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Activity Number: 249 - Multivariate Methods for Neuroimaging Data
Type: Contributed
Date/Time: Tuesday, August 9, 2022 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistics in Imaging
Abstract #323030
Title: Random Covariance Model for Task-Based fMRI Corroborates and Reveals Connections in Neurofeedback Study of Adolescent Depression
Author(s): Lin Zhang and Karina Quevedo and Quinton Neville*
Companies: University of Minnesota and University of Minnesota and University of Minnesota
Keywords: task-based fMRI; neurofeedback; random covariance model; bi-level graphical model; adolescent depression; functional connectivity

Neuroplasticity in adolescence is a period of critical development for self-processing and emotional regulation, disruptions to which are linked to persistent depression. A recent task-based, neurofeedback fMRI study of depressed vs. healthy adolescents elicited differential functional connectivity (FC) amongst brain regions of interest (ROI). However, results were methodologically unadjusted for inherent inter-subject variability in task-based fMRI. To address this, a random covariance model (RCM) for bi-level subject and group-specific graphical models was applied to analyze FC in 17 pre-identified ROIs for (1) depressed vs. healthy, (2) suicide attempters vs. other, and (3) across the entire AAL3 atlas. RCMs were tuned with modified BIC and significance assessed with FDR-corrected 5000-permutation tests. Results in (1) corroborated significant hyper- and hypo-activation of R. and L. Amygdala-Cuneus connectivity, respectively, in depressed vs. healthy adolescents. Initial results in (2) also suggest significant Amygdala-Cuneus activation in suicide attempters vs. other, while (1) suggests exploratory results in (3) ought to yield novel, whole-brain FC differences between groups.

Authors who are presenting talks have a * after their name.

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