Neural correlates of extinguished threat recall underlying the commonality between pediatric anxiety and irritability

Pre-scan state anxiety is associated with greater right amygdala-hippocampal response to fearful versus happy faces among trait-anxious Latina girls

BACKGROUND

Unfamiliarity with academic research may contribute to higher levels of anticipatory state anxiety about affective neuroimaging tasks. Children with high trait anxiety display differences in brain response to fearful facial affect compared to non-anxious youth, but little is known about the influence of state anxiety on this association. Because reduced engagement in scientific research and greater mistrust among minoritized groups may lead to systematic differences in pre-scan state anxiety, it is crucial to understand the neural correlates of state anxiety during emotion processing so as to disambiguate sources of individual differences.

METHODS

The present study probed the interactive effects of pre-scan state anxiety, trait anxiety, and emotional valence (fearful vs. happy faces) on neural activation during implicit emotion processing in a community sample of 46 preadolescent Latina girls (8-13 years).

RESULTS

Among girls with mean and high levels of trait anxiety, pre-scan state anxiety was associated with greater right amygdala-hippocampal and left inferior parietal lobe response to fearful faces relative to happy faces.

CONCLUSIONS

Anticipatory state anxiety in the scanning context may cause children with moderate and high trait anxiety to be hypervigilant to threats, further compounding the effects of trait anxiety. Neuroimaging researchers should control for state anxiety so that systematic differences in brain activation resulting from MRI apprehension are not misleadingly attributed to demographic or environmental characteristics.

The relationship between self-control and mental health problems among Chinese university students

Background

Mental health issues are often associated with poor self-control. Therefore, effective interventions against mental health problems should include self-control training. However, it is unclear whether the effect of self-control varies across different types of mental health problems.

Methods

A cross-sectional survey was conducted using the convenience sampling method at five universities in Chongqing, China, where 1,409 students reported their demographic information, level of self-control, and symptoms of irritability, depression, and anxiety. Descriptive statistical methods and a network analysis approach were employed to explore the relationship between self-control and symptoms of irritability, depression, and anxiety among 1,409 students. The bridging links between self-control and the three mental health problems were analyzed.

Results

The findings revealed a negative correlation between self-control and symptoms of irritability, depression, and anxiety among university students. Impulse control was found to be the bridge between self-control and irritability or anxiety symptoms, while resistance to temptation was the bridge between self-control and depressive symptoms.

Conclusion

These results demonstrate the different relationship between self-control with irritability, anxiety, and depressive symptoms. The findings of this study may shed light on future mental health interventions for university students during potential public health emergencies, such as prior knowledge of the main types of psychological problems among university students, which may allow for the development of precise self-control intervention strategies, such as targeting impulsivity or resistance to temptation.

A Computational Model Reveals Learning Dynamics During Interpretation Bias Training With Clinical Applications

BACKGROUND

Some psychopathologies, including anxiety and irritability, are associated with biases when judging ambiguous social stimuli. Interventions targeting these biases, or interpretation bias training (IBT), are amenable to computational modeling to describe their associative learning mechanisms. Here, we translated ALCOVE (attention learning covering map), a model of category learning, to describe learning in youths with affective psychopathology when training on more positive judgments of ambiguous face emotions.

METHODS

A predominantly clinical sample comprised 71 youths (age range, 8-22 years) representing broad distributions of irritability and anxiety symptoms. Of these, 63 youths were included in the test sample by completing an IBT task with acceptable performance for computational modeling. We used a separate sample of 28 youths to translate ALCOVE for individual estimates of learning rate and generalization. In the test sample, we assessed associations between model learning estimates and irritability, anxiety, their shared variance (negative affectivity), and age.

RESULTS

Age and affective symptoms were associated with category learning during IBT. Lower learning rates were associated with higher negative affectivity common in anxiety and irritability. Lower generalization, or improved discrimination between face emotions, was associated with increasing age.

CONCLUSIONS

This work demonstrates a functional consequence of age- and symptom-related learning during interpretation bias. Learning measured by ALCOVE also revealed learning types not accounted for in the prior literature on IBT. This work more broadly demonstrates the utility of measurement models for understanding trial-by-trial processes and identifying individual learning styles.

Systematic Review and Meta-analysis: Task-based fMRI Studies in Youths With Irritability

OBJECTIVE

Childhood irritability, operationalized as disproportionate and frequent temper tantrums and low frustration tolerance relative to peers, is a transdiagnostic symptom across many pediatric disorders. Studies using task-dependent functional magnetic resonance imaging (fMRI) to probe neural dysfunction in irritability have increased. However, an integrated review summarizing the published methods and synthesized fMRI results remains lacking.

METHOD

We conducted a systematic search using irritability terms and task functional neuroimaging in key databases in March 2021, and identified 30 studies for our systematic review. Sample characteristics and fMRI methods were summarized. A subset of 28 studies met the criteria for extracting coordinate-based data for quantitative meta-analysis. Ten activation-likelihood estimations were performed to examine neural convergence across irritability measures and fMRI task domains.

RESULTS

Systematic review revealed small sample sizes (median = 58, mean age range = 8-16 years) with heterogeneous sample characteristics, irritability measures, tasks, and analytical procedures. Meta-analyses found no evidence for neural activation convergence of irritability across neurocognitive functions related to emotional reactivity, cognitive control, and reward processing, or within each domain. Sensitivity analyses partialing out variances driven by heterogeneous tasks, irritability measures, stimulus types, and developmental ages all yielded null findings. Results were compared with a review on irritability-related structural anomalies from 11 studies.

CONCLUSION

The lack of neural convergence suggests a need for common, standardized irritability assessments and more homogeneous fMRI tasks. Thoughtfully designed fMRI studies probing commonly defined neurocognitive functions may be more fruitful to elucidate the neural mechanisms of irritability. Open science practices, data mining in large neuroscience databases, and standardized analytical methods promote meaningful collaboration in irritability research.

Computational modeling of threat learning reveals links with anxiety and neuroanatomy in humans

Influential theories implicate variations in the mechanisms supporting threat learning in the severity of anxiety symptoms. We use computational models of associative learning in conjunction with structural imaging to explicate links among the mechanisms underlying threat learning, their neuroanatomical substrates, and anxiety severity in humans. We recorded skin-conductance data during a threat-learning task from individuals with and without anxiety disorders (N=251; 8-50 years; 116 females). Reinforcement-learning model variants quantified processes hypothesized to relate to anxiety: threat conditioning, threat generalization, safety learning, and threat extinction. We identified the best-fitting models for these processes and tested associations among latent learning parameters, whole-brain anatomy, and anxiety severity. Results indicate that greater anxiety severity related specifically to slower safety learning and slower extinction of response to safe stimuli. Nucleus accumbens gray-matter volume moderated learning-anxiety associations. Using a modeling approach, we identify computational mechanisms linking threat learning and anxiety severity and their neuroanatomical substrates.