Task MRI-Based Functional Brain Network of Anxiety

Influence of panic disorder and paroxetine on brain functional hubs in drug-free patients

BACKGROUND

The effects of panic disorder (PD) and pharmacotherapy on brain functional hubs in drug-free patients, and the utility of their degree centrality (DC) in diagnosing and predicting treatment response (TR) for PD, remained unclear.

AIMS

This study aimed to assess the effects of PD and paroxetine on brain functional hubs in drug-free patients and to identify neuroimaging biomarkers for diagnosing and predicting TR in patients with PD.

METHODS

Imaging data from 54 medication-free PD patients and 54 matched healthy controls (HCs) underwent DC and functional connectivity (FC) analyses before and after a 4-week paroxetine treatment. Diagnosis and prediction of TR models for PD were constructed using support vector machine (SVM) and support vector regression (SVR), with DC as features.

RESULTS

Patients with PD showed aberrant DC and FC in the anterior cingulum, temporal, and occipital areas compared with HCs at baseline. After treatment, DC of the patients increased in the calcarine cortex, lingual gyrus, and cerebellum IV/V, along with improved clinical symptoms. Utilizing voxel-wise DC values at baseline, the SVM effectively distinguished patients with PD from HCs with an accuracy of 83.33%. In SVR, the predicted TR significantly correlated with the observed TR (correlation coefficient (r) = 0.893, Mean Squared Error = 0.009).

CONCLUSION

Patients with PD exhibited abnormal DC and FC, notably in the limbic network, temporal, and occipital regions. Paroxetine ameliorated patients' symptoms while altering their brain FC. SVM and SVR models, utilizing baseline DC, effectively distinguished the patients from HCs and accurately predicted TR.

Immediate and long-term efficacy of transcranial direct current stimulation (tCDS) in obsessive-compulsive disorder, posttraumatic stress disorder and anxiety disorders: a systematic review and meta-analysis

Currently, there is still debate over the effectiveness of transcranial direct current stimulation (tDCS) in treating obsessive-compulsive disorder (OCD), posttraumatic stress disorder (PTSD) and anxiety disorders (ADs). To investigate the immediate and long-term effectiveness of tDCS in these diseases, we conducted a systematic review and quantitative analysis of existing literature on the treatment of OCD, PTSD, and ADs with tDCS. Following the PRISMA guidelines, we searched seven electronic databases and systematically retrieved articles published from May 2012 to June 2024 that compared the effects of active tDCS with sham stimulation in the treatment of these disorders. We included primary outcome measures such as the change scores in disorder-specific and general anxiety symptoms before and after treatment, as well as secondary outcomes such as changes in disorder-specific and general anxiety symptoms at follow-up. We also assessed the impact of tDCS on depressive symptoms. Fifteen papers met the eligibility criteria. Overall, the results of meta-analysis indicated that tDCS had a high effect in improving specific symptoms (SMD = -0.73, 95% CI: -1.09 to -0.37) and general anxiety symptoms (SMD = -0.75; 95% CI: -1.23 to -0.26) in OCD, PTSD and ADs, with effects lasting up to 1 month and showing a moderate effect size. Furthermore, tDCS demonstrated immediate and significant alleviation of depressive symptoms in these diseases. This study concludes that tDCS can serve as a non-invasive brain stimulation technology for treating these disorders, and the therapeutic effects can be maintained for a period of time.

Algorithm-Based Modular Psychotherapy Alleviates Brain Inflammation in Generalized Anxiety Disorder

Generalized anxiety disorder (GAD) is marked by prolonged and excessive worry, physical signs of anxiety, and associated neuroinflammation. Traditional treatments, like pharmacotherapy and cognitive-behavioral therapy (CBT), often leave residual symptoms and have high relapse rates. This study aimed to explore the efficacy of algorithm-based modular psychotherapy (MoBa), a combination of CBT and mindfulness meditation as validated by the research domain criteria (RDoC), in reducing anxiety and neuroinflammation in GAD. A longitudinal design was used, with 50 patients with GAD undergoing a 12-week MoBa treatment. The patients were investigated pre- and post-treatment using MRI to measure neuroinflammatory markers (DBSI-RF, diffusion-basis spectral imaging-based restricted fraction) in the hippocampus, amygdala, and neocortex. Clinical symptoms were assessed using the Hamilton Anxiety Rating Scale (HAM-A) and the Generalized Anxiety Disorder 7-item scale (GAD-7). Results indicated significant reductions in both anxiety symptoms and MRI RF values in the amygdala, suggesting decreased neuroinflammation. A reduction in anxiety was associated with the amelioration of neuroinflammation in the amygdala. These results suggest that MoBa is effective in alleviating both the psychological and neuroinflammatory aspects of GAD, offering a promising personalized treatment approach. Future research should focus on long-term effects and the mechanisms through which MoBa impacts neuroinflammation and anxiety.

A widespread electrical brain network encodes anxiety in health and depressive states

In rodents, anxiety is charactered by heightened vigilance during low-threat and uncertain situations. Though activity in the frontal cortex and limbic system are fundamental to supporting this internal state, the underlying network architecture that integrates activity across brain regions to encode anxiety across animals and paradigms remains unclear. Here, we utilize parallel electrical recordings in freely behaving mice, translational paradigms known to induce anxiety, and machine learning to discover a multi-region network that encodes the anxious brain-state. The network is composed of circuits widely implicated in anxiety behavior, it generalizes across many behavioral contexts that induce anxiety, and it fails to encode multiple behavioral contexts that do not. Strikingly, the activity of this network is also principally altered in two mouse models of depression. Thus, we establish a network-level process whereby the brain encodes anxiety in health and disease.

Altered single-subject gray matter structural networks in social anxiety disorder

Previous fMRI studies have reported more random brain functional graph configurations in social anxiety disorder (SAD). However, it is still unclear whether the same configurations would occur in gray matter (GM) graphs. Structural MRI was performed on 49 patients with SAD and on 51 age- and gender-matched healthy controls (HC). Single-subject GM networks were obtained based on the areal similarities of GM, and network topological properties were analyzed using graph theory. Group differences in each topological metric were compared, and the structure-function coupling was examined. These network measures were further correlated with the clinical characteristics in the SAD group. Compared with controls, the SAD patients demonstrated globally decreased clustering coefficient and characteristic path length. Altered topological properties were found in the fronto-limbic and sensory processing systems. Altered metrics were associated with the illness duration of SAD. Compared with the HC group, the SAD group exhibited significantly decreased structural-functional decoupling. Furthermore, structural-functional decoupling was negatively correlated with the symptom severity in SAD. These findings highlight less-optimized topological configuration of the brain structural networks in SAD, which may provide insights into the neural mechanisms underlying the excessive fear and avoidance of social interactions in SAD.

Behavioral and brain functional characteristics of children with Attention-Deficit/Hyperactivity disorder and anxiety trait

The current study aimed to explore the behavioral, daily-life executive functional, and brain functional connectivity patterns in children with attention-deficit/hyperactivity disorder (ADHD) and anxiety. A total of 246 children with non-comorbid ADHD and 91 healthy controls (HCs) participated in the current study, among whom 175 subjects went through resting-state functional magnetic resonance imaging (fMRI) scans. The ADHD participants were divided into two subgroups: ADHD with a high level of anxiety (ADHD + ANX) and ADHD with a low level of anxiety (ADHD-ANX). The Child Behavior Checklist (CBCL) and the Behavior Rating Inventory of Executive Function (BRIEF) were used to capture the behavioral and daily-life executive functional characteristics. Independent component analysis with dual regression models was applied to the fMRI data. All statistical models were estimated with age and sex as covariates. Compared with the ADHD-ANX group, the ADHD + ANX group showed more withdrawn, somatic, social, thought, attention, delinquent, and aggressive problems (all corrected p < 0.05). The ADHD + ANX group also displayed more impaired emotional control and working memory than the ADHD-ANX (all corrected p < 0.05). The ADHD-ANX group, but not the ADHD + ANX group, showed elevated functional connectivity within the default mode network compared with the HC group. The mean function connectivity within the default mode network significantly mediated the correlation between anxiety level and attention problems. In sum, anxiety in children with ADHD was associated with more social, emotional, and behavioral problems, more impaired daily-life executive function, and altered brain function. Our work provides important information on the heterogeneity of ADHD.

Alteration of resting-state functional connectivity network properties in patients with social anxiety disorder after virtual reality-based self-training

Social anxiety disorder (SAD) is a mental disorder characterized by excessive anxiety in social situations. This study aimed to examine the alteration of resting-state functional connectivity in SAD patients related to the virtual reality-based self-training (VRS) which enables exposure to social situations in a controlled environment. Fifty-two SAD patients were randomly assigned to the experimental group who received the VRS, or the control group who did not. Self-report questionnaires and resting-state functional magnetic resonance imaging (fMRI) were performed to assess clinical symptoms and analyze the resting-state network properties, respectively. Significant decrease in social anxiety and an increase in self-esteem was found in the experimental group. From the resting-state fMRI analysis, alteration of local network properties in the left dorsolateral prefrontal gyrus (-10.0%, p = 0.025), left inferior frontal gyrus (-32.3%, p = 0.044), left insula (-17.2%, p = 0.046), left Heschl's gyrus (-21.2%, p = 0.011), bilateral inferior temporal gyrus (right: +122.6%, p = 0.045; left:-46.7%, p = 0.015), and right calcarine sulcus (+17.0%, p = 0.010) were found in the experimental group. Average shortest path length (+8.3%, p = 0.008) and network efficiency (-7.6%, p = 0.011) are found to be altered from the global network property analysis. In addition, the experimental group displayed more positive and more negative changes in the correlation trend of average shortest path length (p = 0.004) and global network efficiency (p = 0.014) with the severity of social anxiety, respectively. These results suggest potential effectiveness of the VRS, which is possibly related to the change of aberrant processing and control of visual and auditory linguistic stimuli and the adaptive change in rumination pattern.

Repetitive Transcranial Magnetic Stimulation Modulates Frontal and Temporal Time-Varying EEG Network in Generalized Anxiety Disorder: A Pilot Study

Generalized Anxiety Disorder (GAD) is a highly prevalent yet poorly understood chronic mental disorder. Previous studies have associated GAD with excessive activation of the right dorsolateral prefrontal cortex (DLPFC). This study aimed to investigate the effect of low-frequency repetitive transcranial magnetic stimulation (repetitive TMS, rTMS) targeting the right DLPFC on clinical symptoms and TMS-evoked time-varying brain network connectivity in patients with GAD. Eleven patients with GAD received 1 Hz rTMS treatment targeting the right DLPFC for 10 days. The severity of the clinical symptoms was evaluated using the Hamilton Anxiety Scale (HAMA) and the Hamilton Depression Scale (HAMD) at baseline, right after treatment, and at the one-month follow-up. Co-registration of single-pulse TMS (targeting the right DLPFC) and electroencephalography (TMS-EEG) was performed pre- and post-treatment in these patients and 11 healthy controls. Time-varying brain network connectivity was analyzed using the adaptive directed transfer function. The scores of HAMA and HAMD significantly decreased after low-frequency rTMS treatment, and these improvements in ratings remained at the one-month follow-up. Analyses of the time-varying EEG network in the healthy controls showed a continuous weakened connection information outflow in the left frontal and mid-temporal regions. Compared with the healthy controls, the patients with GAD showed weakened connection information outflow in the left frontal pole and the posterior temporal pole at baseline. After 10-day rTMS treatment, the network patterns showed weakened connection information outflow in the left frontal and temporal regions. The time-varying EEG network changes induced by TMS perturbation targeting right DLPFC in patients with GAD were characterized by insufficient information outflow in the left frontal and temporal regions. Low-frequency rTMS targeting the right DLPFC reversed these abnormalities and improved the clinical symptoms of GAD.

Molecular and neurocircuitry mechanisms of social avoidance

Humans and animals live in social relationships shaped by actions of approach and avoidance. Both are crucial for normal physical and mental development, survival, and well-being. Active withdrawal from social interaction is often induced by the perception of threat or unpleasant social experience and relies on adaptive mechanisms within neuronal networks associated with social behavior. In case of confrontation with overly strong or persistent stressors and/or dispositions of the affected individual, maladaptive processes in the neuronal circuitries and its associated transmitters and modulators lead to pathological social avoidance. This review focuses on active, fear-driven social avoidance, affected circuits within the mesocorticolimbic system and associated regions and a selection of molecular modulators that promise translational potential. A comprehensive review of human research in this field is followed by a reflection on animal studies that offer a broader and often more detailed range of analytical methodologies. Finally, we take a critical look at challenges that could be addressed in future translational research on fear-driven social avoidance.