CTR, ChiCTR, and ICTRP) will be searched from establishment of the database until November 2018. Articles written in English or Chinese languages will be included. The randomized controlled trials of auriculotherapy (auricular acupuncture and auricular acupressure) for patients with primary insomnia will be included. The primary outcome will be assessed according to the Pittsburgh sleep quality index. Meta-analysis will be conducted with the use of RevMan 5.3. The specific process will refer to the Cochrane Handbook 5.1 for Systematic Review.

RESULTS

High-quality synthesis of current evidence on the efficacy and safety of auriculotherapy for primary insomnia will be provided in this study.

CONCLUSION

This systematic review aims to present evidence for whether auriculotherapy is an effective intervention which can improve sleep quality in patients suffering primary insomnia.

PROSPERO REGISTRATION NUMBER

CRD42019106422.

SleepOMICS: How Big Data Can Revolutionize Sleep Science

Sleep disorders have reached epidemic proportions worldwide, affecting the youth as well as the elderly, crossing the entire lifespan in both developed and developing countries. "Real-life" behavioral (sensor-based), molecular, digital, and epidemiological big data represent a source of an impressive wealth of information that can be exploited in order to advance the field of sleep research. It can be anticipated that big data will have a profound impact, potentially enabling the dissection of differences and oscillations in sleep dynamics and architecture at the individual level ("sleepOMICS"), thus paving the way for a targeted, "one-size-does-not-fit-all" management of sleep disorders ("precision sleep medicine").