Reduced dynamic functional connectivity between salience and executive brain networks in insomnia disorder

Improvements in Sleep Quality in Patients With Major Depressive and Generalized Anxiety Disorders Treated With Individualized, Parcel-Guided Transcranial Magnetic Stimulation

INTRODUCTION

Poor quality sleep has often been cited as a cause of lowered quality of life in patients with affective disorders such as major depressive disorder (MDD) and generalized anxiety disorder (GAD). As sleep and affective disorders are affected by multi-network interactions, we hypothesize that the modulation of the central executive network (CEN), salience, and default mode networks (DMNs) through individualized repetitive transcranial magnetic stimulation (rTMS) may improve sleep and quality of life.

METHODS

A retrospective analysis from 2020 to 2023 was conducted in patients with affective disorders at Cingulum Health. Multiple targets were selected based on anomalies detected from individual, functional connectivity networks from a machine-learning connectivity software. rTMS was conducted with accelerated continuous or intermittent theta burst stimulation (TBS) based on the anomaly detected. Pittsburgh Sleep Quality Index (PSQI), EuroQol (EQ5D), Beck's Depression Inventory (BDI), and the General Anxiety Disorder-7 (GAD-7) questionnaires were administered prior to, after, and at follow-up of rTMS.

RESULTS

Twenty-seven patients were identified, and the most common diagnoses were MDD (41%) or MDD with GAD (41%). All patients had at least one rTMS target in the CEN. The most common target (19 patients) was L8Av in the dorsolateral prefrontal cortex (dlPFC). Patients experienced significant improvements in sleep, quality of life, depressive, and anxiety symptoms after rTMS and during follow-up. Improvements in sleep correlated with quality of life at follow-up.

CONCLUSION

This study suggests that personalized, parcel-guided rTMS is safe and may provide sustained improvements in sleep, quality of life, and affective symptoms for patients with affective disorders.

Reproducible, data-driven characterization of sleep based on brain dynamics and transitions from whole-night fMRI

Understanding the function of sleep requires studying the dynamics of brain activity across whole-night sleep and their transitions. However, current gold standard polysomnography (PSG) has limited spatial resolution to track brain activity. Additionally, previous fMRI studies were too short to capture full sleep stages and their cycling. To study whole-brain dynamics and transitions across whole-night sleep, we used an unsupervised learning approach, the Hidden Markov model (HMM), on two-night, 16 hr fMRI recordings of 12 non-sleep-deprived participants who reached all PSG-based sleep stages. This method identified 21 recurring brain states and their transition probabilities, beyond PSG-defined sleep stages. The HMM trained on one night accurately predicted the other, demonstrating unprecedented reproducibility. We also found functionally relevant subdivisions within rapid eye movement (REM) and within non-REM 2 stages. This study provides new insights into brain dynamics and transitions during sleep, aiding our understanding of sleep disorders that impact sleep transitions.

Reproducible, data-driven characterization of sleep based on brain dynamics and transitions from whole-night fMRI

Understanding the function of sleep requires studying the dynamics of brain activity across whole-night sleep and their transitions. However, current gold standard polysomnography (PSG) has limited spatial resolution to track brain activity. Additionally, previous fMRI studies were too short to capture full sleep stages and their cycling. To study whole-brain dynamics and transitions across whole-night sleep, we used an unsupervised learning approach, the Hidden Markov model (HMM), on two-night, 16-hour fMRI recordings of 12 non-sleep-deprived participants who reached all PSG-based sleep stages. This method identified 21 recurring brain states and their transition probabilities, beyond PSG-defined sleep stages. The HMM trained on one night accurately predicted the other, demonstrating unprecedented reproducibility. We also found functionally relevant subdivisions within rapid eye movement (REM) and within non-REM 2 stages. This study provides new insights into brain dynamics and transitions during sleep, aiding our understanding of sleep disorders that impact sleep transitions.

Increased functional connectivity within the salience network in patients with insomnia

BACKGROUND

Insomnia is a common sleep disorder with significant negative impacts on emotional states; however, the underlying mechanism of insomnia with comorbid emotional dysregulation remains largely unknown. The salience network (SN) plays an important role in both sleep and emotional regulation. The study aimed to explore the specific alterations in functional connectivity (FC) within the SN in insomnia patients.

METHODS

A total of 30 eligible patients with insomnia disorder (ID group) and 30 healthy controls (HC group) underwent resting-state functional magnetic resonance imaging (fMRI) scanning and psychometric assessments. Differences in FC within the SN were examined using seed-based region-to-region connectivity analysis.

RESULTS

Compared with healthy controls, patients with insomnia showed increased FC within the SN, mainly between the anterior cingulate cortex (ACC) and right superior frontal gyrus (SFG), the right SFG and right supramarginal gyrus (SMG), and between the right insular (INS) and left SMG (P<0.05). Additionally, significant correlations were observed between increased FC and the Hamilton Depression Rating Scale (HAMD), Pittsburgh Sleep Quality Index (PSQI), and Hamilton Anxiety Rating Scale (HAMA) scores (P<0.05, after Bonferroni correction).

CONCLUSIONS

These results suggest that increased FC within the SN may be related to poor sleep quality and negative emotions, highlighting the importance of the SN in the pathophysiological mechanisms of insomnia with comorbid emotional dysregulation.

Exercise intervention in middle-aged and elderly individuals with insomnia improves sleep and restores connectivity in the motor network

Exercise is a potential treatment to improve sleep quality in middle-aged and elderly individuals. Understanding exercise-induced changes in functional plasticity of brain circuits that underlie improvements in sleep among middle-aged and older adults can inform treatment of sleep problems. The aim of the study is to identify the effects of a 12-week exercise program on sleep quality and brain functional connectivity in middle-aged and older adults with insomnia. The trial was registered with Chinese Clinical Trial Register (ChiCTR2000033652). We recruited 84 healthy sleepers and 85 individuals with insomnia. Participants with insomnia were assigned to receive either a 12-week exercise intervention or were placed in a 12-week waitlist control condition. Thirty-seven middle-aged and older adults in the exercise group and 30 in the waitlist group completed both baseline and week 12 assessments. We found that middle-aged and older adults with insomnia showed significantly worse sleep quality than healthy sleepers. At the brain circuit level, insomnia patients showed decreased connectivity in the widespread motor network. After exercise intervention, self-reported sleep was increased in the exercise group (P < 0.001) compared to that in the waitlist group. We also found increased functional connectivity of the motor network with the cerebellum in the exercise group (P < 0.001). Moreover, we observed significant correlations between improvement in subjective sleep indices and connectivity changes within the motor network. We highlight exercise-induced improvement in sleep quality and functional plasticity of the aging brain.

Top-down and bottom-up alterations of connectivity patterns of the suprachiasmatic nucleus in chronic insomnia disorder

The importance of the suprachiasmatic nucleus (SCN, also called the master circadian clock) in regulating sleep and wakefulness has been confirmed by multiple animal research. However, human studies of SCN in vivo are still nascent. Recently, the development of resting-state functional magnetic resonance imaging (fMRI) has made it possible to study SCN-related connectivity changes in patients with chronic insomnia disorder (CID). Hence, this study aimed to explore whether sleep-wake circuitry (i.e., communication between the SCN and other brain regions) is disrupted in human insomnia. Forty-two patients with CID and 37 healthy controls (HCs) underwent fMRI scanning. Resting-state functional connectivity (rsFC) and Granger causality analysis (GCA) were performed to find abnormal functional and causal connectivity of the SCN in CID patients. In addition, correlation analyses were conducted to detect associations between features of disrupted connectivity and clinical symptoms. Compared to HCs, CID patients showed enhanced rsFC of the SCN-left dorsolateral prefrontal cortex (DLPFC), as well as reduced rsFC of the SCN-bilateral medial prefrontal cortex (MPFC); these altered cortical regions belong to the "top-down" circuit. Moreover, CID patients exhibited disrupted functional and causal connectivity between the SCN and the locus coeruleus (LC) and the raphe nucleus (RN); these altered subcortical regions constitute the "bottom-up" pathway. Importantly, the decreased causal connectivity from the LC-to-SCN was associated with the duration of disease in CID patients. These findings suggest that the disruption of the SCN-centered "top-down" cognitive process and "bottom-up" wake-promoting pathway may be intimately tied to the neuropathology of CID.

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.

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.

Cognitive, Disability, and Treatment Outcome Implications of Symptom-Based Phenotyping in Late-Life Depression

OBJECTIVE

Late-life depression is associated with substantial heterogeneity in clinical presentation, disability, and response to antidepressant treatment. We examined whether self-report of severity of common symptoms, including anhedonia, apathy, rumination, worry, insomnia, and fatigue were associated with differences in presentation and response to treatment. We also examined whether these symptoms improved during treatment with escitalopram.

DESIGN

Eighty-nine older adults completed baseline assessments, neuropsychological testing and providing self-reported symptom and disability scales. They then entered an 8-week, placebo-controlled randomized trial of escitalopram, and self-report scales were repeated at the trial's end. Raw symptom scale scores were combined into three standardized symptom phenotypes and models examined how symptom phenotype severity was associated with baseline measures and depression improvement over the trial.

RESULTS

While rumination/worry appeared independent, severity of apathy/anhedonia and fatigue/insomnia were associated with one another and with greater self-reported disability. Greater fatigue/insomnia was also associated with slower processing speed, while rumination/worry was associated with poorer episodic memory. No symptom phenotype severity score predicted a poorer overall response to escitalopram. In secondary analyses, escitalopram did not improve most phenotypic symptoms more than placebo, aside for greater reductions in worry and total rumination severity.

CONCLUSION

Deeper symptom phenotype characterization may highlight differences in the clinical presentation of late-life depression. However, when compared to placebo, escitalopram did not improve many of the symptoms assessed. Further work is needed to determine whether symptom phenotypes inform longer-term course of illness, and which treatments may best benefit specific symptoms.

Neuroimaging profiles of the negative affective network predict anxiety severity in patients with chronic insomnia disorder: A machine learning study

BACKGROUND

Sleep is instrumental in safeguarding emotional well-being. While the susceptibility to both insomnia and anxiety has been demonstrated to involve intricate brain systems, the neuroimaging profile of chronic insomnia disorder with comorbid anxiety symptoms (CID-A) remains unexplored. Employing machine learning methodologies, this study aims to elucidate the distinct neural substrates underlying CID-A and to investigate whether these cerebral markers can prognosticate anxiety symptoms in patients with insomnia.

METHODS

Functional magnetic resonance imaging (fMRI) data were procured from a relatively large cohort (dataset 1) comprised of 47 CID-A patients, 49 CID patients without anxiety (CID-NA), and 48 good sleeper controls (GSC). Aberrant cerebral functional alterations were assessed through functional connectivity strength (FCS) and resting-state functional connectivity (rsFC). Subsequently, Support Vector Regression (SVR) models were constructed to predict anxiety symptoms in CID patients based on neuroimaging features, which were validated utilizing an external cohort (dataset 2).

RESULTS

In comparison to CID-NA and GSC subjects, CID-A patients exhibited heightened FCS in the right dorsomedial prefrontal cortex (DMPFC), a central hub within the negative affective network. Moreover, the SVR models revealed that DMPFC-related rsFC/FCS features could be employed to predict anxiety symptoms in two independent cohorts of CID patients.

LIMITATION

Modifications in brain functionality might vary across insomnia subtypes.

CONCLUSION

The present findings suggest a potential negative affective network model for the neuropathophysiology of CID accompanied by anxiety. Importantly, the negative affective network pattern may serve as a predictor for anxiety symptoms in CID patients.

Alterations in the global brain network in older adults with poor sleep quality: A resting-state fMRI study

OBJECTIVES

Older adults often experience more fragmented and less restful sleep than younger individuals. However, the mechanisms in the brain that underlie these phenomena have been rarely studied. The aim of this study was to identify the differences in global brain network properties between older adults with good and poor sleep quality and to explore the relationship between these network properties and symptoms of insomnia.

METHODS

We performed a graph-theoretic analysis of resting-state functional magnetic resonance imaging data from two groups of older adults: 59 with good sleep quality and 59 with poor sleep quality. Functional connectivity among 264 brain regions of interest was estimated, and undirected graphs were constructed. Network topological properties were compared using one-way repeated-measures analysis of variance. Pearson's correlation analysis assessed the relationship between the mean scores of the global network properties across network sparsity and insomnia symptoms, as measured using the global Pittsburgh Sleep Quality Index score.

RESULTS

Older adults with poor sleep quality displayed increased small-world-ness, global efficiency and modularity in the functional brain network during rest. Conversely, they exhibited decreased local efficiency, characteristic path length and clustering coefficient. In the total population, we found associations between insomnia symptoms and global network characteristics, except for betweenness centrality and modularity.

CONCLUSIONS

In older adults with poor sleep quality, global network measures revealed a functional brain architecture that tended towards integration rather than segregation. Further research is needed to better understand what these findings mean about the effects of aging on poor sleep quality.

Cerebellum and hippocampus abnormalities in patients with insomnia comorbid depression: a study on cerebral blood perfusion and functional connectivity

Chronic insomnia disorder and major depressive disorder are highly-occurred mental diseases with extensive social harm. The comorbidity of these two diseases is commonly seen in clinical practice, but the mechanism remains unclear. To observe the characteristics of cerebral blood perfusion and functional connectivity in patients, so as to explore the potential pathogenesis and biological imaging markers, thereby improving the understanding of their comorbidity mechanism. 44 patients with chronic insomnia disorder comorbid major depressive disorder and 43 healthy controls were recruited in this study. The severity of insomnia and depression were assessed by questionnaire. The cerebral blood perfusion and functional connectivity values of participants were obtained to, analyze their correlation with questionnaire scores. The cerebral blood flow in cerebellum, vermis, right hippocampus, left parahippocampal gyrus of patients were reduced, which was negatively related to the severity of insomnia or depression. The connectivities of left cerebellum-right putamen and right hippocampus-left inferior frontal gyrus were increased, showing positive correlations with the severity of insomnia and depression. Decreased connectivities of left cerebellum-left fusiform gyrus, left cerebellum-left occipital lobe, right hippocampus-right paracentral lobule, right hippocampus-right precentral gyrus were partially associated with insomnia or depression. The connectivity of right hippocampus-left inferior frontal gyrus may mediate between insomnia and depression. Insomnia and depression can cause changes in cerebral blood flow and brain function. Changes in the cerebellar and hippocampal regions are the result of insomnia and depression. They reflect abnormalities in sleep and emotion regulation. That may be involved in the pathogenesis of comorbidity.

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.

Altered functional connectivity of the default mode and frontal control networks in patients with insomnia

AIMS

The purpose of this study was to investigate the association between spontaneous regional activity and brain functional connectivity, which maybe can distinguish insomnia while being responsive to repetitive transcranial magnetic stimulation (rTMS) treatment effects in insomnia patients.

METHODS

Using resting-state functional magnetic resonance imaging data from 38 chronic insomnia patients and 36 healthy volunteers, we compared the amplitude of low-frequency fluctuations (ALFF) between the two groups. Of all the patients with insomnia, 20 received rTMS for 4 weeks, while 18 patients received a 4-week pseudo-stimulation intervention. Seed-based resting-state functional connectivity (RSFC) analysis was conducted from regions with significantly different ALFF values, and the association between RSFC value and Pittsburgh Sleep Quality Index score was determined.

RESULTS

Our results revealed that insomnia patients presented a significantly higher ALFF value in the posterior cingulate cortex (PCC), whereas a significantly lower ALFF value was observed in the superior parietal lobule (SPL). Moreover, significantly reduced RSFC was detected from both PCC to prefrontal cortex connections, as well as from left SPL to frontal pole connections. In addition, RSFC from frontal pole to left SPL negatively predicted sleep quality (PSQI) and treatment response in patients' group.

CONCLUSION

Our findings suggest that disrupted frontoparietal network connectivity may be a biomarker for insomnia in middle-aged adults, reinforcing the potential of rTMS targeting the frontal lobes. Monitoring pretreatment RSFC could offer greater insight into how rTMS treatments are responded to by insomniacs.

Predicting insomnia severity using structure-function coupling in female chronic insomnia patients

Functional connectivity between brain regions is constrained by the underlying structural pathways. However, how this structure-function coupling is disrupted in female patients with insomnia disorder is unclear. This study examines if the whole-brain pattern of structure-function coupling could be used to predict unseen female patients' insomnia severity index. Resting-state functional MRI and diffusion-weighted imaging were performed in 82 female participants with chronic insomnia. Structure-function coupling was computed using the Spearman rank correlations between structural and functional connectivity profiles. Using relevance vector regression approach and 10-fold cross-validation, we predicted the individuals' insomnia severity index using the pattern of whole-brain structure-function coupling. Finally, we extracted the contribution of each regional coupling to the prediction model. The pattern of structure-function coupling could be used to significantly predict unseen individuals' insomnia severity index scores (r = 0.29, permutation P < 0.001; mean absolute error (MAE) = 4.59, permutation P < 0.001). Moreover, the brain regions with high functional hierarchy, including regions in the default mode network, mainly displayed negative contribution weights, while the regions with lower functional hierarchy, including occipital regions and the precentral gyrus, mainly displayed positive contribution weights. This is the first study to demonstrate an association between structure-function coupling and the insomnia severity index in females with insomnia disorder. Importantly, our data suggest that insomnia severity is associated with a reduction in structure-function coupling in higher-order brain regions and an increase in structure-function coupling in lower-order brain regions.

Sex differences in the effects of sleep disorders on cognitive dysfunction

Sleep is an essential physiological function that sustains human life. Sleep disorders involve problems with the quality, duration, and abnormal behaviour of sleep. Insomnia is the most common sleep disorder, followed by sleep-disordered breathing (SDB). Sleep disorders often occur along with medical conditions or other mental health conditions. Of particular interest to researchers is the role of sleep disorders in cognitive dysfunction. Sleep disorder is a risk factor for cognitive dysfunction, yet the exact pathogenesis is still far from agreement. Little is known about how sex differences influence the changes in cognitive functions caused by sleep disorders. This narrative review examines how sleep disorders might affect cognitive impairment, and then explores the sex-specific consequences of sleep disorders as a risk factor for dementia and the potential underlying mechanisms. Some insights on the direction of further research are also presented.

Insomnia attenuates response inhibition: Evidence from Go/NoGo research

OBJECTIVE

Varied cognitive dysfunctions including memory, attention, inputs, processing and filtration have been found in insomnia. Meanwhile, evidence from functional neuroimaging have revealed that the abnormal metabolism in prefrontal cortex was associated with probable deficit of executive function. And in our study, we have detected the response inhibition in insomnia patients by Go/NoGo,an Event-related potentials (ERPs) study, in order to explore the impaired executive function, because response inhibition is a hallmark of executive function.

METHODS

We used polysomnography (PSG) to record such objective PSG parameters. Go/NoGo was performed in sequence, different ERP components have been analyzed such as latency or amplitude between insomnia group and control group. And we used Person correlation coefficient R to make analysis between different ERP components and gender, duration, education, BMI and sleep characteristics.

RESULTS

On the behavioral level, we found a little poor performance insomnia participants. On the electrophysiological level, under Go condition, insomnia participants have prolonged latency and smaller amplitude of N2 or P3. While, under NoGo condition, insomnia participants also have longer latency, but higher amplitude of N2 or P3. another major finding was that different correlation was found between gender,anxiety-depression,duration, education,BMI,sleep characteristics and N2 or P3.

DISCUSSION

Our study has revealed that sleep loss may influence the response inhibition ability in insomnia, not only on behavior level, but also on the electrophysiological level. Abnormal changes in inhibition process or inhibition supervision can be represented as N2/P3 components under Go/No-go condition. Additionally, correlation analysis has been found between gender, anxiety-depression, BMI, education, and sleep structure. Thus, sleep loss attenuates response inhibition and impairs executive function in insomnia participants.

Adolescents with a concussion have altered brain network functional connectivity one month following injury when compared to adolescents with orthopedic injuries

Concussion is a mild traumatic brain injury (mTBI) with increasing prevalence among children and adolescents. Functional connectivity (FC) within and between the default mode network (DMN), central executive network (CEN) and salience network (SN) has been shown to be altered post-concussion. Few studies have investigated connectivity within and between these 3 networks following a pediatric concussion. The present study explored whether within and between-network FC differs between a pediatric concussion and orthopedic injury (OI) group aged 10-18. Participants underwent a resting-state functional magnetic resonance imaging (rs-fMRI) scan at 4 weeks post-injury. One-way ANCOVA analyses were conducted between groups with the seed-based FC of the 3 networks. A total of 55 concussion and 27 OI participants were included in the analyses. Increased within-network FC of the CEN and decreased between-network FC of the DMN-CEN was found in the concussion group when compared to the OI group. Secondary analyses using spherical SN regions of interest revealed increased within-network FC of the SN and increased between-network FC of the DMN-SN and CEN-SN in the concussion group when compared to the OI group. This study identified differential connectivity patterns following a pediatric concussion as compared to an OI 4 weeks post-injury. These differences indicate potential adaptive brain mechanisms that may provide insight into recovery trajectories and appropriate timing of treatment within the first month following a concussion.

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.

Functional connectivity changes in insomnia disorder: A systematic review

Insomnia (ID) is the most common sleep disorder; however pathogenetic mechanisms underlying ID symptoms are not fully understood. Adopting a multifactorial view and considering ID a condition that involves interregional neuronal coordination would be useful to understand the ID pathophysiology. Functional connectivity (FC) may help to shed light on functional processes and neural correlates underlying ID symptoms. Despite a growing number of studies assessing FC anomalies, insight into ID pathophysiology is still fragmentary. This systematic review aims to search empirical evidence regarding FC changes in ID during resting-state. Thirty-one studies involving 1052 ID participants met the inclusion criteria for this review. Results suggested several associations between ID symptoms and impaired intra- and inter-hemispheric interactions of principal resting-state networks. Overall, evidence supported the hypothesis that a disrupted organization of the brain functional connectome characterizes ID, resulting in a decline in sleep, cognition, emotion, and memory. However, the wide methodological heterogeneity between reviewed studies and limitations in terms of study protocols and statistical approaches raised from this systematic review, makes it difficult to provide a univocal framework of ID pathophysiology. Future researches in this field should lead towards shared and rigorous search designs to ensure solid research evidence in the ID pathophysiology.

Validity and reliability of the Turkish version of the insomnia catastrophizing scale

Insomnia catastrophizing has attracted attention in recent years. Individuals may have started to recognize the importance of evaluating the consequences of insomnia, which has worsened during the coronavirus disease 2019 (COVID-19) pandemic. The present study aimed to test the validity and reliability of the Insomnia Catastrophizing Scale (ICS) in the Turkish young adult population. The study group consisted of a total of 387 participants: 57 in the pilot study and 330 in the main study. The majority of the participants in the study were females. According to the results of the confirmatory factor analysis, the single-factor structures of the ICS nighttime and daytime forms were confirmed to be the same as in the original structure, and the fit indices were above the acceptable limits. The ICS forms had very high reliability. The findings of the present study showed that the Turkish daytime and nighttime forms of the ICS are valid and reliable instruments. The results provide a means of measuring insomnia catastrophizing for use in therapeutic and counseling settings for Turkish young adult population. We also propose that mental health practitioners should design interventions to reduce insomnia catastrophizing in Turkish culture.

Supplementary Information

The online version contains supplementary material available at 10.1007/s41105-021-00336-7.

Severe sleep disturbance is associated with executive function impairment in patients with first-episode, treatment-naïve major depressive disorders

BACKGROUND

Sleep disturbance and executive function impairment are common in patients with major depressive disorder (MDD), though the relationship between the two remains unclear. We investigated this association in first-episode, treatment-naïve patients with MDD.

METHODS

We analyzed data from 242 patients with MDD. We divided the patients into 2 groups based on sleep disturbance severity and compared the executive function odds ratios between the groups.

RESULTS

A total of 121 pairs of patients were matched (age 39.4 ± 10.1, 70.2% female). After propensity score matching, the odds ratios for cognitive impairment in patients with MDD and severe sleep disturbance were 1.922 (1.068-3.459, P = 0.029, q = 0.044) in executive functioning; 2.023 (1.211-3.379, P = 0.007, q = 0.021) in executive shifting.

CONCLUSIONS

Sleep disturbance is associated with executive functioning impairment in first-episode, treatment-naïve patients with MDD. Severe sleep disturbance can be a marker and aid in recognizing executive function impairment in patients with first-episode treatment-naïve MDD. Severe sleep disturbance can be a potential modifiable factor to improve executive function in MDD, as well as an effective measurement to improve cognition for sleep symptom management that should be enforced at initial treatment of first-episode MDD. Further study is required to confirm our results.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT02023567 ; registration date: December 2013.

Why Do They Fall? The Impact of Insomnia on Gait of Older Adults: A Case-Control Study

STUDY OBJECTIVES

To compare gait and cognitive performance conducted separately as a single- (ST) and simultaneously as a dual-task (DT), ie, when a cognitive task was added, among community-dwelling older adults with and without insomnia.

METHODS

Participants included: 39 (28 females) community-dwelling older adults with insomnia, 34 (21 females) controls without insomnia. Subject groups were matched for age, gender, and education. Sleep quality was evaluated based on two-week actigraphy. Gait speed and cognition were assessed as ST and DT performance. DT costs (DTCs) were calculated for both tasks. Outcomes were compared via independent samples t-tests or Mann-Whitney U-tests.

RESULTS

Older adults with insomnia demonstrated significantly slower gait speed during ST (1 ± 0.29 vs 1.27 ± 0.17 m/s, p<0.001) and DT (0.77 ± 0.26 vs 1.14 ± 0.20 m/s, p<0.001) and fewer correct responses in the cognitive task during ST (21 ± 7 vs 27 ± 11, p=0.009) and DT (19 ± 7 vs 23 ± 9, p=0.015) compared to control group. DTC for the gait task was higher among older adults with insomnia (18.32%, IQR: 9.48-30.93 vs 7.81% IQR: 4.43-14.82, p<0.001). However, no significant difference was observed in DTC for the cognitive task (14.71%, IQR: -0.89-38.84 vs 15%, IQR: -0.89-38.84%, p=0.599).

CONCLUSION

Older adults with insomnia have lower gait speed and poorer cognitive performance during ST and DT and an inefficient pattern of task prioritization during walking, compared to counterparts without insomnia. These findings may explain the higher risk of falls among older adults with insomnia. Geriatric professionals should be aware of potential interrelationships between sleep and gait.

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.

Assessing Cognitive Abilities of Patients With Shift Work Disorder: Insights From RBANS and Granger Causality Connections Among Resting-State Networks

BACKGROUND

Numerous studies have confirmed that long-term shift work is not only associated with increased health problems and acute impact on safety but also with impaired cognitive abilities. However, very little is known about effects of shift work on cognition-related brain resting-state networks. The aim of this study was to explore the effects of shift work disorder (SWD) on granger causality connection among resting-state brain networks.

METHODS

Thirty patients with SWD and 25 matched healthy subjects were recruited to undergo the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and resting-state fMRI scanning. We employed independent component analysis (ICA) to extract resting-state brain networks and granger causality analysis (GCA) to characterize the difference of granger causality connection among cognition-related resting-state brain networks.

RESULTS

Compared with healthy subjects, patients with SWD showed impairments on the attention and immediate memory. Seven resting-state brain networks were identified, and patients with SWD showed more numerous granger causality connections in comparison with healthy subjects. Two-sample t test results showed that there were significantly increased inflows from the anterior default mode network (aDMN) to sensorimotor network (SMN) and left frontoparietal network (LFPN) to salience network (SN). Correlation analyses showed that the increased inflows from aDMN to SMN were negatively associated with the score of attention, while LFPN to SN were negatively associated with the score of visuospatial/constructional ability.

CONCLUSIONS

This study indicates that SWD impairs cognitive performance, and the specific intrinsic brain granger causality connectivity among resting-state networks in SWD patients is affected after long-term shift works.

Reduced dynamic functional connectivity between salience and executive brain networks in insomnia disorder

Research into insomnia disorder has pointed to large-scale brain network dysfunctions. Dynamic functional connectivity is instrumental to cognitive functions but has not been investigated in insomnia disorder. This study assessed between-network functional connectivity strength and variability in patients with insomnia disorder as compared with matched controls without sleep complaints. Twelve-minute resting-state functional magnetic resonance images and T1-weighed images were acquired in 65 people diagnosed with insomnia disorder (21-69 years, 48 female) and 65 matched controls without sleep complaints (22-70 years, 42 female). Pairwise correlations between the activity time series of 14 resting-state networks and temporal variability of the correlations were compared between cases and controls. After false discovery rate correction for multiple comparisons, people with insomnia disorder and controls did not differ significantly in terms of mean between-network functional connectivity strength; people with insomnia disorder did, however, show less functional connectivity variability between the anterior salience network and the left executive-control network. The finding suggests less flexible interactions between the networks during the resting state in people with insomnia disorder.