Anxious brain networks: A coordinate-based activation likelihood estimation meta-analysis of resting-state functional connectivity studies in anxiety

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.

Connectome-Based Predictive Modeling of Individual Anxiety

Anxiety-related illnesses are highly prevalent in human society. Being able to identify neurobiological markers signaling high trait anxiety could aid the assessment of individuals with high risk for mental illness. Here, we applied connectome-based predictive modeling (CPM) to whole-brain resting-state functional connectivity (rsFC) data to predict the degree of trait anxiety in 76 healthy participants. Using a computational “lesion” approach in CPM, we then examined the weights of the identified main brain areas as well as their connectivity. Results showed that the CPM successfully predicted individual anxiety based on whole-brain rsFC, especially the rsFC between limbic areas and prefrontal cortex. The prediction power of the model significantly decreased from simulated lesions of limbic areas, lesions of the connectivity within limbic areas, and lesions of the connectivity between limbic areas and prefrontal cortex. Importantly, this neural model generalized to an independent large sample (n = 501). These findings highlight important roles of the limbic system and prefrontal cortex in anxiety prediction. Our work provides evidence for the usefulness of connectome-based modeling in predicting individual personality differences and indicates its potential for identifying personality factors at risk for psychopathology.

Resting State Functional Connectivity of Brain With Electroconvulsive Therapy in Depression: Meta-Analysis to Understand Its Mechanisms

Introduction: Electroconvulsive therapy (ECT) is a commonly used brain stimulation treatment for treatment-resistant or severe depression. This study was planned to find the effects of ECT on brain connectivity by conducting a systematic review and coordinate-based meta-analysis of the studies performing resting state fMRI (rsfMRI) in patients with depression receiving ECT. Methods: We systematically searched the databases published up to July 31, 2020, for studies in patients having depression that compared resting-state functional connectivity (rsFC) before and after a course of pulse wave ECT. Meta-analysis was performed using the activation likelihood estimation method after extracting details about coordinates, voxel size, and method for correction of multiple comparisons corresponding to the significant clusters and the respective rsFC analysis measure with its method of extraction. Results: Among 41 articles selected for full-text review, 31 articles were included in the systematic review. Among them, 13 articles were included in the meta-analysis, and a total of 73 foci of 21 experiments were examined using activation likelihood estimation in 10 sets. Using the cluster-level interference method, one voxel-wise analysis with the measure of amplitude of low frequency fluctuations and one seed-voxel analysis with the right hippocampus showed a significant reduction (p < 0.0001) in the left cingulate gyrus (dorsal anterior cingulate cortex) and a significant increase (p < 0.0001) in the right hippocampus with the right parahippocampal gyrus, respectively. Another analysis with the studies implementing network-wise (posterior default mode network: dorsomedial prefrontal cortex) resting state functional connectivity showed a significant increase (p < 0.001) in bilateral posterior cingulate cortex. There was considerable variability as well as a few key deficits in the preprocessing and analysis of the neuroimages and the reporting of results in the included studies. Due to lesser studies, we could not do further analysis to address the neuroimaging variability and subject-related differences. Conclusion: The brain regions noted in this meta-analysis are reasonably specific and distinguished, and they had significant changes in resting state functional connectivity after a course of ECT for depression. More studies with better neuroimaging standards should be conducted in the future to confirm these results in different subgroups of depression and with varied aspects of ECT.

Sex differences in brain metabolites in anxiety and mood disorders

Gender differences in mood and anxiety disorders are well-established. However, the neural basis of these differences is not clear yet, especially in terms of brain metabolism. Indeed, although several proton Magnetic Resonance Spectroscopy (¹H MRS) investigations reported different metabolic levels in both depression and anxiety disorders, which have been also linked to symptoms severity and response to treatment, the role of gender on these differences have not been explored yet. Therefore, this study aims at investigating the role of sex in neurometabolic alterations associated with both mood and anxiety disorders. A 3T single-voxel ¹H MRS acquisition of the dorsolateral prefrontal cortex was acquired from 14 Major Depressive Disorder, 10 Generalized Anxiety Disorder (GAD), 11 Panic Disorder (PD), patients and 16 healthy controls (HC). Among males, PD patients showed significantly lower GPC+PC (also observed in GAD+PD) and Glu levels compared to HC. Finally, a significant group x sex interaction effect was observed in the GPC+PC and Glu levels. We proved the presence of an association between sex and brain metabolites in anxiety spectrum.

Intrinsic organization of cortical networks predicts state anxiety: an functional near-infrared spectroscopy (fNIRS) study

Although state anxiety has been characterized by hyper-responsive subcortical activity and its bottom-up connectivity with cortical regions, the role of cortical networks in state anxiety is not yet well understood. To this end, we decoded individual state anxiety by using a machine-learning approach based on resting-state functional connectivity (RSFC) with functional near-infrared spectroscopy (fNIRS). Our results showed that the RSFC among a set of cortical networks were highly predictive of state anxiety, rather than trait anxiety. Specifically, these networks included connectivity between cortical areas in the default mode network (DMN) and dorsal attention network (DAN), and connectivity within the DMN, which were negatively correlated with state anxiety; connectivity between cortical areas in the DMN and frontoparietal network (FPN), FPN and salience network (SN), FPN and DAN, DMN and SN, which were positively correlated with state anxiety. These findings suggest a predictive role of intrinsic cortical organization in the assessment of state anxiety. The work provides new insights into potential neural mechanisms of emotion states and implications for prognosis, diagnosis, and treatment of affective disorders.

Movie viewing elicits rich and reliable brain state dynamics

Adaptive brain function requires that sensory impressions of the social and natural milieu are dynamically incorporated into intrinsic brain activity. While dynamic switches between brain states have been well characterised in resting state acquisitions, the remodelling of these state transitions by engagement in naturalistic stimuli remains poorly understood. Here, we show that the temporal dynamics of brain states, as measured in fMRI, are reshaped from predominantly bistable transitions between two relatively indistinct states at rest, toward a sequence of well-defined functional states during movie viewing whose transitions are temporally aligned to specific features of the movie. The expression of these brain states covaries with different physiological states and reflects subjectively rated engagement in the movie. In sum, a data-driven decoding of brain states reveals the distinct reshaping of functional network expression and reliable state transitions that accompany the switch from resting state to perceptual immersion in an ecologically valid sensory experience.

Towards a model of uncertainty distress in the context of Coronavirus (COVID-19)

The paper forms part of a series of papers outlining the theoretical framework for a new model of uncertainty distress (this paper), treatment implications arising from the model, and empirical tests of the model. We define uncertainty distress as the subjective negative emotions experienced in response to the as yet unknown aspects of a given situation. In the first paper we draw on a robust body of research on distinct areas including: threat models of anxiety, perceived illness uncertainty and intolerance of uncertainty. We explore how threat and uncertainty are separable in anxiety and how we can understand behaviours in response to uncertainty. Finally, we propose a clinically, theoretically and empirically informed model for uncertainty distress, and outline how this model can be tested. Caveats, clinical applications and practitioner key points are briefly included, although these are more fully outlined in the treatment implications article. While we outline this model in the context of novel coronavirus (COVID-19), the model has broader applications to both mental and physical health care settings.

KEY LEARNING AIMS

(1)To define the concept of uncertainty distress.(2)To understand the role of threat, over-estimation of threat, perceived uncertainty, actual uncertainty, and intolerance of uncertainty in distress maintenance.(3)To understand how people may behave in response to uncertainty distress.(4)To describe a model of uncertainty distress.

Functional connectivity of the anterior insula associated with intolerance of uncertainty in youth

Intolerance of uncertainty (IU) is a trait characteristic marked by distress in the face of insufficient information. Elevated IU has been implicated in the development and maintenance of anxiety disorders, particularly during adolescence, which is characterized by dramatic neural maturation and the onset of anxiety disorders. Previous task-based work implicates the bilateral anterior insula in IU. However, the association between anterior insula intrinsic functional connectivity (iFC) and IU has not been examined in adolescents. Fifty-eight healthy youth (mean age = 12.56; 55% boys) completed the Intolerance of Uncertainty Scale for Children (IUSC-12) and a 6-minute resting state fMRI scan. Group-level analyses were conducted using a random-effects, ordinary least-squares model, including IUSC-12 scores (Total, Inhibitory subscale, Prospective subscale), and three nuisance covariates (age, sex, and mean framewise displacement). IUSC-12 Inhibitory subscale scores were predictive of iFC between the left and right anterior insula and right prefrontal regions. IUSC-12 Prospective subscale scores significantly predicted iFC between the anterior insula and the anterior cingulate cortex. IUSC-12 total scores did not predict significant iFC of the bilateral anterior insula. Follow-up analyses, including anxiety (MASC Total Score) in the models, failed to find significant results. This could suggest that the associations found between IUSC-12 scores and anterior insula iFC are not unique to IU and, rather, reflect a broader anxiety-related connectivity pattern. Further studies with larger samples are needed to tease apart unique associations. These findings bear significance in contributing to the literature evaluating the neural correlates of risk factors for anxiety in youth.

Transdiagnostic and disease-specific abnormalities in the default-mode network hubs in psychiatric disorders: A meta-analysis of resting-state functional imaging studies

Background.

The default mode network (DMN) dysfunction has emerged as a consistent biological correlate of multiple psychiatric disorders. Specifically, there is evidence of alterations in DMN cohesiveness in schizophrenia, mood and anxiety disorders. The aim of this study was to synthesize at a fine spatial resolution the intra-network functional connectivity of the DMN in adults diagnosed with schizophrenia, mood and anxiety disorders, capitalizing on powerful meta-analytic tools provided by activation likelihood estimation.

Methods.

Results from 70 whole-brain resting-state functional magnetic resonance imaging articles published during the last 15 years were included comprising observations from 2,789 patients and 3,002 healthy controls.

Results.

Specific regional changes in DMN cohesiveness located in the anteromedial and posteromedial cortex emerged as shared and trans-diagnostic brain phenotypes. Disease-specific dysconnectivity was also identified. Unmedicated patients showed more DMN functional alterations, highlighting the importance of interventions targeting the functional integration of the DMN.

Conclusion.

This study highlights functional alteration in the major hubs of the DMN, suggesting common abnormalities in self-referential mental activity across psychiatric disorders.

Amygdala-prefrontal connectivity modulates loss aversion bias in anxious individuals

Anxious individuals tend to make pessimistic judgments in decision making under uncertainty. While this phenomenon is commonly attributed to risk aversion, loss aversion is a critical but often overlooked factor. In this study, we simultaneously examined risk aversion and loss aversion during decision making in high and low trait anxious individuals in a variable gain/loss gambling task during functional magnetic resonance imaging. Although high relative to low anxious individuals showed significant increased risk aversive behavior reflected by decreased overall gamble decisions, there was no group difference in subjective aversion to risk. Instead, loss aversion rather than risk aversion dominantly contributed to predict behavioral decisions, which was associated with attenuated functional connectivity between the amygdala-based emotional system and the prefrontal control regions. Our findings suggest a dominant role of loss aversion in maladaptive risk assessment of anxious individuals, underpinned by disorganization of emotion-related and cognitive-control-related brain networks.

Indian classical music with incremental variation in tempo and octave promotes better anxiety reduction and controlled mind wandering-A randomised controlled EEG study

Studies have reported the benefits of music-listening in stress-reduction using musical pieces of specific scale or 'Raaga'. But the influence of lower-level musical properties (like tempo, octave, timbre, etc.) lack research backing. Carnatic music concerts use incremental modulations in tempo and octave (e.g.: 'Ragam-Tanam-Pallavi') to elevate the mood of audiences. Therefore, the current study aimed to examine the anxiolytic effect of this musical property. A randomised controlled cross-over study with 21 male undergraduate medical students was followed. 11 participants listened to 'Varying music' (VM: instrumental music with incremental variations in tempo and octave) and 10 listened to 'Stable music' (SM: instrumental music without such variations), thrice daily for 6 days, both clips recorded in Raaga-Kaapi and silence being the control intervention. Electroencephalography (EEG) and Electrocardiography (for heart rate variability or HRV) were done on all 6 days. Beck's Anxiety inventory and State-trait anxiety scale were administered on Day-1 and Day-6. A significant anxiety score reduction was seen only in VM. VM showed marked decrease in lower frequency EEG power in bilateral temporo-parieto-occipital regions compared to silence, whereas SM showed increase in higher frequencies. Relatively, VM showed more midline power reduction (i.e., lower default mode network or DMN activity) and SM showed greater left-dominant alpha/beta asymmetry (i.e., greater right brain activation). During both music interventions HRV remained stable, unlike silence intervention. We speculate that, gradual transition between lower-slower and higher-faster music portions of VM induces a 'controlled-mind wandering' state involving balanced switching between heightened mind wandering ('attention to self') and reduced mind wandering ('attention to music') states, respectively. Therefore, music-selection has remarkable influence on stress-management and warrants further research.

The Self and its World: A Neuro-Ecological and Temporo-Spatial Account of Existential Fear

The current international crisis situation caused by the COVID-19 pandemic is having a strong psychological impact on our subjectivities. We are constantly threatened by the danger of i) being infected, ii) infecting other people, and (iii) by the loss of social relation. Departing from these premises, we here aim to investigate the psychological and neurodynamics of this complex phenomenon. First, we discuss about recent psychological and neuronal findings on fear and its disorders, related to an unbalanced intero-exteroceptive processing and emotional regulation. Secondly we move to the psychological and neuronal dynamics of self and others characterized by a temporo-spatial alignment with the world. Due to the neural overlap of emotion and self and the deep-reaching neuro-ecological layers of self, emotional feelings like fear and anxiety cannot be detached and dissociated from the world; they signify the world–brain relation, and, more specifically, our self-other relation. The deepest neuro-ecological and neuro-social layers of self are threatened by the loss of subjectivity, which is manifest in our loss of body and thus the fear of dying, and the loss of intersubjectivity that surfaces in our fear of infecting others, which reflect the intimate anchorage of the self with the world. In our opinion the pandemic of COVID-19 deeply affect our sense of self and its spatio-temporal neuronal dynamics providing the prerequisites for the manifestation of fear and existential anxiety, thus disrupting the brain-world relation with significant repercussions on our psyche and on our daily lives.

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.

Combining fMRI during resting state and an attention bias task in children

Neuroimaging studies typically focus on either resting state or task-based fMRI data. Prior research has shown that similarity in functional connectivity between rest and cognitive tasks, interpreted as reconfiguration efficiency, is related to task performance and IQ. Here, we extend this approach from adults to children, and from cognitive tasks to a threat-based attention task. The goal of the current study was to examine whether similarity in functional connectivity during rest and an attention bias task relates to threat bias, IQ, anxiety symptoms, and social reticence. fMRI was measured during resting state and during the dot-probe task in 41 children (M = 13.44, SD = 0.70). Functional connectivity during rest and dot-probe was positively correlated, suggesting that functional hierarchies in the brain are stable. Similarity in functional connectivity between rest and the dot-probe task only related to threat bias (puncorr < .03). This effect did not survive correction for multiple testing. Overall, children who allocate more attention towards threat also may possess greater reconfiguration efficiency in switching from intrinsic to threat-related attention states. Finally, functional connectivity correlated negatively across the two conditions of the dot-probe task. Opposing patterns of modulation of functional connectivity by threat-congruent and threat-incongruent trials may reflect task-specific network changes during two different attentional processes.

Meditation effect in changing functional integrations across large-scale brain networks: Preliminary evidence from a meta-analysis of seed-based functional connectivity

Meditation is a type of mental training commonly applied in clinical settings and also practiced for general well-being. Brain functional connectivity (FC) patterns associated with meditation have revealed its brain mechanisms. However, the variety of FC methods applied has made it difficult to identify brain communication patterns associated with meditation. Here we carried out a coordinate-based meta-analysis to get preliminary evidence of meditation effects on changing brain network interactions. Fourteen seed-based, voxel-wise FC studies reported in 13 publications were reviewed; 10 studies with seeds in the default mode network (DMN) were meta-analyzed. Seed coordinates and the effect sizes in statistically significant regions were extracted, based on 170 subjects in meditation groups and 163 subjects in control groups. Seed-based d-mapping was used to analyze meditation versus control FC differences with DMN seeds. Meditation was associated with increased connectivity within DMN and between DMN and somatomotor network and with decreased connectivity between DMN and frontoparietal network (FPN) as well as ventral attention network (VAN). The pattern of decreased within-DMN FC and increased between-network FC (FPN and DAN with DMN) was more robust in highly experienced meditators compared to less experienced individuals. The identified neural network interactions may also promote meditation’s effectiveness in clinical interventions for treating physical and mental disorders.

Nodal Global Efficiency in Front-Parietal Lobe Mediated Periventricular White Matter Hyperintensity (PWMH)-Related Cognitive Impairment

White matter hyperintensity (WMH) is widely observed in the elderly population and serves as a key indicator of cognitive impairment (CI). However, the underlying mechanism remains to be elucidated. Herein, we investigated the topological patterns of resting state functional networks in WMH subjects and the relationship between the topological measures and CI. A graph theory-based analysis was employed in the resting-state functional magnetic resonance scans of 112 subjects (38 WMH subjects with cognitive impairment without dementia (CIND), 36 WMH subjects with normal cognition and 38 healthy controls (HCs), and we found that WMH-CIND subjects displayed decreased global efficiency at the levels of the whole brain, specific subnetworks [fronto-parietal network (FPN) and cingulo-opercular network (CON)] and certain nodes located in the FPN and CON, as well as decreased local efficiency in subnetworks. Our results demonstrated that nodal global efficiency in frontal and parietal regions mediated the impairment of information processing speed related to periventricular WMH (PWMH). Additionally, we performed support vector machine (SVM) analysis and found that altered functional efficiency can identify WMH-CIND subjects with high accuracy, sensitivity and specificity. These findings suggest impaired functional networks in WMH-CIND individuals and that decreased functional efficiency may be a feature of CI in WMH subjects.

Novel pharmacological targets in drug development for the treatment of anxiety and anxiety-related disorders

Current medication for anxiety disorders is suboptimal in terms of efficiency and tolerability, highlighting the need for improved drug treatments. In this review an overview of drugs being studied in different phases of clinical trials for their potential in the treatment of fear-, anxiety- and trauma-related disorders is presented. One strategy followed in drug development is refining and improving compounds interacting with existing anxiolytic drug targets, such as serotonergic and prototypical GABAergic benzodiazepines. A more innovative approach involves the search for compounds with novel mechanisms of anxiolytic action using the growing knowledge base concerning the relevant neurocircuitries and neurobiological mechanisms underlying pathological fear and anxiety. The target systems evaluated in clinical trials include glutamate, endocannabinoid and neuropeptide systems, as well as ion channels and targets derived from phytochemicals. Examples of promising novel candidates currently in clinical development for generalised anxiety disorder, social anxiety disorder, panic disorder, obsessive compulsive disorder or post-traumatic stress disorder include ketamine, riluzole, xenon with one common pharmacological action of modulation of glutamatergic neurotransmission, as well as the neurosteroid aloradine. Finally, compounds such as D-cycloserine, MDMA, L-DOPA and cannabinoids have shown efficacy in enhancing fear-extinction learning in humans. They are thus investigated in clinical trials as an augmentative strategy for speeding up and enhancing the long-term effectiveness of exposure-based psychotherapy, which could render chronic anxiolytic drug treatment dispensable for many patients. These efforts are indicative of a rekindled interest and renewed optimism in the anxiety drug discovery field, after decades of relative stagnation.

Odorants: a tool to provide nonpharmacological intervention to reduce anxiety during normal and pathological aging

Anxiety disorders represent 1 of the most common classes of psychiatric disorders. In the aging population and for patients with age-related pathology, the percentage of people suffering of anxiety is significantly elevated. Furthermore, anxiety carries with it an increased risk for a variety of age-related medical conditions, including cardiovascular disease, stroke, cognitive decline, and increased severity of motor symptoms in Parkinson's disease. A variety of anxiolytic compounds are available but often carry with them disturbing side effects that impact quality of life. Among nonmedicinal approaches to reducing anxiety, odor diffusion and aromatherapy are the most popular. In this review, we highlight the emerging perspective that the use of odorants may reduce anxiety symptoms or at least potentiate the effect of other anxiolytic approaches and may serve as an alternative form of therapy to deal with anxiety symptoms. Such approaches may be particularly beneficial in aging populations with elevated risk for these disorders. We also discuss potential neural mechanisms underlying the anxiolytic effects of odorants based on work in animal models.