Common and distinct brain networks underlying panic and social anxiety disorders

Resting-state fMRI is associated with trauma experiences, mood and psychosis in Afro-descendants with bipolar disorder and schizophrenia

BACKGROUND

Bipolar disorder (BD) and schizophrenia (SCZ) may exhibit functional abnormalities in several brain areas, including the medial temporal and prefrontal cortex and hippocampus; however, a less explored topic is how brain connectivity is linked to premorbid trauma experiences and clinical features in non-Caucasian samples of SCZ and BD.

METHODS

Sixty-two individuals with SCZ (n = 20), BD (n = 21), and healthy controls (HC, n = 21) from indigenous and African ethnicity were submitted to clinical screening (Di-PAD), traumata experiences (ETISR-SF), cognitive and functional MRI assessment. The item psychosis/hallucinations in SCZ patients showed a negative correlation with the global efficiency (GE) in the right dorsal attention network. The items mania, irritable mood, and racing thoughts in the Di-PAD scale had a significant negative correlation with the GE in the parietal right default mode network.

CONCLUSIONS

Differences in the activation of specific networks were associated with earlier disease onset, history of physical abuse, and more severe psychotic and mood symptoms in SCZ and BD subjects of indigenous and black ethnicity. Findings provide further evidence on SZ and BD's brain connectivity disturbances, and their clinical significance, in non-Caucasian samples.

A framework for a brain-derived nosology of psychiatric disorders

Current psychiatric diagnoses are not defined by neurobiological measures which hinders the development of therapies targeting mechanisms underlying mental illness 1,2 . Research confined to diagnostic boundaries yields heterogeneous biological results, whereas transdiagnostic studies often investigate individual symptoms in isolation. There is currently no paradigm available to comprehensively investigate the relationship between different clinical symptoms, individual disorders, and the underlying neurobiological mechanisms. Here, we propose a framework that groups clinical symptoms derived from ICD-10/DSM-V according to shared brain mechanisms defined by brain structure, function, and connectivity. The reassembly of existing ICD-10/DSM-5 symptoms reveal six cross-diagnostic psychopathology scores related to mania symptoms, depressive symptoms, anxiety symptoms, stress symptoms, eating pathology, and fear symptoms. They were consistently associated with multimodal neuroimaging components in the training sample of young adults aged 23, the independent test sample aged 23, participants aged 14 and 19 years, and in psychiatric patients. The identification of symptom groups of mental illness robustly defined by precisely characterized brain mechanisms enables the development of a psychiatric nosology based upon quantifiable neurobiological measures. As the identified symptom groups align well with existing diagnostic categories, our framework is directly applicable to clinical research and patient care.

Enhanced interhemispheric resting-state functional connectivity of the visual network is an early treatment response of paroxetine in patients with panic disorder

This study aimed to detect alterations in interhemispheric interactions in patients with panic disorder (PD), determine whether such alterations could serve as biomarkers for the diagnosis and prediction of therapeutic outcomes, and map dynamic changes in interhemispheric interactions in patients with PD after treatment. Fifty-four patients with PD and 54 healthy controls (HCs) were enrolled in this study. All participants underwent clinical assessment and a resting-state functional magnetic resonance imaging scan at (i) baseline and (ii) after paroxetine treatment for 4 weeks. A voxel-mirrored homotopic connectivity (VMHC) indicator, support vector machine (SVM), and support vector regression (SVR) were used in this study. Patients with PD showed reduced VMHC in the fusiform, middle temporal/occipital, and postcentral/precentral gyri, relative to those of HCs. After treatment, the patients exhibited enhanced VMHC in the lingual gyrus, relative to the baseline data. The VMHC of the fusiform and postcentral/precentral gyri contributed most to the classification (accuracy = 87.04%). The predicted changes were accessed from the SVR using the aberrant VMHC as features. Positive correlations (p < 0.001) were indicated between the actual and predicted changes in the severity of anxiety. These findings suggest that impaired interhemispheric coordination in the cognitive-sensory network characterized PD and that VMHC can serve as biomarkers and predictors of the efficiency of PD treatment. Enhanced VMHC in the lingual gyrus of patients with PD after treatment implied that pharmacotherapy recruited the visual network in the early stages.

Microstructural white matter alterations associated with social anxiety disorders: A systematic review

BACKGROUND

Social anxiety disorder (SAD) is a psychiatric condition characterized by impaired social functioning that negatively impacts individuals' quality of life. Previous neuroimaging studies have revealed morphological and functional changes in various brain regions associated with SAD. Recent advances in diffusion tensor imaging (DTI) and diffusion-weighted imaging (DWI) have enabled the investigation of microstructural white matter (WM) alterations in SAD. This study aims to provide an overview of DTI/DWI studies exploring WM microstructure changes in SAD.

METHODS

A systematic search on PubMed, Scopus, Web of Science, and PsycINFO was conducted for relevant records on July 8, 2023. An exploratory meta-analysis was also performed.

RESULTS

Eight studies were reviewed. Consistent findings indicated reduced fractional anisotropy and increased diffusivity measures in different WM tracts in SAD patients compared to healthy controls. These alterations were mostly observed within regions of the fronto-limbic network, like uncinate fasciculus (UF) and superior and inferior longitudinal fasciculi (SLF and ILF). Finally, our exploratory meta-analysis on four studies utilizing a voxel-wise analytic approach yielded no significant differences between SAD patients and controls.

LIMITATIONS

Limited number of studies, small sample sizes, and heterogeneity in analysis methods.

CONCLUSIONS

Patients with SAD exhibited altered WM integrity, particularly in the UF, SLF, and ILF, compared to healthy controls. However, due to the limited number of included studies, our meta-analysis yielded no significant differences between SAD patients and controls. Therefore, future research is crucial to unravel the link between altered WM structure and the involvement of other limbic and cortical structures in SAD pathogenesis.

Specific alterations of resting-state functional connectivity in the triple network related to comorbid anxiety in major depressive disorder

The brain's default mode network (DMN) and the executive control network (ECN) switch engagement are influenced by the ventral attention network (VAN). Alterations in resting-state functional connectivity (RSFC) within this so-called triple network have been demonstrated in patients with major depressive disorder (MDD) or anxiety disorders (ADs). This study investigated alterations in the RSFC in patients with comorbid MDD and ADs to better understand the pathophysiology of this prevalent group of patients. Sixty-eight participants (52.9% male, mean age 35.3 years), consisting of 25 patients with comorbid MDD and ADs (MDD + AD), 20 patients with MDD only (MDD) and 23 healthy controls (HCs) were investigated clinically and with 3T resting-state fMRI. RSFC utilizing a seed-based approach within the three networks belonging to the triple network was compared between the groups. Compared with HC, MDD + AD showed significantly reduced RSFC between the ECN and the VAN, the DMN and the VAN and within the ECN. No differences could be found for the MDD group compared with both other groups. Furthermore, symptom severity and medication status did not affect RSFC values. The results of this study show a distinct set of alterations of RSFC for patients with comorbid MDD and AD compared with HCs. This set of dysfunctions might be related to less adequate switching between the DMN and the ECN as well as poorer functioning of the ECN. This might contribute to additional difficulties in engaging and utilizing consciously controlled emotional regulation strategies.

A model for the diagnosis of anxiety in patients with epilepsy based on phase locking value and Lempel-Ziv complexity features of the electroencephalogram

OBJECTIVE

Anxiety disorders (AD) are critical factors that significantly (about one-fifth) impact the quality of life (QoL) in patients with epilepsy (PWE). Objective diagnostic methods have contributed to the identification of PWE susceptible to AD. This study aimed to identify AD in PWE by constructing a diagnostic model based on the phase locking value (PLV) and Lempel-Ziv Complexity (LZC) features of the electroencephalogram (EEG).

METHODS

EEG data from 131 patients with epilepsy (PWE) were enrolled in this study. Patients were divided into two groups, anxiety disorder (AD, n = 61) and non-anxiety disorder (NAD, n = 70), according to the Hamilton Rating Scale for Anxiety (HAM-A). Support vector machine (SVM) and K-Nearest-Neighbor(KNN) algorithms were used to construct three models - the PLVEEG, LZCEEG, and PLVEEG + LZCEEG feature models. Finally, the area under the receiver operating characteristic curve (AUC) and statistical analyses were performed to evaluate the model performance.

RESULTS

The efficiency of the KNN-based PLCEEG + LZCEEG feature model was the best, and the accuracy, precision, recall, F1-score, and AUC of the model after five-fold cross-validations scores were 87.89 %, 82.27 %, 98.33 %, 88.95 %, and 0.89, respectively. When the model efficiency was optimal, 29 EEG features were suggested. Further analysis of these features indicated 22 EEG features that were significantly different between the two groups, including 50 % features of the alpha (α)-band.

CONCLUSIONS

The PLVEEG + LZCEEG model features can identify AD in PWE. The PLVEEG and LZCEEG characteristics of the α-band may further be explored as potential biomarkers for AD in PWE.

Electrophysiological signatures of anxiety in Parkinson's disease

Anxiety is a common non-motor symptom in Parkinson's disease (PD) occurring in up to 31% of the patients and affecting their quality of life. Despite the high prevalence, anxiety symptoms in PD are often underdiagnosed and, therefore, undertreated. To date, functional and structural neuroimaging studies have contributed to our understanding of the motor and cognitive symptomatology of PD. Yet, the underlying pathophysiology of anxiety symptoms in PD remains largely unknown and studies on their neural correlates are missing. Here, we used resting-state electroencephalography (RS-EEG) of 68 non-demented PD patients with or without clinically-defined anxiety and 25 healthy controls (HC) to assess spectral and functional connectivity fingerprints characterizing the PD-related anxiety. When comparing the brain activity of the PD anxious group (PD-A, N = 18) to both PD non-anxious (PD-NA, N = 50) and HC groups (N = 25) at baseline, our results showed increased fronto-parietal delta power and decreased frontal beta power depicting the PD-A group. Results also revealed hyper-connectivity networks predominating in delta, theta and gamma bands against prominent hypo-connectivity networks in alpha and beta bands as network signatures of anxiety in PD where the frontal, temporal, limbic and insular lobes exhibited the majority of significant connections. Moreover, the revealed EEG-based electrophysiological signatures were strongly associated with the clinical scores of anxiety and followed their progression trend over the course of the disease. We believe that the identification of the electrophysiological correlates of anxiety in PD using EEG is conducive toward more accurate prognosis and can ultimately support personalized psychiatric follow-up and the development of new therapeutic strategies.

Default Mode Network Hypoalignment of Function to Structure Correlates With Depression and Rumination

BACKGROUND

Recent studies have begun to examine how signals in the brain correspond to the underlying white matter structure using tools from the field of graph signal processing to quantify brain function alignment to brain network topology. Here, we applied this framework for the first time toward a transdiagnostic cohort of individuals with internalizing psychopathologies, including mood and anxiety disorders, to uncover how such alignment within the default mode network (DMN) is related to depression and rumination symptoms.

METHODS

Both diffusion-weighted and resting-state functional magnetic resonance imaging were obtained from participants at baseline (n = 60 patients, n = 19 healthy control participants). Patients were randomized to 12 weeks of treatment with either a selective serotonin reuptake inhibitor or cognitive behavioral therapy, and symptom scales were readministered posttreatment (n = 46 patients at follow-up). Using graph signal processing methodology, we quantified the alignment of functional signals to their underlying white matter structural networks.

RESULTS

We found that signal alignment within the posterior DMN was decreased in patients with internalizing psychopathologies compared with healthy control participants and was inversely (negatively) correlated with baseline depression and rumination scales. Signal alignment within the posterior DMN was also correlated with the ratio of total within-DMN to extra-DMN functional connectivity for these regions.

CONCLUSIONS

These findings are consistent with previous literature regarding pathological promiscuity of posterior DMN connectivity and provide the first graph signal processing-based analyses in a transdiagnostic cohort of patients with internalizing psychopathologies.

Internalizing Symptoms and Adverse Childhood Experiences Associated With Functional Connectivity in a Middle Childhood Sample

BACKGROUND

Research has found overlapping associations in adults of resting-state functional connectivity (RSFC) to both internalizing disorders (e.g., depression, anxiety) and a history of traumatic events. The present study aimed to extend this previous research to a younger sample by examining RSFC associations with both internalizing symptoms and adverse childhood experiences (ACEs) in middle childhood.

METHODS

We used generalized linear mixed models to examine associations between a priori within- and between-network RSFC with child-reported internalizing symptoms and ACEs using the Adolescent Brain Cognitive Development dataset (N = 10,168, mean age = 9.95 years, SD = 0.627).

RESULTS

We found that internalizing symptoms and ACEs were associated with both multiple overlapping and unique RSFC network patterns. Both ACEs and internalizing symptoms were associated with a reduced anticorrelation between the default mode network and the dorsal attention network. However, internalizing symptoms were uniquely associated with lower within-network default mode network connectivity, while ACEs were uniquely associated with both lower between-network connectivity of the auditory network and cingulo-opercular network, and higher within-network frontoparietal network connectivity.

CONCLUSIONS

The present study points to overlap in the RSFC associations with internalizing symptoms and ACEs, as well as important areas of specificity in RSFC associations. Many of the RSFC associations found have been previously implicated in attentional control functions, including modulation of attention to sensory stimuli. This may have critical importance in understanding internalizing symptoms and outcomes of ACEs.

Altered resting-state cerebellar-cerebral functional connectivity in patients with panic disorder before and after treatment

The study aimed to investigate the functional connectivity (FC) between the cerebellum and intrinsic cerebral networks in patients with panic disorder (PD), and to observe changes in the cerebellar-cerebral FC following pharmacotherapy. Fifty-four patients with PD and 54 healthy controls (HCs) underwent clinical assessments and functional magnetic resonance imaging scans before and after a 5-week paroxetine treatment. Seed-based cerebellar-cerebral FC was compared between the PD and HC groups, as well as between patients with PD before and after treatment. Additionally, the correlations between FC and clinical features of PD were analyzed. Compared to HCs, patients with PD had altered cerebellar-cerebral FC in the default mode, affective-limbic, and sensorimotor networks. Moreover, a negative correlation between cerebellar-insula disconnection and the severity of depressive symptoms in patients with PD (Pearson correlation, r = -0.424, p = 0.001, Bonferroni corrected) was found. After treatment, most of the enhanced FCs observed in patients with PD at baseline returned to levels similar to those observed in HCs. However, the reduced FC at baseline did not significantly change after treatment. The findings suggest that patients with PD have specific deficits in resting-state cerebellar-cerebral FC and that paroxetine may improve PD by restoring the balance of cerebellar-cerebral FC. These findings emphasize the crucial involvement of cerebellar-cerebral FC in the neuropsychological mechanisms underlying PD and in the potential pharmacological mechanisms of paroxetine for treating PD.

Breaking the Fear Barrier: Aberrant Activity of Fear Networks as a Prognostic Biomarker in Patients with Panic Disorder Normalized by Pharmacotherapy

Panic disorder (PD) is a prevalent type of anxiety disorder. Previous studies have reported abnormal brain activity in the fear network of patients with PD. Nonetheless, it remains uncertain whether pharmacotherapy can effectively normalize these abnormalities. This longitudinal resting-state functional magnetic resonance imaging study aimed to investigate the spontaneous neural activity in patients with PD and its changes after pharmacotherapy, with a focus on determining whether it could predict treatment response. The study included 54 drug-naive patients with PD and 54 healthy controls (HCs). Spontaneous neural activity was measured using regional homogeneity (ReHo). Additionally, support vector regression (SVR) was employed to predict treatment response from ReHo. At baseline, PD patients had aberrant ReHo in the fear network compared to HCs. After 4 weeks of paroxetine treatment (20 mg/day), a significant increase in ReHo was observed in the left fusiform gyrus, which had shown reduced ReHo before treatment. The SVR analysis showed significantly positive correlations (p < 0.0001) between the predicted and actual reduction rates of the severity of anxiety and depressive symptoms. Here, we show patients with PD had abnormal spontaneous neural activities in the fear networks. Furthermore, these abnormal spontaneous neural activities can be partially normalized by pharmacotherapy and serve as candidate predictors of treatment response. Gaining insight into the trajectories of brain activity normalization following treatment holds the potential to provide vital insights for managing PD.

Resting-state fMRI functional connectivity and clinical correlates in Afro-descendants with schizophrenia and bipolar disorder

Schizophrenia (SCZ) and bipolar disorder (BD) exhibited altered activation in several brain areas, including the prefrontal and temporal cortex; however, a less explored topic is how brain connectivity and functional disturbances occur in non-Caucasian samples of SCZ and BD. Individuals with SCZ (n=20), BD (n=21), and healthy controls (HC, n=21) from indigenous and African ethnicity were submitted to clinical screening and functional assessments. Mood, compulsive and psychotic symptoms were also correlated to network dysfunction in each group. Two distinct networks' subcomponents demonstrated significant lower global efficiency (GE) in SCZ versus HC, corresponding to left posterior dorsal attention and medial left ventral attention (VA) networks. Lower GE was found in BD versus controls in four subcomponents, including the left medial and right VA. Higher compulsion scores correlated in BD with lower GE in the left VA, whereas increased report of alcohol abuse was associated with higher GE in left default mode network. Although preliminary, differences in the activation of specific networks, notably the left hemisphere, in SCZ versus controls, and lower activation in VA areas, in BD versus controls. Results highlight default mode and salient network as relevant for the emotional processing of SCZ and BD of indigenous and black ethnicity. Abstract: schizophrenia, bipolar disorder, functional neuroimaging, ethnicity, default network.

Long-term benefits of mindfulness on white matter tracts underlying the cortical midline structures in panic disorder: A 2-year longitudinal study

AIMS

We aimed to examine the long-term benefits of mindfulness-based cognitive therapy (MBCT) on white matter plasticity in the cortical midline structures (CMS) for a period of 2 years in patients with panic disorder and the relationships between white matter changes in the CMS and severity of state and trait symptoms.

METHODS

Seventy-one participants were enrolled and underwent diffusion tensor imaging at baseline and after 2 years (26 who received MBCT as an adjunct to pharmacotherapy [MBCT+PT], 20 treated with pharmacotherapy alone [PT-alone], and 25 healthy controls [HCs]). The severity of symptoms and fractional anisotropy (FA) in white matter regions underlying the CMS were assessed at baseline and 2-year follow-up.

RESULTS

The MBCT+PT group showed better outcomes after 2 years than the PT-alone group. The groups showed different FA changes: the MBCT+PT group showed decreased FA in the left anterior cingulate cortex (ACC); the PT-alone group showed increased FA in the bilateral dorsomedial prefrontal cortex, posterior cingulate cortex (PCC), and precuneus. Decreased white matter FA in the ACC, PCC, and precuneus was associated with improvements in the severity of state and trait symptoms in patients with panic disorder.

CONCLUSION

Alleviation of excessive white matter connectivity in the CMS after MBCT leads to improvements in clinical symptoms and trait vulnerability in patients with panic disorder. Our study provides new evidence for the long-term benefits of MBCT on white matter plasticity and its clinical applicability as a robust treatment for panic disorder.

Machine learning for the detection of social anxiety disorder using effective connectivity and graph theory measures

Introduction

The early diagnosis and classification of social anxiety disorder (SAD) are crucial clinical support tasks for medical practitioners in designing patient treatment programs to better supervise the progression and development of SAD. This paper proposes an effective method to classify the severity of SAD into different grading (severe, moderate, mild, and control) by using the patterns of brain information flow with their corresponding graphical networks.

Methods

We quantified the directed information flow using partial directed coherence (PDC) and the topological networks by graph theory measures at four frequency bands (delta, theta, alpha, and beta). The PDC assesses the causal interactions between neuronal units of the brain network. Besides, the graph theory of the complex network identifies the topological structure of the network. Resting-state electroencephalogram (EEG) data were recorded for 66 patients with different severities of SAD (22 severe, 22 moderate, and 22 mild) and 22 demographically matched healthy controls (HC).

Results

PDC results have found significant differences between SAD groups and HCs in theta and alpha frequency bands (p < 0.05). Severe and moderate SAD groups have shown greater enhanced information flow than mild and HC groups in all frequency bands. Furthermore, the PDC and graph theory features have been used to discriminate three classes of SAD from HCs using several machine learning classifiers. In comparison to the features obtained by PDC, graph theory network features combined with PDC have achieved maximum classification performance with accuracy (92.78%), sensitivity (95.25%), and specificity (94.12%) using Support Vector Machine (SVM).

Discussion

Based on the results, it can be concluded that the combination of graph theory features and PDC values may be considered an effective tool for SAD identification. Our outcomes may provide new insights into developing biomarkers for SAD diagnosis based on topological brain networks and machine learning algorithms.

The neurobiology of irritable bowel syndrome

Irritable bowel syndrome (IBS) is the most prevalent disorder of brain-gut interactions that affects between 5 and 10% of the general population worldwide. The current symptom criteria restrict the diagnosis to recurrent abdominal pain associated with altered bowel habits, but the majority of patients also report non-painful abdominal discomfort, associated psychiatric conditions (anxiety and depression), as well as other visceral and somatic pain-related symptoms. For decades, IBS was considered an intestinal motility disorder, and more recently a gut disorder. However, based on an extensive body of reported information about central, peripheral mechanisms and genetic factors involved in the pathophysiology of IBS symptoms, a comprehensive disease model of brain-gut-microbiome interactions has emerged, which can explain altered bowel habits, chronic abdominal pain, and psychiatric comorbidities. In this review, we will first describe novel insights into several key components of brain-gut microbiome interactions, starting with reported alterations in the gut connectome and enteric nervous system, and a list of distinct functional and structural brain signatures, and comparing them to the proposed brain alterations in anxiety disorders. We will then point out the emerging correlations between the brain networks with the genomic, gastrointestinal, immune, and gut microbiome-related parameters. We will incorporate this new information into a systems-based disease model of IBS. Finally, we will discuss the implications of such a model for the improved understanding of the disorder and the development of more effective treatment approaches in the future.

Infraslow closed-loop brain training for anxiety and depression (ISAD): a protocol for a randomized, double-blind, sham-controlled pilot trial in adult females with internalizing disorders

Background

The core intrinsic connectivity networks (core-ICNs), encompassing the default-mode network (DMN), salience network (SN) and central executive network (CEN), have been shown to be dysfunctional in individuals with internalizing disorders (IDs, e.g. major depressive disorder, MDD; generalized anxiety disorder, GAD; social anxiety disorder, SOC). As such, source-localized, closed-loop brain training of electrophysiological signals, also known as standardized low-resolution electromagnetic tomography (sLORETA) neurofeedback (NFB), targeting key cortical nodes within these networks has the potential to reduce symptoms associated with IDs and restore normal core ICN function. We intend to conduct a randomized, double-blind (participant and assessor), sham-controlled, parallel-group (3-arm) trial of sLORETA infraslow (<0.1 Hz) fluctuation neurofeedback (sLORETA ISF-NFB) 3 times per week over 4 weeks in participants (n=60) with IDs. Our primary objectives will be to examine patient-reported outcomes (PROs) and neurophysiological measures to (1) compare the potential effects of sham ISF-NFB to either genuine 1-region ISF-NFB or genuine 2-region ISF-NFB, and (2) assess for potential associations between changes in PRO scores and modifications of electroencephalographic (EEG) activity/connectivity within/between the trained regions of interest (ROIs). As part of an exploratory analysis, we will investigate the effects of additional training sessions and the potential for the potentiation of the effects over time.

Methods

We will randomly assign participants who meet the criteria for MDD, GAD, and/or SOC per the MINI (Mini International Neuropsychiatric Interview for DSM-5) to one of three groups: (1) 12 sessions of posterior cingulate cortex (PCC) ISF-NFB up-training (n=15), (2) 12 sessions of concurrent PCC ISF up-training and dorsal anterior cingulate cortex (dACC) ISF-NFB down-training (n=15), or (3) 6 sessions of yoked-sham training followed by 6 sessions genuine ISF-NFB (n=30). Transdiagnostic PROs (Hospital Anxiety and Depression Scale, HADS; Inventory of Depression and Anxiety Symptoms – Second Version, IDAS-II; Multidimensional Emotional Disorder Inventory, MEDI; Intolerance of Uncertainty Scale – Short Form, IUS-12; Repetitive Thinking Questionnaire, RTQ-10) as well as resting-state neurophysiological measures (full-band EEG and ECG) will be collected from all subjects during two baseline sessions (approximately 1 week apart) then at post 6 sessions, post 12 sessions, and follow-up (1 month later). We will employ Bayesian methods in R and advanced source-localisation software (i.e. exact low-resolution brain electromagnetic tomography; eLORETA) in our analysis.

Discussion

This protocol will outline the rationale and research methodology for a clinical pilot trial of sLORETA ISF-NFB targeting key nodes within the core-ICNs in a female ID population with the primary aims being to assess its potential efficacy via transdiagnostic PROs and relevant neurophysiological measures.

Trial registration

Our study was prospectively registered with the Australia New Zealand Clinical Trials Registry (ANZCTR; Trial ID: ACTRN12619001428156). Registered on October 15, 2019.

Large-scale dysfunctional white matter and grey matter networks in patients with social anxiety disorder

Dysfunction of large-scale brain networks has been implicated in social anxiety disorder (SAD); most work has focused on grey matter (GM) functional connectivity (FC) abnormalities, whereas white matter (WM) FC alterations remain unclear. Here, using a K-means clustering algorithm, we obtained 8 GM and 10 WM functional networks from a cohort dataset (48 SAD patients and 48 healthy controls). By calculating and comparing FC matrices between SAD group and healthy controls, we demonstrated disrupted connections between the limbic and dorsal prefrontal, lateral temporal, and sensorimotor networks, and between the visual and sensorimotor networks. Furthermore, there were negative correlations between HAMD scores and limbic-dorsal prefrontal and limbic-sensorimotor networks, and between illness duration and sensorimotor-visual networks. These findings reflect the critical role of limbic network, with its extensive connections to other networks, and the neurobiology of disordered cognition processing and emotional regulation in SAD.

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Anomalous interactions between large-scale functional networks were identified in SAD

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The limbic, prefrontal, and perceptual networks underlie the neurobiology of SAD

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The white matter functional network is physiologically important

Predicting social anxiety in young adults with machine learning of resting-state brain functional radiomic features

Social anxiety is a symptom widely prevalent among young adults, and when present in excess, can lead to maladaptive patterns of social behavior. Recent approaches that incorporate brain functional radiomic features and machine learning have shown potential for predicting certain phenotypes or disorders from functional magnetic resonance images. In this study, we aimed to predict the level of social anxiety in young adult participants by training machine learning models with resting-state brain functional radiomic features including the regional homogeneity, fractional amplitude of low-frequency fluctuation, fractional resting-state physiological fluctuation amplitude, and degree centrality. Among the machine learning models, the XGBoost model achieved the best performance with balanced accuracy of 77.7% and F1 score of 0.815. Analysis of input feature importance demonstrated that the orbitofrontal cortex and the degree centrality were most relevant to predicting the level of social anxiety among the input brain regions and the input type of radiomic features, respectively. These results suggest potential validity for predicting social anxiety with machine learning of the resting-state brain functional radiomic features and provide further understanding of the neural basis of the symptom.

Neurochemical Alterations in Social Anxiety Disorder (SAD): A Systematic Review of Proton Magnetic Resonance Spectroscopic Studies

(1) Objective: Considering that current knowledge of mechanisms involved in the molecular pathogenesis of Social Anxiety Disorder (SAD) is limited, we conducted a systematic review to evaluate cumulative data obtained by Proton Magnetic Resonance Spectroscopic (¹H MRS) studies. (2) Methods: A computer-based literature search of Medline, EMBASE, PsycInfo, and ProQuest was performed. Only cross-sectional studies using ¹H MRS techniques in participants with SAD and healthy controls (HCs) were selected. (3) Results: The search generated eight studies. The results indicated regional abnormalities in the ‘fear neurocircuitry’ in patients with SAD. The implicated regions included the anterior cingulate cortex (ACC), dorsomedial prefrontal cortex (dmPFC), dorsolateral prefrontal cortex (dlPFC), insula, occipital cortex (OC), as well as the subcortical regions, including the thalamus, caudate, and the putamen. (4) Conclusions: The evidence derived from eight studies suggests that possible pathophysiological mechanisms of SAD include impairments in the integrity and function of neurons and glial cells, including disturbances in energy metabolism, maintenance of phospholipid membranes, dysregulations of second messenger systems, and excitatory/inhibitory neurocircuitry. Conducting more cross-sectional studies with larger sample sizes is warranted given the limited evidence in this area of research.

Network Diffusion Embedding Reveals Transdiagnostic Subnetwork Disruption and Potential Treatment Targets in Internalizing Psychopathologies

Network diffusion models are a common and powerful way to study the propagation of information through a complex system and they offer straightforward approaches for studying multimodal brain network data. We developed an analytic framework to identify brain subnetworks with perturbed information diffusion capacity using the structural basis that best maps to resting state functional connectivity and applied it towards a heterogeneous dataset of internalizing psychopathologies (IPs), a set of psychiatric conditions in which similar brain network deficits are found across the swath of the disorders, but a unifying neuropathological substrate for transdiagnostic symptom expression is currently unknown. This research provides preliminary evidence of a transdiagnostic brain subnetwork deficit characterized by information diffusion impairment of the right area 8BM, a key brain region involved in organizing a broad spectrum of cognitive tasks, which may underlie previously reported dysfunction of multiple brain circuits in the IPs. We also demonstrate that models of neuromodulation involving targeting this brain region normalize IP diffusion dynamics towards those of healthy controls. These analyses provide a framework for multimodal methods that identify both brain subnetworks with disrupted information diffusion and potential targets of these subnetworks for therapeutic neuromodulatory intervention based on previously well-characterized methodology.

Validity and utility of Hierarchical Taxonomy of Psychopathology (HiTOP): III. Emotional dysfunction superspectrum

The Hierarchical Taxonomy of Psychopathology (HiTOP) is a quantitative nosological system that addresses shortcomings of traditional mental disorder diagnoses, including arbitrary boundaries between psychopathology and normality, frequent disorder co-occurrence, substantial heterogeneity within disorders, and diagnostic unreliability over time and across clinicians. This paper reviews evidence on the validity and utility of the internalizing and somatoform spectra of HiTOP, which together provide support for an emotional dysfunction superspectrum. These spectra are composed of homogeneous symptom and maladaptive trait dimensions currently subsumed within multiple diagnostic classes, including depressive, anxiety, trauma-related, eating, bipolar, and somatic symptom disorders, as well as sexual dysfunction and aspects of personality disorders. Dimensions falling within the emotional dysfunction superspectrum are broadly linked to individual differences in negative affect/neuroticism. Extensive evidence establishes that dimensions falling within the superspectrum share genetic diatheses, environmental risk factors, cognitive and affective difficulties, neural substrates and biomarkers, childhood temperamental antecedents, and treatment response. The structure of these validators mirrors the quantitative structure of the superspectrum, with some correlates more specific to internalizing or somatoform conditions, and others common to both, thereby underlining the hierarchical structure of the domain. Compared to traditional diagnoses, the internalizing and somatoform spectra demonstrated substantially improved utility: greater reliability, larger explanatory and predictive power, and greater clinical applicability. Validated measures are currently available to implement the HiTOP system in practice, which can make diagnostic classification more useful, both in research and in the clinic.

A Two-Person Neuroscience Approach for Social Anxiety: A Paradigm With Interbrain Synchrony and Neurofeedback

Social anxiety disorder has been widely recognised as one of the most commonly diagnosed mental disorders. Individuals with social anxiety disorder experience difficulties during social interactions that are essential in the regular functioning of daily routines; perpetually motivating research into the aetiology, maintenance and treatment methods. Traditionally, social and clinical neuroscience studies incorporated protocols testing one participant at a time. However, it has been recently suggested that such protocols are unable to directly assess social interaction performance, which can be revealed by testing multiple individuals simultaneously. The principle of two-person neuroscience highlights the interpersonal aspect of social interactions that observes behaviour and brain activity from both (or all) constituents of the interaction, rather than analysing on an individual level or an individual observation of a social situation. Therefore, two-person neuroscience could be a promising direction for assessment and intervention of the social anxiety disorder. In this paper, we propose a novel paradigm which integrates two-person neuroscience in a neurofeedback protocol. Neurofeedback and interbrain synchrony, a branch of two-person neuroscience, are discussed in their own capacities for their relationship with social anxiety disorder and relevance to the paradigm. The newly proposed paradigm sets out to assess the social interaction performance using interbrain synchrony between interacting individuals, and to employ a multi-user neurofeedback protocol for intervention of the social anxiety.

Resting-state neuroimaging in social anxiety disorder: a systematic review

There has been a growing interest in resting-state brain alterations in people with social anxiety disorder. However, the evidence has been mixed and contested and further understanding of the neurobiology of this disorder may aid in informing methods to increase diagnostic accuracy and treatment targets. With this systematic review, we aimed to synthesize the findings of the neuroimaging literature on resting-state functional activity and connectivity in social anxiety disorder, and to summarize associations between brain and social anxiety symptoms to further characterize the neurobiology of the disorder. We systematically searched seven databases for empirical research studies. Thirty-five studies met the inclusion criteria, with a total of 1611 participants (795 people with social anxiety disorder and 816 controls). Studies involving resting-state seed-based functional connectivity analyses were the most common. Individuals with social anxiety disorder (vs. controls) displayed both higher and lower connectivity between frontal-amygdala and frontal-parietal regions. Frontal regions were the most consistently implicated across other analysis methods, and most associated with social anxiety symptoms. Small sample sizes and variation in the types of analyses used across studies may have contributed to the inconsistencies in the findings of this review. This review provides novel insights into established neurobiological models of social anxiety disorder and provides an update on what is known about the neurobiology of this disorder in the absence of any overt tasks (i.e., resting state). The knowledge gained from this body of research enabled us to also provide recommendations for a more standardized imaging pre-processing approach to examine resting-state brain activity and connectivity that could help advance knowledge in this field. We believe this is warranted to take the next step toward clinical translation in social anxiety disorder that may lead to better treatment outcomes by informing the identification of neurobiological targets for treatment.

ENIGMA-anxiety working group: Rationale for and organization of large-scale neuroimaging studies of anxiety disorders

Anxiety disorders are highly prevalent and disabling but seem particularly tractable to investigation with translational neuroscience methodologies. Neuroimaging has informed our understanding of the neurobiology of anxiety disorders, but research has been limited by small sample sizes and low statistical power, as well as heterogenous imaging methodology. The ENIGMA-Anxiety Working Group has brought together researchers from around the world, in a harmonized and coordinated effort to address these challenges and generate more robust and reproducible findings. This paper elaborates on the concepts and methods informing the work of the working group to date, and describes the initial approach of the four subgroups studying generalized anxiety disorder, panic disorder, social anxiety disorder, and specific phobia. At present, the ENIGMA-Anxiety database contains information about more than 100 unique samples, from 16 countries and 59 institutes. Future directions include examining additional imaging modalities, integrating imaging and genetic data, and collaborating with other ENIGMA working groups. The ENIGMA consortium creates synergy at the intersection of global mental health and clinical neuroscience, and the ENIGMA-Anxiety Working Group extends the promise of this approach to neuroimaging research on anxiety disorders.

The Effects of Cardiorespiratory and Motor Skill Fitness on Intrinsic Functional Connectivity of Neural Networks in Individuals with Parkinson's Disease

Background:

Studies in aging older adults have shown the positive association between cognition and exercise related fitness, particularly cardiorespiratory fitness. These reports have also demonstrated the association of high cardiorespiratory fitness, as well as other types of fitness, on the reversal of age-related decline in neural network connectivity, highlighting the potential role of fitness on age- and disease-related brain changes. While the clinical benefits of exercise are well-documented in Parkinson’s disease (PD), the extent to which cardiorespiratory fitness (assessed by estimated VO_2max testing) or motor skill fitness (assessed by the Physical Performance Test (PPT)) affects neural network connectivity in PD remains to be investigated. The purpose of this study was to explore the hypothesis that higher fitness level is associated with an increase in the intrinsic network connectivity of cognitive networks commonly affected in PD.

Methods:

In this cross-sectional resting state fMRI, we used a multivariate statistical approach based on high-dimensional independent component analysis (ICA) to investigate the association between two independent fitness metrics (estimated VO_2max and PPT) and resting state network connectivity.

Results:

We found that increased estimated VO_2max was associated with increased within network connectivity in cognitive networks known to be impaired in PD, including those sub-serving memory and executive function. There was a similar trend for high levels of PPT to be associated with increased within network connectivity in distinct resting state networks. The between functional network connectivity analysis revealed that cardiorespiratory fitness was associated with increased functional connectivity between somatosensory motor network and several cognitive networks sub-serving memory, attention, and executive function.

Conclusion:

This study provides important empirical data supporting the potential association between two forms of fitness and multiple resting state networks impacting PD cognition. Linking fitness to circuit specific modulation of resting state network connectivity will help establish a neural basis for the positive effects of fitness and specific exercise modalities and provide a foundation to identify underlying mechanisms to promote repair.

Intrinsic Network Brain Dysfunction Correlates With Temporal Complexity in Generalized Anxiety Disorder and Panic Disorder

Background: Generalized anxiety disorder (GAD) and panic disorder (PD) are the two severe subtypes of anxiety disorders (ADs), which are similar in clinical manifestation, pathogenesis, and treatment. Earlier studies have taken a whole-brain perspective on GAD and PD in the assumption that intrinsic fluctuations are static throughout the entire scan. However, it has recently been suggested that the dynamic alternations in functional connectivity (FC) may reflect the changes in macroscopic neural activity patterns underlying the critical aspects of cognition and behavior, and thus may act as biomarkers of disease. Methods: In this study, the resting-state functional MRI (fMRI) data were collected from 26 patients with GAD, 22 patients with PD, and 26 healthy controls (HCs). We investigated dynamic functional connectivity (DFC) by using the group spatial independent component analysis, a sliding window approach, and the k-means clustering methods. For group comparisons, the temporal properties of DFC states were analyzed statistically. Results: The dynamic analysis demonstrated two discrete connectivity "States" across the entire group, namely, a more segregated State I and a strongly integrated State II. Compared with HCs, patients with both GAD and PD spent more time in the weakly within-network State I, while performing fewer transitions and dwelling shorter in the integrated State II. Additionally, the analysis of DFC strength showed that connections associated with ADs were identified including the regions that belonged to default mode (DM), executive control (EC), and salience (SA) networks, especially the connections between SA and DM networks. However, no significant difference was found between the GAD and PD groups in temporal features and connection strength. Conclusions: More common but less specific alterations were detected in the GAD and PD groups, which implied that they might have similar state-dependent neurophysiological mechanisms and, in addition, could hopefully help us better understand their abnormal affective and cognitive performances in the clinic.

Intrinsic functional connectivity in families genetically enriched for social anxiety disorder - an endophenotype study

BACKGROUND

Social anxiety disorder (SAD) is a serious psychiatric condition with a high prevalence, and a typical onset during childhood/adolescence. The condition runs in families, but it is largely unknown which neurobiological characteristics transfer this genetic vulnerability ('endophenotypes'). Using data from the Leiden Family Lab study on SAD, including two generations of families genetically enriched for SAD, we investigated whether social anxiety (SA) co-segregated with changes in intrinsic functional connectivity (iFC), and examined heritability.

METHODS

Functional MRI data were acquired during resting-state in 109 individuals (56 males; mean age: 31·5, range 9·2-61·5 years). FSL's tool MELODIC was used to perform independent component analysis. Six networks of interest (default mode, dorsal attention, executive control, frontoparietal, limbic and salience) were identified at the group-level and used to generate subject-specific spatial maps. Voxel-wise regression models, with SA-level as predictor and voxel-wise iFC as candidate endophenotypes, were performed to investigate the association with SA, within masks of the networks of interest. Subsequently, heritability was estimated.

FINDINGS

SA co-segregated with iFC within the dorsal attention network (positive association in left middle frontal gyrus and right postcentral gyrus) and frontoparietal network (positive association within left middle temporal gyrus) (cluster-forming-threshold z>2·3, cluster-corrected extent-threshold p<0·05). Furthermore, iFC of multiple voxels within these clusters was at least moderately heritable.

INTERPRETATION

These findings provide initial evidence for increased iFC as candidate endophenotype of SAD, particularly within networks involved in attention. These changes might underlie attentional biases commonly present in SAD.

FUNDING

Leiden University Research Profile 'Health, Prevention and the Human Lifecycle'.

Out-of-step: brain-heart desynchronization in anxiety disorders

Imaging studies in anxiety disorders (AD) show abnormal functional connectivity primarily in the salience network (SN), somatomotor network (SMN), and default mode network (DMN). However, it is not clear how precisely these network changes occur including their relation to psychopathological symptoms. Here, we show that the functional networks affected in AD overlap with cortical regions that receive visceral inputs (the so-called central/visceral autonomic network). Focusing on cardiac afferents, we suggest that network changes in AD may be due to reduced phase synchronization between ongoing neural and cardiac activity. This neuro-cardiac desynchronization occurs due to the abnormal phase resetting of neural activity at the onset of each heartbeat, as measured by a lower intertrial coherence and heartbeat-evoked potential. Biochemically, cardiac afferents reach subcortical serotonergic raphe nuclei and noradrenergic locus coeruleus (among others) which, in turn, are known to reciprocally modulate the DMN and SMN/SN on the cortical level. Consistent with the network changes in AD, decreases in serotonergic and noradrenergic activity are known to increase connectivity in both SMN and SN while, at the same time, they decrease DMN connectivity. SMN and SN increases, in turn, lead to increased emotional arousal/anxiety and bodily awareness whereas decreased DMN connectivity leads to an unstable sense-of-self in AD. Finally, we integrate our proposal with interoceptive predictive processing models suggesting neuro-cardiac desynchronization as a mechanism for "noisy" bottom-up information leading to a persistently uncertain bodily state in top-down models. In sum, integrating theories on active interference and hyperarousal, we propose a precise neuro-cardiac and biochemically -driven mechanisms for key psychopathological symptoms of AD.

Disruption of functional and structural networks in first-episode, drug-naïve adolescents with generalized anxiety disorder

BACKGROUND

Individuals with generalized anxiety disorder (GAD) tend to worry exaggeratedly and uncontrollably about various daily routines. Previous studies have demonstrated that the GAD patients exhibited widespread alternations in both functional networks (FN) and structural networks (SN). However, the simultaneous alternations of the topological organization of FN, SN, as well as their couplings in GAD still remain unknown.

METHODS

Using multimodal approach, we constructed FN from resting-state functional magnetic imaging (R-fMRI) data and SN from diffusion magnetic resonance imaging (dMRI) data of 32 adolescent GAD patients and 25 healthy controls (HC). Graph theory analysis was employed to investigate the topological properties of FN, SN, and FN-SN coupling.

RESULTS

Compared to HC, the GAD patients showed disruptions in global (i.e., decreased clustering coefficient, global, and local efficiency) and subnetwork (i.e., reduced intermodular connections, rich club, and feeder connections) levels in FN. Abnormal global level properties (i.e., increased characteristic path length and reduced global efficiency) were also observed in SN. Altered FN-SN couplings in normalized characteristic path length and feeder connections were identified in the GAD patients. The identified network measures were correlated with anxiety severity in the GAD patients.

LIMITATIONS

The sample size of the current study is small and the cross-sectional nature can not infer causal relationship.

CONCLUSIONS

Our findings identified GAD-related topological alternations in both FN and SN, together with the couplings between FN and SN, providing us with a novel perspective for understanding the pathophysiological mechanisms of GAD.

Initial white matter connectivity differences between remitters and non-remitters of patients with panic disorder after 6 months of pharmacotherapy

Panic disorder (PD) is a harmful mental condition that causes relapsed and persistent impairment. In the treatment of PD, the prognosis for PD should be considered. However, the relationship between pharmacotherapy and biomarkers, for predicting a better response through neuroimaging, is a little known. The purpose of the present study was to examine whether there would be the initial white matter (WM) regions associated with the remission in 6 months. A total of 104 patients with PD were investigated in the study. After six months, there were 17 remission patients with PD and 81 non-remission patients. The Panic Disorder Severity Scale, Albany Panic and Phobia Questionnaire, Anxiety Sensitivity Inventory-Revised, Beck Anxiety Inventory, and Beck Depression Inventory were assessed for all patients at baseline. We compared the diffusion indices between remission and non-remission group at 6 months using Tract-Based Spatial Statistics. The results showed that the fractional anisotropy (FA) values were significantly higher in the non-remitter group compared with those in the remitter group in the WM regions, such as the posterior corona radiata and superior longitudinal fasciculus, at the 6 month evaluation. The logistic regression analysis with clinical symptom severity and FA values of the WM regions as covariates showed that FA values in those regions and the Beck Depression Inventory-II predicted poor remission. This study suggests that posterior corona radiata and superior longitudinal fasciculus are related to potential predictive factors of 6-month remission in patients with PD. WM regions associated with the long-term remission should be verified with further investigations.

Aberrant Resting-State Cerebellar-Cerebral Functional Connectivity in Unmedicated Patients With Obsessive-Compulsive Disorder

Background: Although abnormality of cerebellar-cerebral functional connectivity at rest in obsessive-compulsive disorder (OCD) has been hypothesized, only a few studies have investigated the neural mechanism. To verify the findings of previous studies, a large sample of patients with OCD was studied because OCD shows possible heterogeneity. Methods: Forty-seven medication-free patients with OCD and 62 healthy controls (HCs) underwent resting-state functional magnetic imaging scans. Seed-based connectivity was examined to investigate differences in cerebellar-cerebral functional connectivity in OCD patients compared with HCs. Correlations between functional connectivity and the severity of obsessive-compulsive symptoms were analyzed. Results: In OCD, we found significantly increased functional connectivity between the right lobule VI and the left precuneus, which is a component of the default mode network (DMN), compared to HCs. However, there was no correlation between the connectivity of the right lobule VI-left precuneus and obsessive-compulsive severity. Conclusions: These findings suggest that altered functional connectivity between the cerebellum and DMN might cause changes in intrinsic large-scale brain networks related to the traits of OCD.

Investigating microstructure of white matter tracts as candidate endophenotypes of Social Anxiety Disorder - Findings from the Leiden Family Lab study on Social Anxiety Disorder (LFLSAD)

BACKGROUND

Social anxiety disorder (SAD) is a mental illness with a complex, partially genetic background. Differences in characteristics of white matter (WM) microstructure have been reported in patients with SAD compared to healthy controls. Also, WM characteristics are moderately to highly heritable. Endophenotypes are measurable characteristics on the road from genotype to phenotype, putatively reflective of genetically based disease mechanisms. In search of candidate endophenotypes of SAD we used a unique sample of SAD patients and their family members of two generations to explore microstructure of WM tracts as candidate endophenotypes. We focused on two endophenotype criteria: co-segregation with social anxiety within the families, and heritability.

METHODS

Participants (n = 94 from 8 families genetically vulnerable for SAD) took part in the Leiden Family Lab Study on Social Anxiety Disorder (LFLSAD). We employed tract-based spatial statistics to examine structural WM characteristics, being fractional anisotropy (FA), axial diffusivity (AD), mean diffusivity (MD) and radial diffusivity (RD), in three a-priori defined tracts of interest: uncinate fasciculus (UF), superior longitudinal fasciculus (SLF) and inferior longitudinal fasciculus (ILF). Associations with social anxiety symptoms and heritability were estimated.

RESULTS

Increased FA in the left and right SLF co-segregated with symptoms of social anxiety. These findings were coupled with decreased RD and MD. All characteristics of WM microstructure were estimated to be at least moderately heritable.

CONCLUSION

These findings suggest that alterations in WM microstructure in the SLF could be candidate endophenotypes of SAD, as they co-segregated within families genetically vulnerable for SAD and are heritable. These findings further elucidate the genetic susceptibility to SAD and improve our understanding of the overall etiology.

Dysregulated brain salience within a triple network model in high trait anxiety individuals: A pilot EEG functional connectivity study

Although previous studies have reported the association between large-scale brain networks alterations and pathological anxiety, abnormalities in the dynamic interaction among the triple network model in anxiety disorders and, especially, in trait anxiety is still poorly explored. Thus, the main aim of the current study was to investigate triple network functional dynamics in subjects with high trait anxiety during resting state (RS) through electroencephalography (EEG) connectivity. Twenty-three individuals with high-trait-anxiety (HTA) and forty-five participants with low-trait-anxiety (LTA) were enrolled. EEG analyses were conducted by means of the exact Low-Resolution Electromagnetic Tomography software (eLORETA). Compared to LTA participants, HTA subjects showed a decrease of alpha connectivity within the salience network (SN), between the dorsal anterior cingulate cortex (dACC) and both left and right anterior insula (AI). Furthermore, SN functional connectivity strength was negatively correlated with higher trait anxiety, even when controlling for potential confounding variables (e.g., depressive and obsessive-compulsive symptoms). Taken together, our results point out a specific functional connectivity pattern in HTA individuals, which consists in a dysfunctional communication within the SN, specifically in the AI-dACC pathway. This functional pattern could underline, at rest, saliency detection and brain correlates of altereted emotion regulation and cognitive control processes typically involved in anxiety.

Imaging the socially-anxious brain: recent advances and future prospects

Social anxiety disorder (SAD) is serious psychiatric condition with a genetic background. Insight into the neurobiological alterations underlying the disorder is essential to develop effective interventions that could relieve SAD-related suffering. In this expert review, we consider recent neuroimaging work on SAD. First, we focus on new results from magnetic resonance imaging studies dedicated to outlining biomarkers of SAD, including encouraging findings with respect to structural and functional brain alterations associated with the disorder. Furthermore, we highlight innovative studies in the field of neuroprediction and studies that established the effects of treatment on brain characteristics. Next, we describe novel work aimed to delineate endophenotypes of SAD, providing insight into the genetic susceptibility to develop the disorder. Finally, we outline outstanding questions and point out directions for future research.

A Machine Learning Approach to the Differentiation of Functional Magnetic Resonance Imaging Data of Chronic Fatigue Syndrome (CFS) From a Sedentary Control

Chronic Fatigue Syndrome (CFS) is a debilitating condition estimated to impact at least 1 million individuals in the United States, however there persists controversy about its existence. Machine learning algorithms have become a powerful methodology for evaluating multi-regional areas of fMRI activation that can classify disease phenotype from sedentary control. Uncovering objective biomarkers such as an fMRI pattern is important for lending credibility to diagnosis of CFS. fMRI scans were evaluated for 69 patients (38 CFS and 31 Control) taken before (Day 1) and after (Day 2) a submaximal exercise test while undergoing the n-back memory paradigm. A predictive model was created by grouping fMRI voxels into the Automated Anatomical Labeling (AAL) atlas, splitting the data into a training and testing dataset, and feeding these inputs into a logistic regression to evaluate differences between CFS and control. Model results were cross-validated 10 times to ensure accuracy. Model results were able to differentiate CFS from sedentary controls at a 80% accuracy on Day 1 and 76% accuracy on Day 2 (Table 3). Recursive features selection identified 29 ROI's that significantly distinguished CFS from control on Day 1 and 28 ROI's on Day 2 with 10 regions of overlap shared with Day 1 (Figure 3). These 10 shared regions included the putamen, inferior frontal gyrus, orbital (F3O), supramarginal gyrus (SMG), temporal pole; superior temporal gyrus (T1P) and caudate ROIs. This study was able to uncover a pattern of activated neurological regions that differentiated CFS from Control. This pattern provides a first step toward developing fMRI as a diagnostic biomarker and suggests this methodology could be emulated for other disorders. We concluded that a logistic regression model performed on fMRI data significantly differentiated CFS from Control.

Anxiety Disorders and the Brain's Resting State Networks: From Altered Spatiotemporal Synchronization to Psychopathological Symptoms

Anxiety disorders include a variety of different disorders including panic disorder (PD), social anxiety disorder (SAD), generalized anxiety disorder (GAD), and phobias. We here focus our review on GAD, SAD, and PD and put a specific emphasis on resting state networks and the coupling between the brain and the heart as all anxiety disorders exhibit abnormal perception of their own heartbeat in some way or the other. Resting state functional connectivity (rsFC) studies demonstrate abnormalities in default-mode network (DMN) in all anxiety disorders, e.g., mostly decreases in rsFC of DMN. In contrast, resting state fMRI shows increased rsFC in salience network (SN) (SAD, GAD) and/or somato-motor/sensory network (SMN) (PD). Since rsFC is coherence- or phase-based operating in the infraslow frequency domain (0.01-0.1 Hz), these data suggest spatiotemporal hypo- or hyper-synchronization in DMN and SMN/SN, respectively. These abnormalities in the neural network's spatiotemporal synchronization may, in turn, impact phase-based temporal synchronization of neural and cardiac activities resulting in decreased (DMN) or increased (SMN/SN) neuro-cardiac coupling in anxiety disorders. That, in turn, may be related to the various psychopathological symptoms like unstable sense of self (as based on unstable DMN showing spatiotemporal hypo-synchronization), increased emotions and specifically anxiety (as related to increased SN showing spatiotemporal hyper-synchronization), and increased bodily awareness (mediated by increased SMN with spatiotemporal hyper-synchronization) in anxiety disorders. Taken together, we here suggest altered spatiotemporal synchronization of neural and cardiac activity within the brain's resting state to underlie various psychopathological symptoms in anxiety disorders. Such spatiotemporal basis of psychopathological symptoms is well compatible with the recently suggested "Spatiotemporal Psychopathology."

Diagnostic Utility of Sodium Lactate Infusion and CO2-35% Inhalation for Panic Disorder

Laboratory measures have played an integral role in diagnosing pathology; however, compared to traditional medicine, psychiatric medicine has lagged behind in using such measures. A growing body of literature has begun to examine the viability and development of different laboratory measures in order to diagnose psychopathologies. The present review examines the current state of development of both sodium lactate infusion and CO2-35% inhalation as potential ancillary measures to diagnose panic disorder (PD). A previously established 3-step approach to identifying laboratory-based diagnostic tests was applied to available literature assessing the ability of both sodium lactate infusion or CO2-35% inhalation to induce panic attacks in PD patients, healthy controls, and individuals with other psychiatric conditions. Results suggest that across the literature reviewed, individuals with PD were more likely to exhibit panic attacks following administration of sodium lactate or CO2-35% compared to control participants. The majority of the studies examined only compared individuals with PD to healthy controls, suggesting that these ancillary measures are underdeveloped. In order to further determine the utility of these ancillary measures, research is needed to determine if panic attacks following administration of these chemical agents are unique to PD, or if individuals with related pathologies also respond, which may be indicative of transdiagnostic characteristics found across disorders.

Sex differences in brain correlates of STEM anxiety

Anxiety is known to dysregulate the salience, default mode, and central executive networks of the human brain, yet this phenomenon has not been fully explored across the STEM learning experience, where anxiety can impact negatively academic performance. Here, we evaluated anxiety and large-scale brain connectivity in 101 undergraduate physics students. We found sex differences in STEM-related and clinical anxiety, with longitudinal increases in science anxiety observed for both female and male students. Sex-specific relationships between STEM anxiety and brain connectivity emerged, with male students exhibiting distinct inter-network connectivity for STEM and clinical anxiety, and female students demonstrating no significant within-sex correlations. Anxiety was negatively correlated with academic performance in sex-specific ways at both pre- and post-instruction. Moreover, math anxiety in male students mediated the relation between default mode-salience connectivity and course grade. Together, these results reveal complex sex differences in the neural mechanisms driving how anxiety is related to STEM learning.

Toddler Temperament Mediates the Effect of Prenatal Maternal Stress on Childhood Anxiety Symptomatology: The QF2011 Queensland Flood Study

It is not known whether alterations to temperamental characteristics associated with prenatal maternal stress (PNMS) exposure account for the development of childhood anxiety symptomatology (internalizing behaviors and anxiety symptoms). The QF2011 Queensland flood study examined whether (1) toddler temperamental characteristics explained the association between PNMS exposure and childhood anxiety symptomatology; and (2) whether effects were dependent upon child sex or the timing of gestational exposure to PNMS. We investigated the effects of various aspects of flood-related stress in pregnancy (objective hardship, cognitive appraisal, subjective distress) on maternal report of 16-month toddler temperament (attentional control, shy-inhibition, negative reactivity), 4-year maternal-reported childhood anxiety symptomatology (internalizing and anxiety symptoms; N = 104), and teacher reports of internalizing behaviors (N = 77). Severity of maternal objective hardship during pregnancy and shy-inhibited behaviors were uniquely associated with 4-year child anxiety symptoms. Mediation analyses found that higher levels of 16-month negative reactivity accounted, in part, for the relationship between increased maternal objective flood-related hardship and greater internalizing behaviors (maternal but not teacher report). Neither child sex nor gestational timing of exposure moderated the hypothesized mediations. Our findings highlight several pathways through which varying aspects of disaster-related PNMS may influence early childhood anxiety symptomatology.

Blood CRP levels are elevated in children and adolescents with functional neurological symptom disorder

There is accumulating evidence that patients with functional neurological symptom disorder (FND) show activation of multiple components of the stress system-the hypothalamic-pituitary-adrenal axis, autonomic nervous system, and brain regions involved in arousal- and emotion-processing. This study aims to examine whether the immune-inflammatory component of the stress system is also activated. C-reactive protein (CRP) blood titre levels were measured in 79 children and adolescents with FND. CRP values ≥ 2 mg/L suggest low-grade inflammation. CRP values > 10 mg/L suggest a disease process. Sixty-six percent of subjects (n = 52) had CRP titres ≥ 2 mg/L. The upward shift in the distribution of CRP levels suggested low-grade inflammation (median CRP concentration was 4.60 mg/L, with 75th and 90th percentiles of 6.1 and 10.3 mg/L, respectively). Elevated CRP titres were not explained by sex, pubertal status, BMI, or medical factors. Confounder analyses suggested that history of maltreatment (χ² = 2.802, df = 1, p = 0.094, φ = 0.190; β = 2.823, p = 0.04) and a diagnosis of anxiety (χ² = 2.731, df = 1, p = 0.098, φ = 0.187; β = 4.520, p = 0.061) contributed to elevated CRP levels. Future research will need to identify the origins and locations of immune cell activation and the pathways and systems contributing to their activation and modulation. Because functional activity in neurons and glial cells-the brain's innate effector immune cells-is tightly coupled, our finding of elevated CRP titres suggests activation of the immune-inflammatory component of the brain's stress system. A more direct examination of inflammation-related molecules in the brain will help clarify the role of immune-inflammatory processes in FND.

Default mode network alterations in individuals with high-trait-anxiety: An EEG functional connectivity study

BACKGROUND

Although several researches investigated Default Mode Network (DMN) alterations in individuals with anxiety disorders, up to now no studies have investigated DMN functional connectivity in non-clinical individuals with high-trait-anxiety using quantitative electroencephalography (EEG). Here, the main aim was to extend previous findings investigating the association between trait anxiety and DMN EEG functional connectivity.

METHODS

Twenty-three individuals with high-trait-anxiety and twenty-four controls were enrolled. EEG was recorded during 5 min of resting state (RS). EEG analyses were conducted by means of the exact Low-Resolution Electromagnetic Tomography software (eLORETA).

RESULTS

Compared to controls, individuals with high-trait-anxiety showed a decrease of theta connectivity between right medial prefrontal cortex (mPFC) and right posterior cingulate/retrosplenial cortex. A decrease of beta connectivity was also observed between right mPFC and right anterior cingulate cortex. Furthermore, DMN functional connectivity strength was negatively related with STAI-T total score (i.e., lower connectivity was associated with higher trait anxiety), even when controlling for potential confounding variables (i.e., sex, age, and general psychopathology).

LIMITATIONS

Small sample size makes it difficult to draw definitive conclusions. Furthermore, we did not assess state variation of anxiety, which make our interpretation specific to trait anxiety.

CONCLUSIONS

Taken together, our results suggest that high-trait-anxiety individuals fail to synchronize DMN during RS, reflecting a possible top-down cognitive control deficit. These results may help in the understanding of the individual differences in functional brain networks associated with trait anxiety, a crucial aim in the prevention and in the early etiology understanding of clinical anxiety and related sequelae.

Phasic amygdala and BNST activation during the anticipation of temporally unpredictable social observation in social anxiety disorder patients

Anticipation of potentially threatening social situations is a key process in social anxiety disorder (SAD). In other anxiety disorders, recent research of neural correlates of anticipation of temporally unpredictable threat suggests a temporally dissociable involvement of amygdala and bed nucleus of the stria terminalis (BNST) with phasic amygdala responses and sustained BNST activation. However, the temporal profile of amygdala and BNST responses during temporal unpredictability of threat has not been investigated in patients suffering from SAD. We used functional magnetic resonance imaging (fMRI) to investigate neural activation in the central nucleus of the amygdala (CeA) and the BNST during anticipation of temporally unpredictable aversive (video camera observation) relative to neutral (no camera observation) events in SAD patients compared to healthy controls (HC). For the analysis of fMRI data, we applied two regressors (phasic/sustained) within the same model to detect temporally dissociable brain responses. The aversive condition induced increased anxiety in patients compared to HC. SAD patients compared to HC showed increased phasic activation in the CeA and the BNST for anticipation of aversive relative to neutral events. SAD patients as well as HC showed sustained activity alterations in the BNST for aversive relative to neutral anticipation. No differential activity during sustained threat anticipation in SAD patients compared to HC was found. Taken together, our study reveals both CeA and BNST involvement during threat anticipation in SAD patients. The present results point towards potentially SAD-specific threat processing marked by elevated phasic but not sustained CeA and BNST responses when compared to HC.

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fMRI in SAD during anticipation of temporally unpredictable aversive events.

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Anticipation of social observation induces increased anxiety in SAD patients.

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SAD patients show elevated phasic activity in fundamental anxiety network regions.

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Evidence of SAD-specific threat processing.

Reduced Resting State Neural Activity in the Right Orbital Part of Middle Frontal Gyrus in Anxious Depression

BACKGROUND

Anxious depression (AD), which is generally recognized as a common clinical subtype of major depressive disorder (MDD), holds distinctive features compared with unanxious depression (UAD). However, the neural mechanism of AD still remains unrevealed. To give insight to it, we compared resting-state functional magnetic resonance amplitude of low-frequency fluctuation (ALFF) and functional connectivity (FC) between AD and UAD patients.

METHOD

The data were collected from 60 AD patients, 38 UAD patients, and 60 matched healthy controls. The ALFF and seed-based FC were examined. Pearson correlations were computed between ALFF/FC and clinical measures.

RESULTS

In Comparison with the UAD group, the ALFF value of the right orbital part of middle frontal gyrus (RO-MFG) decreased in AD group. Specifically, the ALFF values of the RO-MFG were negatively correlated with retardation factor scores in AD group (r = -0.376, p = 0.003).

CONCLUSIONS

AD patients exhibited disturbed intrinsic brain function compared with UAD patients. The decreased activity of the RO-MFG is indicative of the alterations involved in the neural basis of AD.

Widely Impaired White Matter Integrity and Altered Structural Brain Networks in Psychogenic Non-Epileptic Seizures

OBJECTIVE

The underlying neural correlates of psychogenic non-epileptic seizures (PNES) are still unknown and their identification would be helpful for clinicians and patients. This study aimed to reveal details of white matter microstructure and alterations in brain structural networks in patients with PNES by using diffusion tensor imaging (DTI) and graph theoretical connectivity analysis.

METHODS

Seventeen patients with PNES and 26 age- and sex-matched healthy controls were enrolled. All participants underwent DTI on a 3.0-T MRI scanner, and fractional anisotropy (FA) and mean diffusivity (MD) maps were compared by tract-based spatial statistics. Additionally, the structural networks derived from DTI data were analyzed using graph theory and two different parcellation schemes.

RESULTS

Patients with PNES showed widespread decreases in FA and increases in MD, particularly in the deep white matter. In addition, graph theoretical analysis revealed impaired brain networks in PNES, including increased path length, decreased network efficiency, altered nodal topology, and reduced regional connectivity in the right posterior areas.

CONCLUSION

We found widely impaired white matter integrity and impaired brain structural networks in Japanese patients with PNES. These findings contribute to the accumulation of evidence on PNES and may improve understanding of this condition.

Prenatal maternal anxiety and children's brain structure and function: A systematic review of neuroimaging studies

BACKGROUND

Maternal anxiety disorders are common during pregnancy and postpartum, and are associated with increased behaviour problems and risk of mental health difficulties in children. Understanding alterations in brain structure and function associated with maternal anxiety may help elucidate potential mechanisms via which high maternal anxiety could affect children.

METHODS

We conducted a systematic review of extant research studying the associations between prenatal anxiety and children's brain structure and function, as assessed through neuroimaging. Data were gathered in accordance with the PRISMA review guidelines.

RESULTS

Ten articles were identified, and all found a significant association between antenatal maternal anxiety and child neurodevelopment. Studies vary considerably in their methods with five studies employing electroencephalography (EEG), one using magnetoencephalography (MEG), and the rest employing magnetic resonance imaging (MRI).

LIMITATIONS

The heterogeneity of neuroimaging techniques undertaken by the reviewed studies precluded a meta-analysis from being performed. The applicability of this systematic review to clinical practice is also limited given that the studies examined children across a wide age range (neonates to 17 years).

CONCLUSIONS

From early infancy to late adolescence, findings suggest alterations of brain structure and function in frontal, temporal, and limbic areas in children born to mothers who experienced prenatal anxiety. These brain abnormalities may underlie associations between prenatal anxiety and children's behaviour, though more research incorporating neuroimaging and behavioural data is necessary to determine this.

Cerebral resting state markers of biased perception in social anxiety

Social anxiety (SA) comprises a multitude of persistent fears around the central element of dreaded negative evaluation and exclusion. This very common anxiety is spectrally distributed among the general population and associated with social perception biases deemed causal in its maintenance. Here, we investigated cerebral resting state markers linking SA and biased social perception. To this end, resting state functional connectivity (RSFC) was assessed as the neurobiological marker in a study population with greatly varying SA using fMRI in the first step of the experiment. One month later the impact of unattended laughter-exemplifying social threat-on a face rating task was evaluated as a measure of biased social perception. Applying a dimensional approach, SA-related cognitive biases tied to the valence, dominance and arousal of the threat signal and their underlying RSFC patterns among central nodes of the cerebral emotion, voice and face processing networks were identified. In particular, the connectivity patterns between the amygdalae and the right temporal voice area met all criteria for a cerebral mediation of the association between SA and the laughter valence-related interpretation bias. Thus, beyond this identification of non-state-dependent cerebral markers of biased perception in SA, this study highlights both a starting point and targets for future research on the causal relationships between cerebral connectivity patterns, SA and biased perception, potentially via neurofeedback methods.