B0279
Title: Nonparametric motion adjustment in studies of functional connectivity alterations in autistic children
Authors: Jialu Ran - Emory University (United States)
Benjamin Risk - Emory University (United States)
David Benkeser - Emory University (United States)
Benjamin Risk - Emory University (United States) [presenting]
Abstract: Autism spectrum disorder (ASD) is a common neurodevelopmental condition associated with difficulties with social interactions, communication and restricted and repetitive behaviours. To study the characteristics of ASD, investigators often use functional connectivity derived from resting-state functional magnetic resonance imaging. However, participants' head motion during the scanning session can induce motion artifacts. Many studies remove scans with excessive motion, but children who move more tend to have more severe symptoms. Scan exclusion can lead to drastic reductions in sample size and introduce selection bias. A framework to decompose neural and motion-induced sources of functional connectivity group differences between autistic children and typically developing children is proposed, without excluding high-motion participants. Motion is adjusted via causal mediation with stochastic interventions, where motion and other covariates are flexibly modelled using an ensemble of machine learning methods. The framework is applied to estimate the difference in functional connectivity between autistic children and typically developing children. The analyses indicate that some long-range connections between a seed region in the default mode network and frontal-parietal regions exhibit hyperconnectivity in ASD. Naively including high-motion children appears to cause spurious differences. Naively excluding high-motion children removed group differences.
