Neuroplastic changes in anterior cingulate cortex gray matter volume and functional connectivity following attention bias modification in high trait anxious individuals

Mental imagery abilities in different modalities moderate the efficacy of cognitive bias modification for interpretation bias in social anxiety

OBJECTIVES

Cognitive bias modification for interpretation bias (CBM-I) is an effective low-intensity intervention that targets interpretation biases associated with the development and maintenance of social anxiety. Few studies to-date have examined the extent to which individual mental imagery ability affects the efficacy of CBM-I.

METHODS

A total of 666 individuals were screened. Seventy-two participants with high levels of social anxiety and elevated baseline interpretation bias were randomly assigned to either CBM-I (n = 36) or control groups (n = 36). They completed 5-day internet-delivered training in modifying their interpretation bias associated with ambiguous social scenarios (CBM-I) or reading neutral text passages (control).

RESULTS

Intent-to-treat analyses revealed that participants in the CBM-I group had a significant reduction in their interpretation bias compared to the controls. They had a reduction of 11 %-18 % on the social anxiety measures. Participants' mental imagery ability was significantly associated with the reduction of interpretation bias and social anxiety symptoms in the CBM-I group. Specifically, participants with higher mental imagery ability in emotional feelings benefited the most from the intervention.

CONCLUSIONS

CBM-I is an efficacious intervention for modulating social anxiety-related biases and symptoms. Mental imagery ability facilitated the efficacy of CBM-I.

Anxiety disorder identification with biomarker detection through subspace-enhanced hypergraph neural network

In this study, we propose a subspace-enhanced hypergraph neural network (seHGNN) for classifying anxiety disorders (AD), which are prevalent mental illnesses that affect a significant portion of the global population. Our seHGNN model utilizes a learnable incidence matrix to strengthen the influence of hyperedges in graphs and enhance the feature extraction performance of hypergraph neural networks (HGNNs). Then, we integrate multimodal data on the brain limbic system into a hypergraph within an existing binary hypothesis testing framework. Experimental results demonstrate that our seHGNN achieves a remarkable accuracy of 84.46% for AD classification. By employing an ensemble learning strategy, we can further improve its performance, achieving a high accuracy of 94.1%. Our method outperforms other deep-learning-based methods, particularly GNN-based methods. Furthermore, our seHGNN successfully identifies discriminative AD biomarkers that align with existing reports, providing strong evidence supporting the effectiveness and interpretability of our proposed method.

Structural brain changes in the anterior cingulate cortex of major depressive disorder individuals with suicidal ideation: Evidence from the REST-meta-MDD project

BACKGROUND

Suicidal ideation (SI) is very common in patients with major depressive disorder (MDD). However, its neural mechanisms remain unclear. The anterior cingulate cortex (ACC) region may be associated with SI in MDD patients. This study aimed to elucidate the neural mechanisms of SI in MDD patients by analyzing changes in gray matter volume (GMV) in brain structures in the ACC region, which has not been adequately studied to date.

METHODS

According to the REST-meta-MDD project, this study subjects consisted of 235 healthy controls and 246 MDD patients, including 123 MDD patients with and 123 without SI, and their structural magnetic resonance imaging data were analyzed. The 17-item Hamilton Depression Rating Scale (HAMD) was used to assess depressive symptoms. Correlation analysis and logistic regression analysis were used to determine whether there was a correlation between GMV of ACC and SI in MDD patients.

RESULTS

MDD patients with SI had higher HAMD scores and greater GMV in bilateral ACC compared to MDD patients without SI (all p < 0.001). GMV of bilateral ACC was positively correlated with SI in MDD patients and entered the regression equation in the subsequent logistic regression analysis.

CONCLUSIONS

Our findings suggest that GMV of ACC may be associated with SI in patients with MDD and is a sensitive biomarker of SI.

Enriched rehabilitation on brain functional connectivity in patients with post-stroke cognitive impairment

Objective

This study aims to observe the effect of enrichment rehabilitation (ER) on cognitive function in post-stroke patients and to clarify its underlying mechanism.

Methods

Forty patients with post-stroke cognitive impairment (PSCI) meeting the inclusion criteria were randomly assigned to two groups: conventional medical rehabilitation (CM group) and ER intervention (ER group). All patients underwent assessments of overall cognitive function, attention function, and executive function within 24 h before the start of training and within 24 h after the 8 weeks of training. We investigated the altered resting-state functional connectivity (RSFC) with the right dorsolateral prefrontal cortex (DLPFC) in patients with PSCI following ER training through functional magnetic resonance imaging (fMRI). Additionally, twenty people undergoing routine physical examinations in the outpatient department of our hospital were selected as the healthy control (HC) group.

Results

Before training, both groups of PSCI patients exhibited significant impairment in overall cognitive function, attention function, and executive function compared to the HC group. However, there was no significant difference between the two PSCI patient groups. Following 8 weeks of treatment, both PSCI patient groups demonstrated substantial improvement in overall cognitive function, attention function, and executive function. Moreover, the ER group exhibited greater improvement after training compared to the CM group. Despite the improvements, the cognitive behavioral performance assessment scores of both PSCI patient groups remained lower than those of the HC group. RSFC analysis in the ER group revealed strengthened positive functional connectivity between the right DLPFC and the left superior frontal gyrus (SFG) and left anterior cingulate gyrus (ACG), along with decreased functional connectivity between the right DLPFC and the right superior temporal gyrus (STG) and right precentral gyrus post-ER intervention.

Conclusion

ER intervention is more effective than conventional medical rehabilitation in improving the cognitive function of PSCI patients, potentially by augmenting the FC between the right DLPFC and dominant cognitive brain regions, such as the left SFG and left ACG while attenuating the FC between the right DLPFC and non-dominant hemisphere areas including the STG and precentral gyrus within the right hemisphere.

Neural activation changes following attention bias modification treatment or a selective serotonin reuptake inhibitor for social anxiety disorder

BACKGROUND

Delineation of changes in neural function associated with novel and established treatments for social anxiety disorder (SAD) can advance treatment development. We examined such changes following selective serotonin reuptake inhibitor (SSRI) and attention bias modification (ABM) variant - gaze-contingent music reward therapy (GC-MRT), a first-line and an emerging treatments for SAD.

METHODS

Eighty-one patients with SAD were allocated to 12-week treatments of either SSRI or GC-MRT, or waitlist (ns = 22, 29, and 30, respectively). Baseline and post-treatment functional magnetic resonance imaging (fMRI) data were collected during a social-threat processing task, in which attention was directed toward and away from threat/neutral faces.

RESULTS

Patients who received GC-MRT or SSRI showed greater clinical improvement relative to patients in waitlist. Compared to waitlist patients, treated patients showed greater activation increase in the right inferior frontal gyrus and anterior cingulate cortex when instructed to attend toward social threats and away from neutral stimuli. An additional anterior cingulate cortex cluster differentiated between the two active groups. Activation in this region increased in ABM and decreased in SSRI. In the ABM group, symptom change was positively correlated with neural activation change in the dorsolateral prefrontal cortex.

CONCLUSIONS

Brain function measures show both shared and treatment-specific changes following ABM and SSRI treatments for SAD, highlighting the multiple pathways through which the two treatments might work. Treatment-specific neural responses suggest that patients with SAD who do not fully benefit from SSRI or ABM may potentially benefit from the alternative treatment, or from a combination of the two.

TRIAL REGISTRATION

ClinicalTrials.gov, Identifier: NCT03346239. https://clinicaltrials.gov/ct2/show/NCT03346239.

Climate change on the brain: Neural correlates of climate anxiety

Climate change is a global crisis impacting individuals' mental health. Climate anxiety is an emerging area of interest within popular culture and the scientific community. Yet, little is known about the mechanisms underlying climate anxiety. We provide evidence that climate anxiety is related to gray matter volume in the midcingulate cortex as well as its level of functional connectivity with the insula cortex. These neuroanatomical and neurofunctional features of climate anxiety are involved in identifying and anticipating potential threats within the environment and preparing an appropriate action response to such threats. These neural correlates align with those observed in anxiety disorders. Yet, climate anxiety itself as well as the neural correlates of climate anxiety were related to pro-environmental behavior. This may suggest that the midcingulate and insula are part of a network linked to an adaptive aspect of climate anxiety in motivating behavioral engagement.

Biases in affective attention tasks in posttraumatic stress disorder patients: A systematic review of neuroimaging studies

INTRODUCTION

Posttraumatic stress disorder (PTSD) is characterized by alterations in emotional and cognitive processing. The current neurobiological model of PTSD posits that amygdala and prefrontal cortex functioning impairment underpins symptoms, such as altered emotional and cognitive processing. Additionally, these structures are key components of emotional and attention regulation.

AIM

This review sought to evaluate studies comparing PTSD group to non-PTSD controls performance in affective attention tasks during neuroimaging.

RESULTS

PTSD group behavioral performance when responding to affective stimuli differed from controls only in stroop-based tasks. However, neuroimaging techniques were able to identify brain activation differences even when behavioral differences were not present. Amygdala hyperactivation in PTSD patients was confirmed in most cases, but cortical networks results were not as consistent. More than a general reduction in activity, PTSD group data points out to impaired recruitment of ventral cortical structures and increased reliance on dorsal cortical structures during task performance.

CONCLUSION

Stroop-based tasks seem to be better at identifying differences in behavioral performance of PTSD individuals. PTSD individuals seems to present an altered brain activation pattern in affective attention tasks when compared to controls, where PTSD individuals seem to present enhanced amygdala activation and rely more on dorsal anterior cingulate cortex and posterior insula activation during tasks. The PROSPERO ID for this study is CRD42022355471.

The gray matter morphology associated with the electrophysiological response to errors in individuals with high trait anxiety

Enhanced error monitoring has been associated with higher levels of anxiety. This has been consistently demonstrated in its most reliable electrophysiological index, the error-related negativity (ERN), such that increased ERN is related with elevated anxiety symptomology. However, it is still unclear whether the structural properties of the brain are associated with individual differences in ERN amplitude. Moreover, the relationship between ERN and anxiety has recently been suggested to be moderated by sex, but the degree to which sex moderates the association between brain structure and ERN amplitude is unknown. The present study investigated the association between gray matter volume (GMV) and ERN amplitude in individuals with high trait anxiety (N = 98) as well as the role of sex in moderating this association. The ERN was elicited from a flanker task, whereas structural MRI images were obtained from whole brain structural T1-weighted MRI scans. The results of voxel-based morphometry analyses showed that the relationship between ERN difference scores and GMV was moderated by sex in the dorsal anterior cingulate cortex (dACC). This sex difference was derived from a negative correlation between ERN difference scores and dACC GMV in females and a positive correlation in males. Our findings are in accordance with the critical role of the dACC serving as a neural substrate of error monitoring. It also provides further evidence for sex-specific associations with brain structures related to error monitoring.

Anxious Brains: A Combined Data Fusion Machine Learning Approach to Predict Trait Anxiety from Morphometric Features

Trait anxiety relates to the steady propensity to experience and report negative emotions and thoughts such as fear and worries across different situations, along with a stable perception of the environment as characterized by threatening stimuli. Previous studies have tried to investigate neuroanatomical features related to anxiety mostly using univariate analyses and thus giving rise to contrasting results. The aim of this study is to build a predictive model of individual differences in trait anxiety from brain morphometric features, by taking advantage of a combined data fusion machine learning approach to allow generalization to new cases. Additionally, we aimed to perform a network analysis to test the hypothesis that anxiety-related networks have a central role in modulating other networks not strictly associated with anxiety. Finally, we wanted to test the hypothesis that trait anxiety was associated with specific cognitive emotion regulation strategies, and whether anxiety may decrease with ageing. Structural brain images of 158 participants were first decomposed into independent covarying gray and white matter networks with a data fusion unsupervised machine learning approach (Parallel ICA). Then, supervised machine learning (decision tree) and backward regression were used to extract and test the generalizability of a predictive model of trait anxiety. Two covarying gray and white matter independent networks successfully predicted trait anxiety. The first network included mainly parietal and temporal regions such as the postcentral gyrus, the precuneus, and the middle and superior temporal gyrus, while the second network included frontal and parietal regions such as the superior and middle temporal gyrus, the anterior cingulate, and the precuneus. We also found that trait anxiety was positively associated with catastrophizing, rumination, other- and self-blame, and negatively associated with positive refocusing and reappraisal. Moreover, trait anxiety was negatively associated with age. This paper provides new insights regarding the prediction of individual differences in trait anxiety from brain and psychological features and can pave the way for future diagnostic predictive models of anxiety.

Eye-size effects in the dot-probe task: Greater sclera exposure predicts delayed disengagement from fearful faces

Fearful facial expressions are nonverbal and biologically salient signals of potential threat that automatically hold, capture, and direct observers' attention. They are characterized by enlarged eye whites and dilated pupils, and fearful eyes alone are sufficient to capture attention. The morphological properties of the eye region, such as sclera exposure, are thought to play an important role in nonverbal communication. Specifically, increased sclera exposure associated with fearful expressions has been shown to moderate how observers' shift their attention toward the direction of another's gaze. Yet, the extent to which variability in sclera exposure possibly impacts the capture and hold of attention by fearful faces is untested. To address this, a sample of 249 adults completed a dot-probe task of selective attention with fearful and neutral faces. The results suggested that (1) fearful faces were prioritized over neutral faces (i.e., they captured and held attention), (2) greater sclera exposure at target locations facilitated reaction times, and (3) attention was held by greater sclera exposure of fearful faces at task irrelevant locations resulting in delayed disengagement. Collectively, the results indicate that fearful facial expressions and sclera exposure modulate spatial attention through independent and interactive mechanisms. Sclera exposure appears to be an important facilitator of nonverbal communication and perhaps represents an understudied variable in social cognition more broadly.

The questionable validity of attention bias variability: Evidence from two conceptually unrelated cognitive tasks

Background

Attention bias variability is thought to measure fluctuations in attention towards and away from threat-related information and is elevated in affective disorders. However, recent evidence suggests that attention bias variability may quantify general reaction time variability rather than attention bias behavior per se.

Methods

The current study calculated "attention bias variability" from two conceptually unrelated cognitive tasks: the dot-probe task (measuring attentional bias) and the arrow flanker task (measuring cognitive control).

Results

Attention bias variability measures were correlated across these unrelated tasks. Yet, when general reaction time variability was controlled, attention bias variability across tasks was no longer correlated. In addition, the reliability of attention bias variability measures decreased when controlling for general reaction time variability. Finally, although attention bias variability calculated from the dot-probe task initially correlated with anxious symptoms, this association was no longer significant when controlling for general reaction time variability.

Limitations

Our sample was comprised of high trait anxious individuals. Replication in clinical samples is warranted.

Conclusions

These findings collectively provide strong empirical evidence that attention bias variability is not a valid measure of attention-related behavior, but reflective of general reaction time variability more broadly.