Directed threat imagery in generalized anxiety disorder

Basic processes and clinical applications of mental imagery in worry: A systematic review

BACKGROUND

In this systematic review, we aimed to synthesise existing research on the phenomenology of mental imagery among high worriers compared to healthy individuals, and to characterise the nature and effectiveness of existing imagery-related interventions in treatment of worry.

METHODS

PsycInfo, CENTRAL, EMBASE, Medline, Medline Epub, and PubMed were searched for studies examining the relationship between worry/GAD and mental imagery, or interventions using imagery in treatment of worry/GAD. We assessed study quality and used qualitative narrative synthesis to comprehensively map study results.

RESULTS

The search yielded 2589 abstracts that were assessed for eligibility independently by two authors. From this, 183 full texts were screened and 50 qualitatively synthesised. Twenty-seven reported an association between worry/GAD and an aspect of mental imagery. Here, overactive negative and worry imagery, and diminished positive future imagining, were associated with worry/GAD. Twenty-three studies reported an intervention. This literature suggested mixed findings regarding efficacy, including for imaginal exposure as an independent technique for GAD.

CONCLUSIONS

Findings support dysfunctional negative imagining and diminished positive prospective imagery in GAD. General imagining abilities remain intact, which is promising for efforts to utilise imagery in treatment. Further research is warranted to develop innovative clinical applications of imagery in treatment of GAD.

An investigation into the abnormal dynamic connection mechanism of generalized anxiety disorders based on non-homogeneous Markov models

BACKGROUND

The dynamic and hierarchical nature of the functional brain network. The neural dynamical systems tend to converge to multiple attractors (stable fixed points or dynamical states) in long run. Little is known about how the changes in this brain dynamic "long-term" behavior of the connectivity flow of brain network in generalized anxiety disorder (GAD).

METHODS

This study recruited 92 patients with GAD and 77 healthy controls (HC). We applied a reachable probability approach combining a Non-homogeneous Markov model with transition probability to quantify all possible connectivity flows and the hierarchical structure of brain functional systems at the dynamic level and the stationary probability vector (10-step transition probabilities) to describe the steady state of the system in the long run. A random forest algorithm was conducted to predict the severity of anxiety.

RESULTS

The dynamic functional patterns in distributed brain networks had larger possibility to converge in bilateral thalamus, posterior cingulate cortex (PCC), right superior occipital gyrus (SOG) and smaller possibility to converge in bilateral superior temporal gyrus (STG) and right parahippocampal gyrus (PHG) in patients with GAD compared to HC. The abnormal transition probability pattern could predict anxiety severity in patients with GAD.

LIMITATIONS

Small samples and subjects taking medications may have influenced our results. Future studies are expected to rule out the potential confounding effects.

CONCLUSION

Our results have revealed abnormal dynamic neural communication and integration in emotion regulation in patients with GAD, which give new insights to understand the dynamics of brain function of patients with GAD.

Reduced vmPFC-insula functional connectivity in generalized anxiety disorder: a Bayesian confirmation study

Differences in the correlated activity of networked brain regions have been reported in individuals with generalized anxiety disorder (GAD) but an overreliance on null-hypothesis significance testing (NHST) limits the identification of disorder-relevant relationships. In this preregistered study, we applied both a Bayesian statistical framework and NHST to the analysis of resting-state fMRI scans from females with GAD and matched healthy comparison females. Eleven a-priori hypotheses about functional connectivity (FC) were evaluated using Bayesian (multilevel model) and frequentist (t-test) inference. Reduced FC between the ventromedial prefrontal cortex (vmPFC) and the posterior-mid insula (PMI) was confirmed by both statistical approaches and was associated with anxiety sensitivity. FC between the vmPFC-anterior insula, the amygdala-PMI, and the amygdala-dorsolateral prefrontal cortex (dlPFC) region pairs did not survive multiple comparison correction using the frequentist approach. However, the Bayesian model provided evidence for these region pairs having decreased FC in the GAD group. Leveraging Bayesian modeling, we demonstrate decreased FC of the vmPFC, insula, amygdala, and dlPFC in females with GAD. Exploiting the Bayesian framework revealed FC abnormalities between region pairs excluded by the frequentist analysis and other previously undescribed regions in GAD, demonstrating the value of applying this approach to resting-state FC data in clinical investigations.

Difference analysis of multidimensional electroencephalogram characteristics between young and old patients with generalized anxiety disorder

Growing evidences indicate that age plays an important role in the development of mental disorders, but few studies focus on the neuro mechanisms of generalized anxiety disorder (GAD) in different age groups. Therefore, this study attempts to reveal the neurodynamics of Young_GAD (patients with GAD under the age of 50) and Old_GAD (patients with GAD over 50 years old) through statistical analysis of multidimensional electroencephalogram (EEG) features and machine learning models. In this study, 10-min resting-state EEG data were collected from 45 Old_GAD and 33 Young_GAD. And multidimensional EEG features were extracted, including absolute power (AP), fuzzy entropy (FE), and phase-lag-index (PLI), on which comparison and analyses were performed later. The results showed that Old_GAD exhibited higher power spectral density (PSD) value and FE value in beta rhythm compared to theta, alpha1, and alpha2 rhythms, and functional connectivity (FC) also demonstrated significant reorganization of brain function in beta rhythm. In addition, the accuracy of machine learning classification between Old_GAD and Young_GAD was 99.67%, further proving the feasibility of classifying GAD patients by age. The above findings provide an objective basis in the field of EEG for the age-specific diagnosis and treatment of GAD.

Prefrontal cortical circuits in anxiety and fear: an overview

Pathological anxiety is among the most difficult neuropsychiatric diseases to treat pharmacologically, and it represents a major societal problem. Studies have implicated structural changes within the prefrontal cortex (PFC) and functional changes in the communication of the PFC with distal brain structures in anxiety disorders. Treatments that affect the activity of the PFC, including cognitive therapies and transcranial magnetic stimulation, reverse anxiety- and fear-associated circuit abnormalities through mechanisms that remain largely unclear. While the subjective experience of a rodent cannot be precisely determined, rodent models hold great promise in dissecting well-conserved circuits. Newly developed genetic and viral tools and optogenetic and chemogenetic techniques have revealed the intricacies of neural circuits underlying anxiety and fear by allowing direct examination of hypotheses drawn from existing psychological concepts. This review focuses on studies that have used these circuit-based approaches to gain a more detailed, more comprehensive, and more integrated view on how the PFC governs anxiety and fear and orchestrates adaptive defensive behaviors to hopefully provide a roadmap for the future development of therapies for pathological anxiety.

Generalized anxiety disorder symptoms and type 2 diabetes onset: Findings from the Prospective Cooperative Health Research in the Region of Augsburg F4 and FF4 studies

OBJECTIVE

To investigate the association of generalized anxiety disorder (GAD) symptomology on the incidence of type 2 diabetes.

RESEARCH DESIGN & METHODS

Participants from the prospective KORA F4/FF4 German cohort were followed for a mean of 6.5 years. Generalized Anxiety Disorder Scale-7 (GAD-7) was used to assess GAD symptoms and incident type 2 diabetes cases were confirmed using a standard oral glucose tolerance test. Multivariate logistic regression models were used to estimate the effect of GAD symptoms on the incidence of type 2 diabetes.

RESULTS

The present study included 1694 participants (51.8% women, 48.2% men) with a mean age of 51.2 years, among whom 113 (6.7%) had high GAD symptoms. During the follow-up period (11,102 person/years), 113 (6.5%) type 2 diabetes cases were confirmed. Participants with GAD symptoms had 2-fold higher incidence of type 2 diabetes than participants without GAD (17.7 vs. 8.7 cases/1000 person-years). Correspondingly, GAD symptoms independently increased the risk of type 2 diabetes by an odds ratio of 2.09 [95%CI 1.02-4.32, p = 0.04] after adjustment for concurrent sociodemographic, lifestyle and cardiometabolic risk factors, high sensitivity C-reactive protein, depression, and the use of antidepressant medications. Additionally, GAD symptoms had an even larger impact on the onset of type 2 diabetes incidence following additional adjustment for prediabetes at baseline (2.68 [1.23-5.88], p=0.01).

CONCLUSIONS

Participants with GAD symptoms had 2-times higher odds of type 2 diabetes incidence during 6.5 years of follow-up, highlighting the significant role of dysregulated stress mechanisms in the pathway to developing type 2 diabetes.

Altered Task-Evoked Corticolimbic Responsivity in Generalized Anxiety Disorder

Generalized anxiety disorder (GAD) is marked by uncontrollable, persistent worry and exaggerated response to uncertainty. Here, we review and summarize the findings from the GAD literature that employs functional neuroimaging methods. In particular, the present review focuses on task-based blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) studies. We find that select brain regions often regarded as a part of a corticolimbic circuit (e.g., amygdala, anterior cingulate cortex, prefrontal cortex) are consistently targeted for a priori hypothesis-driven analyses, which, in turn, shows varying degrees of abnormal BOLD responsivity in GAD. Data-driven whole-brain analyses show the insula and the hippocampus, among other regions, to be affected by GAD, depending on the task used in each individual study. Overall, while the heterogeneity of the tasks and sample size limits the generalizability of the findings thus far, some promising convergence can be observed in the form of the altered BOLD responsivity of the corticolimbic circuitry in GAD.

The effects of verbal and imaginal worry on panic symptoms during an interoceptive exposure task

Previous research has documented the inhibitory effects of worry on cardiovascular reactivity to subsequently presented fear-relevant stimuli. Although theoretical assertions point to the verbal-linguistic (as opposed to imagery-based) nature of worry as the cause of these inhibitory effects, extant research investigating the effects of worrisome thinking on subsequent anxiety-eliciting tasks has not isolated the verbal-linguistic nature of worry as the active ingredient in its suppressive effects on arousal. Furthermore, prior research has not examined the potential effects of worry on maintenance of panic symptoms. In this study, participants high in anxiety sensitivity were asked to engage in verbal worry, imaginal worry, or relaxation prior to each of three repeated presentations of an interoceptive exposure task. Relaxation was associated with lower initial subjective fear that remained low across repeated exposures, and related stable sympathetic arousal (and decreased heart rate) over time. Imagery-based worry was associated with moderate initial subjective fear that was sustained across repeated exposures, and sympathetic arousal (and heart rate) that was likewise stable over time. However, verbal worry was associated with high initial subjective fear that was sustained over time, but sympathetic arousal (and heart rate) that decreased across repeated exposures. Thus, verbal worry was uniquely associated with a lack of synchronous response systems and maintenance of anxious meaning over time. Theoretical and clinical implications are discussed.

Neuroinflammation-Associated Alterations of the Brain as Potential Neural Biomarkers in Anxiety Disorders

Stress-induced changes in the immune system, which lead to neuroinflammation and consequent brain alterations, have been suggested as possible neurobiological substrates of anxiety disorders, with previous literature predominantly focusing on panic disorder, agoraphobia, and generalized anxiety disorder, among the anxiety disorders. Anxiety disorders have frequently been associated with chronic stress, with chronically stressful situations being reported to precipitate the onset of anxiety disorders. Also, chronic stress has been reported to lead to hypothalamic–pituitary–adrenal axis and autonomic nervous system disruption, which may in turn induce systemic proinflammatory conditions. Preliminary evidence suggests anxiety disorders are also associated with increased inflammation. Systemic inflammation can access the brain, and enhance pro-inflammatory cytokine levels that have been shown to precipitate direct and indirect neurotoxic effects. Prefrontal and limbic structures are widely reported to be influenced by neuroinflammatory conditions. In concordance with these findings, various imaging studies on panic disorder, agoraphobia, and generalized anxiety disorder have reported alterations in structure, function, and connectivity of prefrontal and limbic structures. Further research is needed on the use of inflammatory markers and brain imaging in the early diagnosis of anxiety disorders, along with the possible efficacy of anti-inflammatory interventions on the prevention and treatment of anxiety disorders.

Emotion reactivity-related brain network analysis in generalized anxiety disorder: a task fMRI study

BACKGROUND

Generalized anxiety disorder (GAD) is closely associated with emotional dysregulation. Patients with GAD tend to overreact to emotional stimuli and are impaired in emotional regulation. Using emotional regulation task, studies have found hypo-activation in prefrontal cortex (PFC) of GAD patients and concluded with inadequate top-down control. However, results remain inconsistent concerning PFC and limbic area's reactivity to emotional stimuli. What's more, only a few studies aim to identify how limbic area interacts with PFC in GAD patients. The current study aims to identify the difference in PFC-limbic circuitry response to emotional stimuli between GAD patients and healthy controls (HCs) from the perspective of brain network. Through brain network analysis, it revealed the connectivity between limbic area and PFC, and moreover, the orientation of connectivity, all of which gave a better test of inadequate top-down control hypothesis.

METHODS

During fMRI scanning, participants were required to complete an emotional face identification task (fearful, neutral, happy facial expression). 30 participants (16 GAD patients, 14 HCs) were included in the formal analysis. A Bayesian-network based method was used to identify the brain network consisting of several pre-hypothesized regions of interest (ROIs) under each condition (negative, positive, neutral). In total, six graphs were obtained. Each of them represented the brain network that was common to the group under corresponding condition.

RESULTS

Results revealed that GAD patients showed more bottom-up connection but less top-down connection regardless of condition, relative to HCs. Also, the insula was more connected but the amygdala was less connected regardless of condition, relative to HCs. the results also revealed a very different brain network response between GAD patients and HCs even under neutral condition.

CONCLUSIONS

More bottom-up connection but less top-down connection may indicate that GAD patients are insufficient in top-down control, in keeping with inadequate top-down control hypothesis. The more connected insula may indicate GAD patients' abnormality in interoception processing. Relative to HCs, distinct brain network response pattern in GAD patients under neutral condition suggests GAD patients' abnormality in distinguishing safety from threat and intolerance of uncertainty.

A mechanistic model for individualised treatment of anxiety disorders based on predictive neural biomarkers

Increased amygdala responsiveness is the hallmark of fear and a characteristic across patients with anxiety disorders. The amygdala is embedded in a complex regulatory circuit. Multiple different mechanisms may elevate amygdala responsiveness and lead to the occurrence of an anxiety disorder. While top-down control by the prefrontal cortex (PFC) downregulates amygdala responses, the locus coeruleus (LC) drives up amygdala activation via noradrenergic projections. This indicates that the same fearful phenotype may result from different neural mechanisms. We propose a mechanistic model that defines three different neural biomarkers causing amygdala hyper-responsiveness in patients with anxiety disorders: (a) inherent amygdala hypersensitivity, (b) low prefrontal control and (c) high LC drive. First-line treatment for anxiety disorders is exposure-based cognitive behavioural therapy, which strengthens PFC recruitment during emotion regulation and thus targets low-prefrontal control. A treatment response rate around 50% (Loerinc et al., 2015, Clinical Psychological Reviews, 42, 72-82) might indicate heterogeneity of underlying neurobiological mechanisms among patients, presumably leading to high variation in treatment benefit. Transforming insights from cognitive neuroscience into applicable clinical heuristics to categorise patients based on their underlying biomarker may support individualised treatment selection in psychiatry. We review literature on the three anxiety-related mechanisms and present a mechanistic model that may serve as a rational for pathology-based diagnostic and biomarker-guided treatment selection in psychiatry.

Dynamic changes of amplitude of low-frequency fluctuations in patients with generalized anxiety disorder

Previous neuroimaging studies have mainly focused on alterations of static and dynamic functional connectivity in patients with generalized anxiety disorder (GAD). However, the characteristics of local brain activity over time in GAD are poorly understood. This study aimed to investigate the abnormal time‐varying local brain activity of GAD by using the amplitude of low‐frequency fluctuation (ALFF) method combined with sliding‐window approach. Group comparison results showed that compared with healthy controls (HCs), patients with GAD exhibited increased dynamic ALFF (dALFF) variability in widespread regions, including the bilateral dorsomedial prefrontal cortex, hippocampus, thalamus, striatum; and left orbital frontal gyrus, inferior parietal lobule, temporal pole, inferior temporal gyrus, and fusiform gyrus. The abnormal dALFF could be used to distinguish between patients with GAD and HCs. Increased dALFF variability values in the striatum were positively correlated with GAD symptom severity. These findings suggest that GAD patients are associated with abnormal temporal variability of local brain activity in regions implicated in executive, emotional, and social function. This study provides insight into the brain dysfunction of GAD from the perspective of dynamic local brain activity, highlighting the important role of dALFF variability in understanding neurophysiological mechanisms and potentially informing the diagnosis of GAD.

Structural and functional neuroimaging studies in generalized anxiety disorder: a systematic review

OBJECTIVES

Brain imaging studies carried out in patients suffering from generalized anxiety disorder (GAD) have contributed to better characterize the pathophysiological mechanisms underlying this disorder. The present study reviews the available functional and structural brain imaging evidence on GAD, and suggests further strategies for investigations in this field.

METHODS

A systematic literature review was performed in PubMed, PsycINFO, and Google Scholar, aiming to identify original research evaluating GAD patients with the use of structural and functional magnetic resonance imaging as well as diffusion tensor imaging.

RESULTS

The available studies have shown impairments in ventrolateral and dorsolateral prefrontal cortex, anterior cingulate, posterior parietal regions, and amygdala in both pediatric and adult GAD patients, mostly in the right hemisphere. However, the literature is often tentative, given that most studies have employed small samples and included patients with comorbidities or in current use of various medications. Finally, different methodological aspects, such as the type of imaging equipment used, also complicate the generalizability of the findings.

CONCLUSIONS

Longitudinal neuroimaging studies with larger samples of both juvenile and adult GAD patients, as well as at risk individuals and unaffected relatives, should be carried out in order to shed light on the specific biological signature of GAD.

Brain activation during disorder-related script-driven imagery in panic disorder: a pilot study

Despite considerable effort, the neural correlates of altered threat-related processing in panic disorder (PD) remain inconclusive. Mental imagery of disorder-specific situations proved to be a powerful tool to investigate dysfunctional threat processing in anxiety disorders. The current functional magnetic resonance imaging (fMRI) study aimed at investigating brain activation in PD patients during disorder-related script-driven imagery. Seventeen PD patients and seventeen healthy controls (HC) were exposed to newly developed disorder-related and neutral narrative scripts while brain activation was measured with fMRI. Participants were encouraged to imagine the narrative scripts as vividly as possible and they rated their script-induced emotional states after the scanning session. PD patients rated disorder-related scripts as more arousing, unpleasant and anxiety-inducing as compared to HC. Patients relative to HC showed elevated activity in the right amygdala and the brainstem as well as decreased activity in the rostral anterior cingulate cortex, and the medial and lateral prefrontal cortex to disorder-related vs. neutral scripts. The results suggest altered amygdala/ brainstem and prefrontal cortex engagement and point towards the recruitment of brain networks with opposed activation patterns in PD patients during script-driven imagery.

Aberrant Functional Network Connectivity as a Biomarker of Generalized Anxiety Disorder

Neural disruptions during emotion regulation are common of generalized anxiety disorder (GAD). Identifying distinct functional and effective connectivity patterns in GAD may provide biomarkers for their diagnoses. This study aims to investigate the differences of features of brain network connectivity between GAD patients and healthy controls (HC), and to assess whether those differences can serve as biomarkers to distinguish GAD from controls. Independent component analysis (ICA) with hierarchical partner matching (HPM-ICA) was conducted on resting-state functional magnetic resonance imaging data collected from 20 GAD patients with medicine-free and 20 matched HC, identifying nine highly reproducible and significantly different functional brain connectivity patterns across diagnostic groups. We then utilized Granger causality (GC) to study the effective connectivity between the regions that identified by HPM-ICA. The linear discriminant analysis was finally used to distinguish GAD from controls with these measures of neural connectivity. The GAD patients showed stronger functional connectivity in amygdala, insula, putamen, thalamus, and posterior cingulate cortex, but weaker in frontal and temporal cortex compared with controls. Besides, the effective connectivity in GAD was decreased from the cortex to amygdala and basal ganglia. Applying the ICA and GC features to the classifier led to a classification accuracy of 87.5%, with a sensitivity of 90.0% and a specificity of 85.0%. These findings suggest that the presence of emotion dysregulation circuits may contribute to the pathophysiology of GAD, and these aberrant brain features may serve as robust brain biomarkers for GAD.