Altered connection properties of important network hubs may be neural risk factors for individuals with primary insomnia

Multimodal transformer graph convolution attention isomorphism network (MTCGAIN): a novel deep network for detection of insomnia disorder

Background

In clinic, the subjectivity of diagnosing insomnia disorder (ID) often leads to misdiagnosis or missed diagnosis, as ID may have the same symptoms as those of other health problems.

Methods

A novel deep network, the multimodal transformer graph convolution attention isomorphism network (MTGCAIN) is proposed in this study. In this network, graph convolution attention (GCA) is first employed to extract the graph features of brain connectivity and achieve good spatial interpretability. Second, the MTGCAIN comprehensively utilizes multiple brain network atlases and a multimodal transformer (MT) to facilitate coded information exchange between the atlases. In this way, MTGCAIN can be used to more effectively identify biomarkers and arrive at accurate diagnoses.

Results

The experimental results demonstrated that more accurate and objective diagnosis of ID can be achieved using the MTGCAIN. According to fivefold cross-validation, the accuracy reached 81.29% and the area under the receiver operating characteristic curve (AUC) reached 0.8760. A total of nine brain regions were detected as abnormal, namely right supplementary motor area (SMA.R), right temporal pole: superior temporal gyrus (TPOsup.R), left temporal pole: superior temporal gyrus (TPOsup.L), right superior frontal gyrus, dorsolateral (SFGdor.R), right middle temporal gyrus (MTG.R), left middle temporal gyrus (MTG.L), right inferior temporal gyrus (ITG.R), right median cingulate and paracingulate gyri (DCG.R), left median cingulate and paracingulate gyri (DCG.L).

Conclusions

The brain regions in the default mode network (DMN) of patients with ID show significant impairment (occupies four-ninths). In addition, the functional connectivity (FC) between the right middle occipital gyrus and inferior temporal gyrus (ITG) has an obvious correlation with comorbid anxiety (P=0.008) and depression (P=0.005) among patients with ID.

Towards the neurobiology of insomnia: A systematic review of neuroimaging studies

Insomnia disorder signifies a major public health concern. The development of neuroimaging techniques has permitted to investigate brain mechanisms at a structural and functional level. The present systematic review aims at shedding light on functional, structural, and metabolic substrates of insomnia disorder by integrating the available published neuroimaging data. The databases PubMed, PsycARTICLES, PsycINFO, CINAHL and Web of Science were searched for case-control studies comparing neuroimaging data from insomnia patients and healthy controls. 85 articles were judged as eligible. For every observed finding of each study, the effect size was calculated from standardised mean differences, statistic parameters and figures, showing a marked heterogeneity that precluded a comprehensive quantitative analysis. From a qualitative point of view, considering the findings of significant group differences in the reported regions across the articles, this review highlights the major involvement of the anterior cingulate cortex, thalamus, insula, precuneus and middle frontal gyrus, thus supporting some central themes in the debate on the neurobiology of and offering interesting insights into the psychophysiology of sleep in this disorder.

Opposing brain signatures of sleep in task-based and resting-state conditions

Sleep and depression have a complex, bidirectional relationship, with sleep-associated alterations in brain dynamics and structure impacting a range of symptoms and cognitive abilities. Previous work describing these relationships has provided an incomplete picture by investigating only one or two types of sleep measures, depression, or neuroimaging modalities in parallel. We analyze the correlations between brainwide neural signatures of sleep, cognition, and depression in task and resting-state data from over 30,000 individuals from the UK Biobank and Human Connectome Project. Neural signatures of insomnia and depression are negatively correlated with those of sleep duration measured by accelerometer in the task condition but positively correlated in the resting-state condition. Our results show that resting-state neural signatures of insomnia and depression resemble that of rested wakefulness. This is further supported by our finding of hypoconnectivity in task but hyperconnectivity in resting-state data in association with insomnia and depression. These observations dispute conventional assumptions about the neurofunctional manifestations of hyper- and hypo-somnia, and may explain inconsistent findings in the literature.

Neuroimaging in insomnia: Review and reconsiderations

Over the last decades, neuroimaging has become a substantial component of insomnia research. While theoretical underpinnings of different studies vary just like methodological choices and the experimental design, it is suggested that major features of insomnia disorder rely on the impaired function, structure, metabolism and connectivity of brain areas involved in sleep generation, emotion regulation, self-processing/-awareness and attentional orientation. However, neuroimaging research on insomnia often suffers from small sample sizes, heterogeneous methodology and a lack of replicability. With respect to these issues, the field needs to address the questions: (1a) how sufficiently large sample sizes can be accumulated within a reasonable economic framework; (1b) how effect sizes in insomnia-related paradigms can be amplified; (2a) how a higher degree of standardisation and transparency in methodology can be provided; and (2b) how an adequate amount of flexibility/complexity in study design can be maintained. On condition that methodological consistency and a certain degree of adaptability are given, pooled data/large cohort analyses can be considered to be one way to answer these questions. Regarding experimental single-centre trials, it might be helpful to focus on insomnia-related transdiagnostic concepts. In doing so, expectable effect sizes (in between-subjects designs) can be increased by: (a) comparing groups that are truly distinct regarding the variables examined in a concept-specific paradigm; and (b) facilitated, intensified and precise elicitation of a target symptom.

Amygdala resting-state functional connectivity alterations in patients with chronic insomnia disorder: correlation with electroencephalography beta power during sleep

STUDY OBJECTIVES

This study investigated alterations in resting-state functional connectivity (RSFC) and hyperarousal biomarkers in patients with chronic insomnia disorder (CID), compared with good sleepers (GS). We also examined the relationships between altered RSFC and hyperarousal biomarkers.

METHODS

Fifty patients with CID and 52 GS completed self-reporting questionnaires, and then underwent polysomnography and resting-state functional magnetic resonance imaging. We analyzed RSFC in the amygdala (AMG) and anterior insula (aINS), which are core regions of the salience network that are likely to be involved in hyperarousal. We also analyzed electroencephalography (EEG) relative beta power and heart rate variability (HRV) parameters (e.g. low and high frequency) during sleep. We then tested between-group differences in the RSFC and hyperarousal biomarkers; we examined correlations of RSFC with EEG beta power and HRV.

RESULTS

Compared with GS, patients with CID showed more negative RSFC between the right amygdala (R.AMG) and left supramarginal gyrus (L.SMG), but less positive RSFC between the left aINS and bilateral lateral prefrontal cortex. The R.AMG-L.SMG RSFC was negatively correlated with EEG beta power in central regions (C3: r = -0.336, p = 0.012; C4: r = -0.314, p = 0.024).

CONCLUSIONS

Decreased RSFC between the R.AMG and L.SMG in patients with insomnia may reflect the difficulty in cortical top-down regulation of the AMG, indicating daytime hyperarousal. Individuals who experience hyperarousal during the daytime may also exhibit cortical hyperarousal during sleep, as indicated by increased EEG beta power.

Prefrontal Cortex Hemodynamics and Functional Connectivity Changes during Performance Working Memory Tasks in Older Adults with Sleep Disorders

Objective: Older adults with sleep disorders (SDs) show impaired working memory abilities, and working memory processes are closely related to the prefrontal cortex (PFC). However, the neural mechanism of working memory impairment in older adults with SD remains unclear. This study aimed to investigate changes in PFC function among older adults with SD when carrying out the N-back task by functional near-infrared spectroscopy (fNIRS). Method: A total of 37 older adults with SDs were enrolled in this study and matched with 37 healthy older adults by gender, age, and years of education. Changes in PFC function were observed by fNIRS when carrying out the N-back task. Results: The accuracy on the 0-back and 2-back tasks in the SD group was significantly lower than that in the healthy controls (HC) group. The oxygenated hemoglobin (oxy-Hb) concentration of channel 8 which located in the dorsolateral prefrontal cortex (DLPFC) was significantly reduced in the SD group during the 2-back task, and the channel-to-channel connectivity between the PFC subregions was significantly decreased. Conclusions: These results suggest that patients with sleep disorders have a weak performance of working memory; indeed, the activation and functional connectivity in the prefrontal subregions were reduced in this study. This may provide new evidence for working memory impairment and brain function changes in elderly SDs.

Aberrant brain functional hubs convergence in the acute severe traumatic brain injury patients with rapidly recovering

PURPOSE

We aimed to identify the aberrant functional hubs in patients with acute severe traumatic brain injury (sTBI) and investigate whether they could help inform prognosis.

METHODS

Twenty-eight sTBI patients and health controls underwent imaging scanning. The graph-theoretical measure of degree centrality (DC) was applied to identify the abnormal brain functional hubs and conjoined with regions of interest-based analysis to investigate their interaction and impact on whole-brain. We further split sTBI patients into two subgroups according to their recovery to explore whether the fractional amplitude of low-frequency fluctuation (fALFF) roles in functional connectivity (FC) differential areas to help inform the patients' long-term prognosis.

RESULTS

We identified the part of prefrontal cortex (PFC), precentral and postcentral gyrus (Pre-/Post-CG), cingulate gyrus (CgG), posterior medial cortex (PMC), and brainstem that could be core hubs whose DC was significantly increased in patients with acute sTBI. The interaction strength of the paired hubs could be enhanced (CG-PFC, CgG-PFC, CG-brainstem, CgG-brainstem, PMC-brainstem, and PFC-brainstem) and weakened (CG-CgG, CG-PMC, CgG-PMC, and PMC-PFC), compared with healthy controls. We also found abnormal FC in 5 hubs to whole-brain. The spontaneous brain activities in the FC differential regions [e.g., the fALFF and mean fALFF value] were valid to predict outcome at 6-month in patients with sTBI.

CONCLUSION

We demonstrated a compensatory mechanism that part of brain regions will converge into abnormal functional hubs in patients with acute sTBI, which provides a potential approach to objectively predicting patients' long-term outcome.

The increased functional connectivity between the locus coeruleus and supramarginal gyrus in insomnia disorder with acupuncture modulation

Background

Insomnia disorder (ID) seriously affects the quality of people's daily life, and acupuncture is an effective therapy for it. As an essential component of the upward activation system, the locus coeruleus (LC) plays a crucial role in sleep-wake regulation, its aberrant functional connectivity (FC) is found to be involved in ID. The purpose of this study was to explore the modulation effect of acupuncture on the resting state FC of LC in ID patients.

Methods

60 ID patients were recruited and randomly assigned to real acupuncture (RA) or sham acupuncture (SA) treatment. Resting-state functional magnetic resonance imaging (fMRI) data were collected before and after the treatment. With LC as the region of interest, the FC method was adopted to examine acupuncture-related modulation of intrinsic connectivity in ID patients. The Pittsburgh Sleep Quality Index (PSQI), Hyperarousal Scale (HAS), and actigraphy were used to assess sleep quality and cortical hyperarousal states. Associations between clinical outcomes and FC features were calculated using Pearson's correlation analysis.

Results

The improvement in sleep quality and hyperarousal in the RA group was greater than that in the SA group. After treatment, the FC between the LC and left inferior frontal gyrus (IFG) decreased in the RA group. The FC between the LC and left insula and supramarginal gyrus (SMG) was higher in the RA group. The change of LC FC values with the SMG was negatively associated with the change in PSQI scores.

Conclusion

Acupuncture can modulate FC between the LC and IFG, insular gyrus, and SMG. This may imply the potential mechanism of acupuncture treatment for insomnia.

Hippocampal atrophy in neurofunctional subfields in insomnia individuals

Objective

The aim of this study was to investigate the pattern of volume changes in neurofunctional hippocampal subfields in patients with insomnia and their associations with risk of development of insomnia.

Methods

A total of 120 patients with insomnia (78 females, 42 males; mean age ± standard deviation, 43.74 ± 13.02 years) and 120 good sleepers (67 females, 53 males; mean age, 42.69 ± 12.24 years) were recruited. The left hippocampus was segmented into anterior (L1), middle (L2), and posterior (L3) subregions. The right hippocampus was segmented into top anterior (R1), second top anterior (R2), middle (R3), posterior (R4), and last posterior (R5) subregions. Multivariate logistic regression was used to evaluate the associations of hippocampal volume (HV) of each subfield with the risk of the development of insomnia. Mediation analyses were performed to evaluate mediated associations among post-insomnia negative emotion, insomnia severity, and HV atrophy. A visual easy-to-deploy risk nomogram was used for individual prediction of risk of development of insomnia.

Results

Hippocampal volume atrophy was identified in the L1, R1, and R2 subregions. L1 and R2 volume atrophy each predisposed to an ~3-fold higher risk of insomnia (L1, odds ratio: 2.90, 95% confidence intervals: [1.24, 6.76], p = 0.014; R2, 2.72 [1.19, 6.20], p = 0.018). Anxiety fully mediates the causal path of insomnia severity leading to R1 volume atrophy with a positive effect. We developed a practical and visual competing risk-nomogram tool for individual prediction of insomnia risk, which stratifies individuals into different levels of insomnia risk with the highest prediction accuracy of 97.4% and an average C-statistic of 0.83.

Conclusion

Hippocampal atrophy in specific neurofunctional subfields was not only found to be associated with insomnia but also a significant risk factor predicting development of insomnia.

Classification of severe obstructive sleep apnea with cognitive impairment using degree centrality: A machine learning analysis

In this study, we aimed to use voxel-level degree centrality (DC) features in combination with machine learning methods to distinguish obstructive sleep apnea (OSA) patients with and without mild cognitive impairment (MCI). Ninety-nine OSA patients were recruited for rs-MRI scanning, including 51 MCI patients and 48 participants with no mild cognitive impairment. Based on the Automated Anatomical Labeling (AAL) brain atlas, the DC features of all participants were calculated and extracted. Ten DC features were screened out by deleting variables with high pin-correlation and minimum absolute contraction and performing selective operator lasso regression. Finally, three machine learning methods were used to establish classification models. The support vector machine method had the best classification efficiency (AUC = 0.78), followed by random forest (AUC = 0.71) and logistic regression (AUC = 0.77). These findings demonstrate an effective machine learning approach for differentiating OSA patients with and without MCI and provide potential neuroimaging evidence for cognitive impairment caused by OSA.

Connectomic disturbances underlying insomnia disorder and predictors of treatment response

Objective

Despite its prevalence, insomnia disorder (ID) remains poorly understood. In this study, we used machine learning to analyze the functional connectivity (FC) disturbances underlying ID, and identify potential predictors of treatment response through recurrent transcranial magnetic stimulation (rTMS) and pharmacotherapy.

Materials and methods

51 adult patients with chronic insomnia and 42 healthy age and education matched controls underwent baseline anatomical T1 magnetic resonance imaging (MRI), resting-stage functional MRI (rsfMRI), and diffusion weighted imaging (DWI). Imaging was repeated for 24 ID patients following four weeks of treatment with pharmacotherapy, with or without rTMS. A recently developed machine learning technique, Hollow Tree Super (HoTS) was used to classify subjects into ID and control groups based on their FC, and derive network and parcel-based FC features contributing to each model. The number of FC anomalies within each network was also compared between responders and non-responders using median absolute deviation at baseline and follow-up.

Results

Subjects were classified into ID and control with an area under the receiver operating characteristic curve (AUC-ROC) of 0.828. Baseline FC anomaly counts were higher in responders than non-responders. Response as measured by the Insomnia Severity Index (ISI) was associated with a decrease in anomaly counts across all networks, while all networks showed an increase in anomaly counts when response was measured using the Pittsburgh Sleep Quality Index. Overall, responders also showed greater change in all networks, with the Default Mode Network demonstrating the greatest change.

Conclusion

Machine learning analysis into the functional connectome in ID may provide useful insight into diagnostic and therapeutic targets.

Suvorexant in the Treatment of Difficulty Falling and Staying Asleep (Insomnia)

Purpose of Review

Insomnia affects more than 10% of the population and causes significant discomfort and disability. Suvorexant is an orexin receptor antagonist that specifically targets the wake-sleep cycle. This review summarizes recent and seminal evidence in the biological and physiological evidence of insomnia, the mechanism of action of suvorexant in treating insomnia, and clinical evidence regarding its use.

Recent Findings

There is no single clear diagnosis for insomnia, and thus prevalence is not entirely clear, but it is estimated to affect 10%-30% of the adult population. Comorbidities include obesity, diabetes, and various psychiatric conditions, and insomnia likely has a contributing role in these conditions. Insomnia, by definition, impacts sleep quality and also wakefulness, including academic success and work efficiency. Insomnia is likely related to genetic susceptibility and a triggering event, leading to hyper-arousal states and functional brain disturbances. This leads to hyperactivity of the hypothalamic-pituitary-adrenal axis, over-secretion of corticotropin-releasing factor, and aberrancy in neurotransmitter release. Though several pharmacological options exist for the treatment of insomnia, there is equivocal data regarding their efficacy or limits to their use due to side effects and contraindications. Suvorexant is a novel dual orexin receptor antagonist, which is shown to improve sleep by reducing arousals. Unlike classical therapeutics, suvorexant does not alter the sleep profile; it prolongs the time spent in each sleep state. Though it may cause some somnolence, it is milder than reported with other drugs.

Summary

Multiple clinical studies support the use of suvorexant in insomnia. In primary insomnia, suvorexant is effective (over placebo), as measured by polysomnography and reported by patients, in both attaining and maintaining sleep. Similar, albeit to a smaller degree, results were found in secondary insomnia. Suvorexant carries two significant advantages over existing therapies; it has a much better safety profile in approved doses, and it preserves natural sleep architecture, thus promoting more restful sleep and recovery. Unfortunately, data exists mostly for suvorexant versus placebo, and head-to-head trials with common hypnotics are needed to assess the true efficacy of suvorexant over the alternatives. And while tolerance is less likely to develop, close monitoring of post-marketing data is required to evaluate for long term adverse events and efficacy.

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.

Alterations of Resting-State Locus Coeruleus Functional Connectivity After Transdermal Trigeminal Electrical Neuromodulation in Insomnia

BACKGROUND

Transdermal trigeminal electrical neuromodulation (TTEN) is a novel treatment modality that is known for noradrenergic modulation through the trigeminal nerve and locus coeruleus (LC). This study aimed to demonstrate the alterations of LC functional connectivity (FC) in patients with insomnia after a 4-week TTEN.

METHODS

The Cefaly device targeting the ophthalmic division of the trigeminal nerve was applied to a total of 12 patients with insomnia to monitor for the effects of TTEN. All the patients went through a 4-week daily 20 min TTEN sessions before bedtime. Baseline and post-TTEN demographic data, polysomnography (PSG) parameters, and insomnia severity index (ISI) were attained. Data from pre- and post-intervention resting-state functional magnetic resonance imaging (MRI) were collected. LC FC differences were measured between the pre-and post-TTEN groups through seed-to-voxel analysis. Correlation analyses were conducted between LC FC changes after TTEN, ISI score changes, and PSG parameter changes.

RESULTS

There was a significantly decreased LC FC with occipital and temporal cortices after a 4-week TTEN. However, there was no significant correlation between LC FC, ISI score changes, and PSG parameter changes.

CONCLUSION

By targeting hyperarousal symptoms of insomnia, TTEN can be a promising intervention that can modulate LC FC in patients with insomnia patients. The data presented in the study are from a study exploring the effect of TTEN on insomnia (www.clinicaltrials.gov, NCT04838067).

Altered functional connectivity strength in chronic insomnia associated with gut microbiota composition and sleep efficiency

BACKGROUND

There is limited evidence on the link between gut microbiota (GM) and resting-state brain activity in patients with chronic insomnia (CI). This study aimed to explore the alterations in brain functional connectivity strength (FCS) in CI and the potential associations among altered FCS, GM composition, and neuropsychological performance indicators.

MATERIALS AND METHODS

Thirty CI patients and 34 age- and gender-matched healthy controls (HCs) were recruited. Each participant underwent resting-state functional magnetic resonance imaging (rs-fMRI) for the evaluation of brain FCS and was administered sleep-, mood-, and cognitive-related questionnaires for the evaluation of neuropsychological performance. Stool samples of CI patients were collected and subjected to 16S rDNA amplicon sequencing to assess the relative abundance (RA) of GM. Redundancy analysis or canonical correspondence analysis (RDA or CCA, respectively) was used to investigate the relationships between GM composition and neuropsychological performance indicators. Spearman correlation was further performed to analyze the associations among alterations in FCS, GM composition, and neuropsychological performance indicators.

RESULTS

The CI group showed a reduction in FCS in the left superior parietal gyrus (SPG) compared to the HC group. The correlation analysis showed that the FCS in the left SPG was correlated with sleep efficiency and some specific bacterial genera. The results of CCA and RDA showed that 38.21% (RDA) and 24.62% (CCA) of the GM composition variation could be interpreted by neuropsychological performance indicators. Furthermore, we found complex relationships between Alloprevotella, specific members of the family Lachnospiraceae, Faecalicoccus, and the FCS alteration, and neuropsychological performance indicators.

CONCLUSION

The brain FCS alteration of patients with CI was related to their GM composition and neuropsychological performance indicators, and there was also an association to some extent between the latter two, suggesting a specific interaction pattern among the three aspects: brain FCS alteration, GM composition, and neuropsychological performance indicators.

Decreased modulation of segregated SEEKING and selective attention systems in chronic insomnia

Sleep-related attentional bias and instinctual craving-sleep status may be associated with value-driven selective attention network and SEEKING system. We hypothesized that the two networks might be important components and underlie etiology of inability to initiate or/and maintain sleep in patients with chronic insomnia (PIs). Our aim is to investigate whether frequency-frequency couplings(temporal and spatial coupling, and differences of a set of imaging parameters) could elevate the sensibility to characterize the two insomnia-related networks in studying their relationships with sleep parameters and post-insomnia emotions. Forty-eight PIs and 48 status-matched good sleepers were requested to complete sleep and emotion-related questionnaires. Receiver operating characteristic curve was used to calculate the discriminatory power of a set of parameters. Granger causality and mediating causality analysis were used to address the causal relationships between the two networks and sleep/emotion-related parameters. Frequency-frequency couplings could characterize the two networks with high discriminatory power (AUC, 0.951; sensitivity, 87.5%; specificity, 95.8%), which suggested that the frequency-frequency couplings could be served as a useful biomarker to address the insomnia-related brain networks. Functional deficits of the SEEKING system played decreased mediator acting in post-insomnia negative emotions (decreased frequency-frequency coupling). Functional hyperarousal of the value-driven attention network played decreased mediator acting in sleep regulation (increased frequency-frequency coupling). Granger causality analysis showed decreased causal effect connectivity between and within the two networks. The between-network causal effect connectivity segregation played decreased mediator acting in sleep regulation (decreased connectivity). These findings suggest that the functional deficits and segregation of the two systems may underlie etiology of PIs.

The Instant Spontaneous Neuronal Activity Modulation of Transcutaneous Auricular Vagus Nerve Stimulation on Patients With Primary Insomnia

Primary insomnia (PI) is associated with increased spontaneous neuronal activity. Transcutaneous auricular vagus nerve stimulation (taVNS) modulates brain function, and it is an effective treatment for primary insomnia. However, whether taVNS alleviates insomnia through modulating spontaneous neuronal activity is not fully clarified. This study aims to investigate the instant effect of taVNS in modulating spontaneous neuronal activity in PI patients using resting-state functional magnetic resonance imaging (rs-fMRI). Twenty-two PI subjects underwent rs-fMRI scanning prior and immediately after 30 min treatment of taVNS controlled by twenty healthy adults. Amplitude of low frequency fluctuations (ALFF) analysis was employed to assess the difference in spontaneous neuronal activity between PI patients and healthy adults, as well as between pre-treatment and post-treatment of taVNS. The taVNS-induced altered ALFF brain areas were then selected as regions of interest to perform the resting state functional connectivity (RSFC) analysis in PI patients. The right precuneus showed significantly increased ALFF in PI patients. After immediate taVNS treatment, the ALFF was significantly decreased in the right precuneus and increased in the left middle occipital gyrus. The RSFC in right precuneus with right angular, right superior frontal gyrus, and right middle frontal gyrus was significantly decreased. This study provides insights into the instant brain effects of taVNS on PI patients.

Ventral Visual Pathway-Cerebellar Circuit Deficits in Alcohol Dependence: Long- and Short-Range Functional Connectivity Density Study

Objective: To identify the underlying intrinsic functional connectome changes in patients with alcohol dependence. Methods: A functional connectivity density (FCD) analysis was used to report on the functional connectivity changes in 24 male patients with alcohol dependence (age, 47.83 ± 6.93 years) and 24 healthy male subjects (age, 47.67 ± 6.99 years). We defined the voxels with a correlated threshold of r > 0.25 inside their neighborhood (radius sphere ≤ 6 mm) as shortFCD, and radius sphere > 6 mm as longFCD. We repeated the network analysis using a range of correlation r thresholds (r = 0.30, 0.35, 0.40, 0.45, 0.50, 0.6, and 0.75) to determine whether between-group differences were substantially affected by the selection of the different R-value thresholds used. A ROC curve was used to test the ability of the FCD in discriminating between the two groups. Pearson's correlation was used to evaluate the relationships between the FCD differences in brain areas and demographic characteristics. Results: The covered differences in brain areas in binarized shortFCD were larger than binarized longFCD in both groups. The intra-group FCD differences did not depend on the selection of different thresholds used. Patients with alcohol dependence were associated with the longFCD deficit in the cerebellum posterior lobe, and shortFCD deficit in the ventral system of the visual pathway and increased shortFCD in the left precentral gyrus, right salience network and right cingulate gyrus. A ROC curve demonstrated that these specific brain areas alone discriminated between the two groups with a high degree of sensitivity and specificity. In the alcohol dependence group, the cerebellum posterior lobe, visual association cortex and the salience network displayed significant correlations with demographic characteristics. Conclusions: The shortFCD analysis was more sensitive than the longFCD analysis in finding differences in the brain areas. The ventral visual pathway-cerebellar circuit deficit appeared to be altered in patients with alcohol dependence.

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

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

Altered Long- and Short-Range Functional Connectivity Density in Healthy Subjects After Sleep Deprivations

Objective: To investigate the brain functional organization induced by sleep deprivation (SD) using functional connectivity density (FCD) analysis.

Methods: Twenty healthy subjects (12 female, 8 male; mean age, 20.6 ± 1.9 years) participated a 24 h sleep deprivation (SD) design. All subjects underwent the MRI scan and attention network test twice, once during rested wakefulness (RW) status, and the other was after 24 h acute SD. FCD was divided into the shortFCD and longFCD. Receiver operating characteristic (ROC) curve was used to evaluate the discriminating ability of those FCD differences in brain areas during the SD status from the RW status, while Pearson correlations was used to evaluate the relationships between those differences and behavioral performances.

Results: Subjects at SD status exhibited lower accuracy rate and longer reaction time relative to RW status. Compared with RW, SD had a significant decreased shortFCD in the left cerebellum posterior lobe, right cerebellum anterior lobe, and right orbitofrontal cortex, and increased shortFCD in the left occipital gyrus, bilateral thalamus, right paracentral lobule, bilateral precentral gyrus, and bilateral postcentral gyrus. Compared with RW, SD had a significant increased longFCD in the right precentral gyrus, bilateral postcentral gyrus, and right visuospatial network, and decreased longFCD in the default mode network. The area under the curve values of those specific FCD differences in brain areas were (mean ± std, 0.933 ± 0.035; 0.863~0.977). Further ROC curve analysis demonstrated that the FCD differences in those brain areas alone discriminated the SD status from the RW status with high degree of sensitivities (89.19 ± 6%; 81.3~100%) and specificities (89.15 ± 6.87%; 75~100%). Reaction time showed a negative correlation with the right orbitofrontal cortex (r = −0.48, p = 0.032), and accuracy rate demonstrated a positive correlation with the right default mode network (r = 0.573, p = 0.008).

Conclusions: The longFCD and shortFCD analysis might be potential indicator biomarkers to locate the underlying altered intrinsic brain functional organization disturbed by SD. SD sustains the cognitive performance by the decreased high-order cognition related areas and the arousal and sensorimotor related areas.

Topological Reorganization of the Default Mode Network in Severe Male Obstructive Sleep Apnea

Impaired spontaneous regional activity and altered topology of the brain network have been observed in obstructive sleep apnea (OSA). However, the mechanisms of disrupted functional connectivity (FC) and topological reorganization of the default mode network (DMN) in patients with OSA remain largely unknown. We explored whether the FC is altered within the DMN and examined topological changes occur in the DMN in patients with OSA using a graph theory analysis of resting-state functional magnetic resonance imaging data and evaluated the relationship between neuroimaging measures and clinical variables. Resting-state data were obtained from 46 male patients with untreated severe OSA and 46 male good sleepers (GSs). We specifically selected 20 DMN subregions to construct the DMN architecture. The disrupted FC and topological properties of the DMN in patients with OSA were characterized using graph theory. The OSA group showed significantly decreased FC of the anterior-posterior DMN and within the posterior DMN, and also showed increased FC within the DMN. The DMN exhibited small-world topology in both OSA and GS groups. Compared to GSs, patients with OSA showed a decreased clustering coefficient (C_p) and local efficiency, and decreased nodal centralities in the left posterior cingulate cortex and dorsal medial prefrontal cortex, and increased nodal centralities in the ventral medial prefrontal cortex and the right parahippocampal cortex. Finally, the abnormal DMN FC was significantly related to C_p, path length, global efficiency, and Montreal cognitive assessment score. OSA showed disrupted FC within the DMN, which may have contributed to the observed topological reorganization. These findings may provide further evidence of cognitive deficits in patients with OSA.

Aberrant Effective Connectivity of the Right Anterior Insula in Primary Insomnia

Objective

Daytime cognitive impairment is an essential symptom of primary insomnia (PI). However, the underlying neural substrate remains largely unknown. Many studies have shown that the right anterior insula (rAI) as a key node of salience network (SN) plays a critical role in switching between the executive control network (ECN) and the default mode network (DMN) for better performance of cognitively demanding tasks. Aberrant effective connectivity (directional functional connectivity) of rAI with ECN or DMN may be one reason for daytime cognitive impairment in PI patients. Up to now, no effective connectivity study has been conducted on patients with PI during resting state. Our aim is to investigate the effective connectivity between the rAI and the other voxels in the whole brain in PI.

Materials and methods

Fifty drug-naive patients with PI and forty age- and sex-matched healthy controls were scanned using resting-state functional MRI. Seed-based Granger causality analysis was used to examine effective connectivity between the rAI, including ventral and dorsal part, and the whole brain. The effective connectivity was compared between the two groups and was correlated with clinical characteristics.

Results

Compared with controls, patients showed decreased effective connectivity from the rAI to the bilateral precuneus, the left postcentral gyrus (extending to bilateral precuneus) and the bilateral cerebellum posterior lobe, and decreased effective connectivity from the bilateral orbitofrontal cortex (OFC) to the rAI (single voxel P < 0.001, AlphaSim corrected with P < 0.01). In addition, effective connectivity from the ventral rAI to the left postcentral gyrus and from the left OFC to the ventral rAI were significantly negatively correlated with Insomnia Severity Index scores (r = -0.28/P = 0.046 and r = -0.29/P = 0.038, respectively).

Conclusion

The present study is the first to reveal aberrant effective connectivity between the SN hub (rAI) and the posterior DMN hub (precuneus) as well as decision-making region (OFC) and sensori-motor region in PI. These findings suggest an aberrant salience processing system of the rAI in PI patients.

Plasticity and Susceptibility of Brain Morphometry Alterations to Insufficient Sleep

Background: Insufficient sleep is common in daily life and can lead to cognitive impairment. Sleep disturbance also exists in neuropsychiatric diseases. However, whether and how acute and chronic sleep loss affect brain morphology remain largely unknown. Methods: We used voxel-based morphology method to study the brain structural changes during sleep deprivation (SD) at six time points of rested wakefulness, 20, 24, 32, 36 h SD, and after one night sleep in 22 healthy subjects, and in 39 patients with chronic primary insomnia relative to 39 status-matched good sleepers. Attention network and spatial memory tests were performed at each SD time point in the SD Procedure. The longitudinal data were analyzed using one-way repeated measures ANOVA, and post-hoc analysis was used to determine the between-group differences. Results: Acute SD is associated with widespread gray matter volume (GMV) changes in the thalamus, cerebellum, insula and parietal cortex. Insomnia is associated with increased GMV in temporal cortex, insula and cerebellum. Acute SD is associated with brain atrophy and as SD hours prolong more areas show reduced GMV, and after one night sleep the brain atrophy is restored and replaced by increased GMV in brain areas. SD has accumulative negative effects on attention and working memory. Conclusions: Acute SD and insomnia exhibit distinct morphological changes of GMV. SD has accumulative negative effects on brain morphology and advanced cognitive function. The altered GMV may provide neurobiological basis for attention and memory impairments following sleep loss.

STATEMENT OF SIGNIFICANCE

Sleep is less frequently studied using imaging techniques than neurological and psychiatric disorders. Whether and how acute and chronic sleep loss affect brain morphology remain largely unknown. We used voxel-based morphology method to study brain structural changes in healthy subjects over multiple time points during sleep deprivation (SD) status and in patients with chronic insomnia. We found that prolonged acute SD together with one night sleep recovery exhibits accumulative atrophic effect and recovering plasticity on brain morphology, in line with behavioral changes on attentional tasks. Furthermore, acute SD and chronic insomnia exhibit distinct morphological changes of gray matter volume (GMV) but they also share overlapping GMV changes. The altered GMV may provide structural basis for attention and memory impairments following sleep loss.