Multivariate Assessment of Inhibitory Control in Youth: Links With Psychopathology and Brain Function.

Inhibitory control is central to many theories of cognitive and brain development, and impairments in inhibitory control are posited to underlie developmental psychopathology. In this study, we tested the possibility of shared versus unique associations between inhibitory control and three common symptom dimensions in youth psychopathology: attention-deficit/hyperactivity disorder (ADHD), anxiety, and irritability. We quantified inhibitory control using four different experimental tasks to estimate a latent variable in 246 youth (8-18 years old) with varying symptom types and levels. Participants were recruited from the Washington, D.C., metro region. Results of structural equation modeling integrating a bifactor model of psychopathology revealed that inhibitory control predicted a shared or general psychopathology dimension, but not ADHD-specific, anxiety-specific, or irritability-specific dimensions. Inhibitory control also showed a significant, selective association with global efficiency in a frontoparietal control network delineated during resting-state functional magnetic resonance imaging. These results support performance-based inhibitory control linked to resting-state brain function as an important predictor of comorbidity in youth psychopathology.

BOLD Response is more than just magnitude: Improving detection sensitivity through capturing hemodynamic profiles.

Typical fMRI analyses often assume a canonical hemodynamic response function (HRF) that primarily focuses on the peak height of the overshoot, neglecting other morphological aspects. Consequently, reported analyses often reduce the overall response curve to a single scalar value. In this study, we take a data-driven approach to HRF estimation at the whole-brain voxel level, without assuming a response profile at the individual level. We then employ a roughness penalty at the population level to estimate the response curve, aiming to enhance predictive accuracy, inferential efficiency, and cross-study reproducibility. By examining a fast event-related FMRI dataset, we demonstrate the shortcomings and information loss associated with adopting the canonical approach. Furthermore, we address the following key questions: 1) To what extent does the HRF shape vary across different regions, conditions, and participant groups? 2) Does the data-driven approach improve detection sensitivity compared to the canonical approach? 3) Can analyzing the HRF shape help validate the presence of an effect in conjunction with statistical evidence? 4) Does analyzing the HRF shape offer evidence for whole-brain response during a simple task?

An Exposure-Based Cognitive-Behavioral Therapy for Youth with Severe Irritability: Feasibility and Preliminary Efficacy.

OBJECTIVE: Clinically impairing irritability and temper outbursts are among the most common psychiatric problems in youth and present transdiagnostically; however, few mechanistically informed treatments have been developed. Here, we test the acceptability, feasibility, and preliminary efficacy of a novel exposure-based treatment with integrated parent management skills for youth with severe irritability using a randomized between-subjects multiple baseline design. METHOD: N = 41 patients (Age, Mean (SD) = 11.23 years (1.85), 62.5% male, 77.5% white) characterized by severe and impairing temper outbursts and irritability were randomized to different baseline observation durations (2, 4, or 6 weeks) prior to active treatment; 40 participants completed the 12 session treatment of exposure-based cognitive-behavioral therapy for irritability with integrated parent management skills. Masked clinician ratings were acquired throughout baseline and treatment phases, as well as 3- and 6-months post-treatment. To examine acceptability and feasibility, drop-out rates and adverse events were examined. Primary clinical outcome measures included clinician-administered measures of irritability severity and improvement. Secondary clinical outcome measures included multi-informant measures of irritability, depression, anxiety, and attention-deficit/hyperactivity disorder symptoms. RESULTS: No patients dropped out once treatment began, and no adverse events were reported. Irritability symptoms improved during the active phase of treatment across all measurements (all ßs > -0.04, ps < .011, Cohen's d range: -0.33 to -0.98). Treatment gains were maintained at follow-up (all ßs(39) < -0.001, ps > .400). Sixty-five percent of patients were considered significantly improved or recovered post-treatment based on the primary clinician-rated outcome measure. CONCLUSIONS: Results support acceptability, feasibility, and preliminary efficacy of this novel treatment for youth with severe irritability. Limitations and future directions are also discussed.

Hyperbolic trade-off: The importance of balancing trial and subject sample sizes in neuroimaging.

Here we investigate the crucial role of trials in task-based neuroimaging from the perspectives of statistical efficiency and condition-level generalizability. Big data initiatives have gained popularity for leveraging a large sample of subjects to study a wide range of effect magnitudes in the brain. On the other hand, most task-based FMRI designs feature a relatively small number of subjects, so that resulting parameter estimates may be associated with compromised precision. Nevertheless, little attention has been given to another important dimension of experimental design, which can equally boost a study's statistical efficiency: the trial sample size. The common practice of condition-level modeling implicitly assumes no cross-trial variability. Here, we systematically explore the different factors that impact effect uncertainty, drawing on evidence from hierarchical modeling, simulations and an FMRI dataset of 42 subjects who completed a large number of trials of cognitive control task. We find that, due to an approximately symmetric hyperbola-relationship between trial and subject sample sizes in the presence of relatively large cross-trial variability, 1) trial sample size has nearly the same impact as subject sample size on statistical efficiency; 2) increasing both the number of trials and subjects improves statistical efficiency more effectively than focusing on subjects alone; 3) trial sample size can be leveraged alongside subject sample size to improve the cost-effectiveness of an experimental design; 4) for small trial sample sizes, trial-level modeling, rather than condition-level modeling through summary statistics, may be necessary to accurately assess the standard error of an effect estimate. We close by making practical suggestions for improving experimental designs across neuroimaging and behavioral studies.

Reliability of task-evoked neural activation during face-emotion paradigms: Effects of scanner and psychological processes.

Assessing and improving test-retest reliability is critical to efforts to address concerns about replicability of task-based functional magnetic resonance imaging. The current study uses two statistical approaches to examine how scanner and task-related factors influence reliability of neural response to face-emotion viewing. Forty healthy adult participants completed two face-emotion paradigms at up to three scanning sessions across two scanners of the same build over approximately 2 months. We examined reliability across the main task contrasts using Bayesian linear mixed-effects models performed voxel-wise across the brain. We also used a novel Bayesian hierarchical model across a predefined whole-brain parcellation scheme and subcortical anatomical regions. Scanner differences accounted for minimal variance in temporal signal-to-noise ratio and task contrast maps. Regions activated during task at the group level showed higher reliability relative to regions not activated significantly at the group level. Greater reliability was found for contrasts involving conditions with clearly distinct visual stimuli and associated cognitive demands (e.g., face vs. nonface discrimination) compared to conditions with more similar demands (e.g., angry vs. happy face discrimination). Voxel-wise reliability estimates tended to be higher than those based on predefined anatomical regions. This work informs attempts to improve reliability in the context of task activation patterns and specific task contrasts. Our study provides a new method to estimate reliability across a large number of regions of interest and can inform researchers' selection of task conditions and analytic contrasts.

Changes in Internalizing Symptoms During the COVID-19 Pandemic in a Transdiagnostic Sample of Youth: Exploring Mediators and Predictors.

The COVID-19 pandemic is a chronically stressful event, particularly for youth. Here, we examine (i) changes in mood and anxiety symtpoms, (ii) pandemic-related stress as a mediator of change in symptoms, and (ii) threat processing biases as a predictor of increased anxiety during the pandemic. A clinically well-characterized sample of 81 youth ages 8-18 years (M = 13.8 years, SD = 2.65; 40.7% female) including youth with affective and/or behavioral psychiatric diagnoses and youth without psychopathology completed pre- and during pandemic assessments of anxiety and depression and COVID-related stress. Forty-six youth also completed a threat processing fMRI task pre-pandemic. Anxiety and depression significantly increased during the pandemic (all ps < 0.05). Significant symptom change was partially mediated by pandemic stress and worries. Increased prefrontal activity in response to neutral faces pre-pandemic was associated with more intense parent-reported anxiety during the pandemic (all Fs(1.95,81.86) > 14.44, ps < 0.001). The present work extends existing knowledge on the mediating role of psychological stress on symptoms of anxiety and depression in youth.

Trial and error: A hierarchical modeling approach to test-retest reliability.

The concept of test-retest reliability indexes the consistency of a measurement across time. High reliability is critical for any scientific study, but specifically for the study of individual differences. Evidence of poor reliability of commonly used behavioral and functional neuroimaging tasks is mounting. Reports on low reliability of task-based fMRI have called into question the adequacy of using even the most common, well-characterized cognitive tasks with robust population-level effects, to measure individual differences. Here, we lay out a hierarchical framework that estimates reliability as a correlation divorced from trial-level variability, and show that reliability tends to be underestimated under the conventional intraclass correlation framework through summary statistics based on condition-level modeling. In addition, we examine how reliability estimation between the two statistical frameworks diverges and assess how different factors (e.g., trial and subject sample sizes, relative magnitude of cross-trial variability) impact reliability estimates. As empirical data indicate that cross-trial variability is large in most tasks, this work highlights that a large number of trials (e.g., greater than 100) may be required to achieve precise reliability estimates. We reference the tools TRR and 3dLMEr for the community to apply trial-level models to behavior and neuroimaging data and discuss how to make these new measurements most useful for future studies.

A computational network perspective on pediatric anxiety symptoms.

BACKGROUND: While taxonomy segregates anxiety symptoms into diagnoses, patients typically present with multiple diagnoses; this poses major challenges, particularly for youth, where mixed presentation is particularly common. Anxiety comorbidity could reflect multivariate, cross-domain interactions insufficiently emphasized in current taxonomy. We utilize network analytic approaches that model these interactions by characterizing pediatric anxiety as involving distinct, inter-connected, symptom domains. Quantifying this network structure could inform views of pediatric anxiety that shape clinical practice and research. METHODS: Participants were 4964 youths (ages 5-17 years) from seven international sites. Participants completed standard symptom inventory assessing severity along distinct domains that follow pediatric anxiety diagnostic categories. We first applied network analytic tools to quantify the anxiety domain network structure. We then examined whether variation in the network structure related to age (3-year longitudinal assessments) and sex, key moderators of pediatric anxiety expression. RESULTS: The anxiety network featured a highly inter-connected structure; all domains correlated positively but to varying degrees. Anxiety patients and healthy youth differed in severity but demonstrated a comparable network structure. We noted specific sex differences in the network structure; longitudinal data indicated additional structural changes during childhood. Generalized-anxiety and panic symptoms consistently emerged as central domains. CONCLUSIONS: Pediatric anxiety manifests along multiple, inter-connected symptom domains. By quantifying cross-domain associations and related moderation effects, the current study might shape views on the diagnosis, treatment, and study of pediatric anxiety.

Emotional distractors and attentional control in anxious youth: eye tracking and fMRI data.

Attentional control theory suggests that high cognitive demands impair the flexible deployment of attention control in anxious adults, particularly when paired with external threats. Extending this work to pediatric anxiety, we report two studies utilising eye tracking (Study 1) and functional magnetic resonance imaging (Study 2). Both studies use a visual search paradigm to examine anxiety-related differences in the impact of threat on attentional control at varying levels of task difficulty. In Study 1, youth ages 8-18 years (N = 109), completed the paradigm during eye tracking. Results indicated that youth with more severe anxiety took longer to fixate on and identify the target, specifically on difficult trials, compared to youth with less anxiety. However, no anxiety-related effects of emotional distraction (faces) emerged. In Study 2, a separate cohort of 8-18-year-olds (N = 72) completed a similar paradigm during fMRI. Behaviourally, youth with more severe anxiety were slower to respond on searches following non-threatening, compared to threatening, distractors, but this effect did not vary by task difficulty. The same interaction emerged in the neuroimaging analysis in the superior parietal lobule and precentral gyrus-more severe anxiety was associated with greater brain response following non-threatening distractors. Theoretical implications of these inconsistent findings are discussed.

Modulatory effects of dynamic fMRI-based neurofeedback on emotion regulation networks in adolescent females.

Research has shown that difficulties with emotion regulation abilities in childhood and adolescence increase the risk for developing symptoms of mental disorders, e.g anxiety. We investigated whether functional magnetic resonance imaging (fMRI)-based neurofeedback (NF) can modulate brain networks supporting emotion regulation abilities in adolescent females. We performed three experiments (Experiment 1: N â€‹= â€‹18; Experiment 2: N â€‹= â€‹30; Experiment 3: N â€‹= â€‹20). We first compared different NF implementations regarding their effectiveness of modulating prefrontal cortex (PFC)-amygdala functional connectivity (fc). Further we assessed the effects of fc-NF on neural measures, emotional/metacognitive measures and their associations. Finally, we probed the mechanism underlying fc-NF by examining concentrations of inhibitory and excitatory neurotransmitters. Results showed that NF implementations differentially modulate PFC-amygdala fc. Using the most effective NF implementation we observed important relationships between neural and emotional/metacognitive measures, such as practice-related change in fc was related with change in thought control ability. Further, we found that the relationship between state anxiety prior to the MRI session and the effect of fc-NF was moderated by GABA concentrations in the PFC and anterior cingulate cortex. To conclude, we were able to show that fc-NF can be used in adolescent females to shape neural and emotional/metacognitive measures underlying emotion regulation. We further show that neurotransmitter concentrations moderate fc-NF-effects.

Levels of early-childhood behavioral inhibition predict distinct neurodevelopmental pathways to pediatric anxiety.

BACKGROUND: Anxiety symptoms gradually emerge during childhood and adolescence. Individual differences in behavioral inhibition (BI), an early-childhood temperament, may shape developmental paths through which these symptoms arise. Cross-sectional research suggests that level of early-childhood BI moderates associations between later anxiety symptoms and threat-related amygdala-prefrontal cortex (PFC) circuitry function. However, no study has characterized these associations longitudinally. Here, we tested whether level of early-childhood BI predicts distinct evolving associations between amygdala-PFC function and anxiety symptoms across development. METHODS: Eighty-seven children previously assessed for BI level in early childhood provided data at ages 10 and/or 13 years, consisting of assessments of anxiety and an fMRI-based dot-probe task (including threat, happy, and neutral stimuli). Using linear-mixed-effects models, we investigated longitudinal changes in associations between anxiety symptoms and threat-related amygdala-PFC connectivity, as a function of early-childhood BI. RESULTS: In children with a history of high early-childhood BI, anxiety symptoms became, with age, more negatively associated with right amygdala-left dorsolateral-PFC connectivity when attention was to be maintained on threat. In contrast, with age, low-BI children showed an increasingly positive anxiety-connectivity association during the same task condition. Behaviorally, at age 10, anxiety symptoms did not relate to fluctuations in attention bias (attention bias variability, ABV) in either group; by age 13, low-BI children showed a negative anxiety-ABV association, whereas high-BI children showed a positive anxiety-ABV association. CONCLUSIONS: Early-childhood BI levels predict distinct neurodevelopmental pathways to pediatric anxiety symptoms. These pathways involve distinct relations among brain function, behavior, and anxiety symptoms, which may inform diagnosis and treatment.

Advancing clinical neuroscience through enhanced tools: Pediatric social anxiety as an example.

BACKGROUND: Clinical researchers face challenges when trying to quantify diverse processes engaged during social interactions. We report results from two studies, each demonstrating the potential utility of tools for examining processes engaged during social interactions. METHOD: In the first study, youth (n = 57) used a smartphone-based tool to rate mood and responses to social events. A subset (n = 20) completed the second, functional magnetic resonance imaging study. This second study related anxiety to error-evoked brain responses in two social conditions-while being observed and when alone. We also combined these tools to bridge clinical, social-contextual, and neural levels of measurement. RESULTS: Results from the first study showed an association between negatively-perceived social experiences and a range of negative emotions. In the second study there was a positive correlation during error monitoring between social-anxiety severity and context-specific activation of the pregenual anterior cingulate cortex. Finally, during imaging, the perceived quality of peer interactions as assessed using the smartphone-based tool, interacted with social context to predict levels of activation in the hippocampus and superior frontal gyrus. CONCLUSIONS: By improving measurement, enhanced tools may provide new means for studying relationships among anxiety, brain function, and social interactions.

Intraclass correlation: Improved modeling approaches and applications for neuroimaging.

Intraclass correlation (ICC) is a reliability metric that gauges similarity when, for example, entities are measured under similar, or even the same, well-controlled conditions, which in MRI applications include runs/sessions, twins, parent/child, scanners, sites, and so on. The popular definitions and interpretations of ICC are usually framed statistically under the conventional ANOVA platform. Here, we provide a comprehensive overview of ICC analysis in its prior usage in neuroimaging, and we show that the standard ANOVA framework is often limited, rigid, and inflexible in modeling capabilities. These intrinsic limitations motivate several improvements. Specifically, we start with the conventional ICC model under the ANOVA platform, and extend it along two dimensions: first, fixing the failure in ICC estimation when negative values occur under degenerative circumstance, and second, incorporating precision information of effect estimates into the ICC model. These endeavors lead to four modeling strategies: linear mixed-effects (LME), regularized mixed-effects (RME), multilevel mixed-effects (MME), and regularized multilevel mixed-effects (RMME). Compared to ANOVA, each of these four models directly provides estimates for fixed effects and their statistical significances, in addition to the ICC estimate. These new modeling approaches can also accommodate missing data and fixed effects for confounding variables. More importantly, we show that the MME and RMME approaches offer more accurate characterization and decomposition among the variance components, leading to more robust ICC computation. Based on these theoretical considerations and model performance comparisons with a real experimental dataset, we offer the following general-purpose recommendations. First, ICC estimation through MME or RMME is preferable when precision information (i.e., weights that more accurately allocate the variances in the data) is available for the effect estimate; when precision information is unavailable, ICC estimation through LME or the RME is the preferred option. Second, even though the absolute agreement version, ICC(2,1), is presently more popular in the field, the consistency version, ICC(3,1), is a practical and informative choice for whole-brain ICC analysis that achieves a well-balanced compromise when all potential fixed effects are accounted for. Third, approaches for clear, meaningful, and useful result reporting in ICC analysis are discussed. All models, ICC formulations, and related statistical testing methods have been implemented in an open source program 3dICC, which is publicly available as part of the AFNI suite. Even though our work here focuses on the whole-brain level, the modeling strategy and recommendations can be equivalently applied to other situations such as voxel, region, and network levels.

Establishing a system with Drosophila melanogaster (Diptera: Drosophilidae) to assess the non-target effects of gut-active insecticidal compounds.

Potentially adverse effects on ecosystem functioning by the planting of insect-resistant, genetically engineered plants or by the direct application of insecticidal compounds are carefully evaluated in pre-market risk assessments. To date, few studies have assessed the potential risks of genetically engineered crops or insecticidal compounds on the survival and fitness of dipteran species, despite their important contribution to ecosystem services such as decomposition in agricultural systems. Therefore, we propose that Drosophila melanogaster Meigen (Drosophilidae) be used as a surrogate species for the order Diptera and for the functional guild of soil arthropod decomposers in pre-market risk assessments. We developed two assays to assess the toxicity of gut-active insecticidal compounds to D. melanogaster. One assay uses groups of fly larvae, and the other uses individuals. Cryolite, a mineral pesticide, proved to be an adequate positive control. The effects of cryolite on D. melanogaster larvae were comparable between the two assays. Statistical power analyses were used to define the number of replications required to identify different effect sizes between control and treatment groups. Finally, avidin, E-64, GNA, and SBTI were used as test compounds to validate the individual-based assay; only avidin adversely affected D. melanogaster. These results indicate that both D. melanogaster assays will be useful for early tier risk assessment concerning the effects of orally active compounds on non-target dipterans.

Eye-tracking measurement of attention bias to social threat among youth: A replication and extension study.

Attentional bias to social threat cues has been linked to heightened anxiety and irritability in youth. Yet, inconsistent methodology has limited replication and led to mixed findings. The current study aims to 1) replicate and extend two previous pediatric studies demonstrating a relationship between negative affectivity and attentional bias to social threat and 2) examine the test-retest reliability of an eye-tracking paradigm among a subsample of youth. Attention allocation to negative versus non-negative emotional faces was measured using a free-viewing eye-tracking task among youth (N=185 total, 60% female, M age=13.10 years, SD age=2.77) with three face-pair conditions: happy-angry, neutral-disgust, sad-happy. Replicating procedures of two previous studies, linear mixed-effects models compared attention bias between children with anxiety disorders and healthy controls. Bifactor analysis was used to parse shared versus unique facets of general negative affectivity (i.e., anxiety, irritability), which were then examined in relation to attention bias. Test-retest reliability of the bias-index was estimated among a subsample of youth (N=36). No significant differences in attention allocation or bias emerged between anxiety and healthy control groups. While general negative affectivity across the sample was not associated with attention bias, there was a positive relationship for anxiety and irritability on duration of attention allocation toward negative faces. Test-retest reliability for attention bias was moderate (r=0.50, p<.01). While anxiety-related findings from the two previous studies were not replicated, the relationship between attention bias and facets of negative affect suggests a potential target for treatment. Evidence for test-retest reliability encourages future use of the eye-tracking task for researchers.

Evaluating the development and well-being assessment (DAWBA) in pediatric anxiety and depression.

Enhancing screening practices and developing scalable diagnostic tools are imperative in response to the increasing prevalence of youth mental health challenges. Structured lay psychiatric interviews have emerged as one such promising tool. However, there remains limited research evaluating structured psychiatric interviews, specifically their characterization of internalizing disorders in treatment-seeking youth. This study evaluates the relationship between the Development and Well-Being Assessment (DAWBA), a structured psychiatric interview, and established measures of pediatric anxiety and depression, including the Screen for Child Anxiety Related Disorders (SCARED), the Pediatric Anxiety Rating Scale (PARS), and the Mood and Feelings Questionnaire (MFQ). The study comprised two independent clinical samples of treatment-seeking youth: sample one included 55 youth with anxiety and 29 healthy volunteers (HV), while sample two included 127 youth with Major Depressive Disorder and 73 HVs. We examined the association between the DAWBA band scores, indicating predicted risk for diagnosis, the SCARED and PARS (sample one), and the MFQ (sample two). An exploratory analysis was conducted in a subset of participants to test whether DAWBA band scores predicted the change in anxiety symptoms (SCARED, PARS) across a 12-week course of cognitive behavioral therapy. The results revealed that the DAWBA significantly predicted the SCARED, PARS and MFQ measures at baseline; however, it did not predict changes in anxiety symptoms across treatment. These findings suggest that the DAWBA may be a helpful screening tool for indexing anxiety and depression in treatment-seeking youth but is not especially predictive of longitudinal trajectories in symptomatology across psychotherapy.

Differentiating neural sensitivity and bias during face-emotion processing in youth: a computational approach.

The ability to interpret face-emotion displays is critical for the development of adaptive social interactions. Using a novel variant of a computational model and fMRI data, we examined behavioral and neural associations between two metrics of face-emotion labeling (sensitivity and bias) and age in youth. Youth and adults (n = 44, M age = 20.02, s.d. = 7.44, range = 8-36) completed an explicit face-emotion labeling fMRI task including happy to angry morphed face emotions. A drift-diffusion model was applied to choice and reaction time distributions to examine sensitivity and bias in interpreting face emotions. Model fit and reliability of parameters were assessed on adult data (n = 42). Linear and quadratic slopes modeled brain activity associated with dimensions of face-emotion valence and ambiguity during interpretation. Behaviorally, age was associated with sensitivity. The bilateral anterior insula exhibited a more pronounced neural response to ambiguity with older age. Associations between sensitivity and bias metrics and activation patterns indicated that systems encoding face-emotion valence and ambiguity both contribute to the ability to discriminate face emotions. The current study provides evidence for age-related improvement in perceptual sensitivity to facial affect across adolescence and young adulthood.

Normalization of Fronto-Parietal Activation by Cognitive-Behavioral Therapy in Unmedicated Pediatric Patients With Anxiety Disorders.

OBJECTIVE: Anxiety disorders are prevalent among youths and are often highly impairing. Cognitive-behavioral therapy (CBT) is an effective first-line treatment. The authors investigated the brain mechanisms associated with symptom change following CBT. METHODS: Unmedicated youths diagnosed with an anxiety disorder underwent 12 weeks of CBT as part of two randomized clinical trials testing the efficacy of adjunctive computerized cognitive training. Across both trials, participants completed a threat-processing task during functional MRI before and after treatment. Age-matched healthy comparison youths completed two scans over the same time span. The mean age of the samples was 13.20 years (SD=2.68); 41% were male (youths with anxiety disorders, N=69; healthy comparison youths, N=62). An additional sample including youths at temperamental risk for anxiety (N=87; mean age, 10.51 years [SD=0.43]; 41% male) was utilized to test the stability of anxiety-related neural differences in the absence of treatment. Whole-brain regional activation changes (thresholded at p<0.001) were examined using task-based blood-oxygen-level-dependent response. RESULTS: Before treatment, patients with an anxiety disorder exhibited altered activation in fronto-parietal attention networks and limbic regions relative to healthy comparison children across all task conditions. Fronto-parietal hyperactivation normalized over the course of treatment, whereas limbic responses remained elevated after treatment. In the at-risk sample, overlapping clusters emerged between regions showing stable associations with anxiety over time and regions showing treatment-related changes. CONCLUSIONS: Activation in fronto-parietal networks may normalize after CBT in unmedicated pediatric anxiety patients. Limbic regions may be less amenable to acute CBT effects. Findings from the at-risk sample suggest that treatment-related changes may not be attributed solely to the passage of time.

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.

Development of Neural Mechanisms Underlying Threat Processing: Associations With Childhood Social Reticence and Adolescent Anxiety.

Background: Social reticence in early childhood is characterized by shy and anxiously avoidant behavior, and it confers risk for pediatric anxiety disorders later in development. Aberrant threat processing may play a critical role in this association between early reticent behavior and later psychopathology. The goal of this longitudinal study is to characterize developmental trajectories of neural mechanisms underlying threat processing and relate these trajectories to associations between early-childhood social reticence and adolescent anxiety. Methods: In this 16-year longitudinal study, social reticence was assessed from 2 to 7 years of age; anxiety symptoms and neural mechanisms during the dot-probe task were assessed at 10, 13, and 16 years of age. The sample included 144 participants: 71 children provided data at age 10 (43 girls, meanage = 10.62), 85 at age 13 (46 girls, meanage = 13.25), and 74 at age 16 (36 girls, meanage = 16.27). Results: A significant interaction manifested among social reticence, anxiety symptoms, and time, on functional connectivity between the left amygdala and the left dorsolateral prefrontal cortex, voxelwise p < .001, clusterwise familywise error p < .05. Children with high social reticence showed a negative association between amygdala-dorsolateral prefrontal cortex connectivity and anxiety symptoms with age, compared to children with low social reticence, suggesting distinct neurodevelopmental pathways to anxiety. Conclusions: These findings were present across all conditions, suggesting task-general effects in potential threat processing. Additionally, the timing of these neurodevelopmental pathways differed for children with high versus low social reticence, which could affect the timing of effective preventive interventions.