Air Pollution, Multidimensional Behavior, and Neuroimaging in Children with Neurodevelopmental Disorders

I am a dually trained neuroscientist and environmental epidemiologist with a primary research interest in understanding how early-life environmental exposures shape brain development. This R00 proposal supports my transition to an independent, transdisciplinary investigator in the emerging field of big-data environmental developmental neuroscience. Leveraging rich, existing behavioral and multi-modal MRI data from the Healthy Brain Network (HBN), a large-scale neurodevelopmental biobank, I propose to investigate how prenatal exposure to fine particulate air pollution (PM2.s) influences neurodevelopmental outcomes. Using a novel spatiotemporal model, I will estimate weekly PM2.s exposure throughout gestation and apply lagged weighted quantile sum (LWQS) regression to identify sensitive windows of exposure. Rather than relying on diagnostic categories, I adopt a cross-diagnostic, dimensional approach that focuses on continuous measures of social and attentional functioning-key domains impacted in both autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD). In this R00 phase, I will acquire longitudinal behavioral and neuroimaging data to examine how prenatal PM2.5 exposure shapes developmental trajectories in these domains. This project advances our understanding of the neurobiological mechanisms linking environmental exposures to neurodevelopmental disorders and provides a foundation for preventive strategies and targeted interventions. My long-term goal is to establish an independent research program using large-scale data to uncover environmental determinants of brain and behavioral development in children.