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Poster #25 - Resting State Fronto-Amygdala Network Connectivity Associated with a Parent-Focused Intervention for Childhood Anxiety

Fri, March 24, 3:30 to 4:15pm, Salt Palace Convention Center, Floor: 1, Hall A-B

Abstract

In considering the etiology of anxiety disorders, functional connections between the amygdala and prefrontal cortex (PFC) during rest play a central role in a child’s regulation of anxious behaviors (Liu et al., 2015). In this study, we draw participants from a randomized controlled trial examining the efficacy of a parent-focused anxiety intervention designed to decrease family accommodation (Supportive Parenting for Anxious Childhood Emotions; SPACE), aiming to test whether the SPACE intervention modulates patterns of resting state functional connectivity. The SPACE intervention leverages the notion that aspects of a child’s environment, such as family, are critical in the etiology and maintenance of anxiety. Family members may provide external regulation for their child or filter their child’s experienced environment. Family accommodation, where parents and other family members change their behaviors in efforts to lessen their child’s anxiety, is a common practice in pediatric anxiety disorders (Lebowitz et al., 2013). Targeting these behaviors may be an alternate treatment for pediatric anxiety, with promise for children who have not had success with other interventions.
Parents and their children (6-12 years of age with a primary diagnosis of anxiety, N = up to 60) were randomly assigned to either SPACE or a control intervention. Children completed a resting state fMRI scan before and after their parents participated in the intervention. Resting state data will be preprocessed using fMRIprep 20.2.1. Parcellated time series data will be derived using xcpEngine using 36P+DESPIKE to clean for motion artifacts (Lydon-Staley et al., 2018). We will then take a person-centered, data-driven approach to assess networks of resting state connectivity between regions of interest (ROIs). Group Iterative Multiple Model Estimation (GIMME) will be used to construct data-driven subgroups based on connectivity between ROIs from both the pre- and post-intervention resting state connectivity data (Gates et al., 2017). Bilateral ROIs will be selected as defined by the Harvard-Oxford atlas, including the amygdala, frontal medial cortex, frontal orbital cortex, and frontal pole. GIMME is unique in that it assesses contemporaneous and lagged relations, as well as autoregressive paths, in network mapping. Considering lagged relations establishes Granger causality as well as decreases false positives as compared to traditional correlation approaches to neuroimaging data (Gates & Molenaar, 2012). GIMME may present orthogonally to traditional correlation approaches, offering a different perspective on network connectivity (Gunther et al., 2022).
Descriptive statistics will characterize the nature of connectivity in each of these subgroups before and after the intervention, as well as associations between these subgroups and severity of anxiety. We hypothesize that GIMME-derived subgroups will vary in the quantity and directionality of edges between the amygdala and PFC ROIs, and that density of connections between the PFC and amygdala will relate to symptom severity. A latent transition analysis will assess the effect of the SPACE intervention on changes in connectivity. We hypothesize that the SPACE intervention (relative to the control) will increase the likelihood of a child transitioning from a subgroup characterized by fewer recovered connections between the amygdala and PFC to a subgroup with more dense connections between regions.

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