Youth violence victimization is common and increases risk for a host of negative health outcomes, most notably posttraumatic stress disorder (PTSD), which is the strongest predictor of poor quality of life following trauma, even among those injured during the event. Given the potential harmful sequelae of trauma exposure, it is crucial to identify acute post-victimization risk factors that predict chronic PTSD. At this juncture relatively little data exists to aid in prediction of youth at risk for poor long-term adjustment following victimization or other types of trauma, and there are no studies measuring relevant neural systems. Thus, our team aims to 1) characterize acute post-victimization neurobehavioral predictors of risk for chronic PTSD with a focus on prefrontal-subcortical function during processing of threat processing and frontoparietal networks for cognitive control, and 2) use machine learning to identify the most robust set of predictors of chronic PTSD drawn from a comprehensive assessment of youth neuroimaging, behavior and self-report, parent and family factors, and neighborhood and community variables. Our team is well-prepared to successfully achieve these aims, as we have relevant expertise in conducting prospective longitudinal assessment of acute neurobehavioral predictors of risk for PTSD in adults (Larson), conducting longitudinal assessment of youth victims of violence (Levas), and longitudinally characterizing neurobehavioral profiles of youth PTSD (Herringa). We will recruit youth victims of violence aged 10-16 from the Emergency Department at Children’s Hospital of Wisconsin in Milwaukee, and conduct comprehensive assessments at 2 weeks, 3 months, and 12 months following victimization. To achieve a final sample of 200 youth at 12 month follow-up, we will recruit 240 youth, oversampled for risk for PTSD based on currently available brief self-report indicators. Each assessment will include measures of neural systems instantiating threat processing, including both reactivity to threat and anticipation of unpredictable and predictable threat, and cognitive control, along with measures of PTSD and other symptoms, cognitive functioning, family environment, social and school functioning, and socioenvironmental factors (e.g. neighborhood disadvantage, discrimination). We will examine how acute post- victimization variables (2 week) and early change following victimization (from 2 weeks to 3 months) predict PTSD and other outcomes twelve months later. We will use both hypothesis-driven analyses focusing on a priori specified regions and predictors, as well as comprehensive data-driven machine learning analyses. The comprehensive assessment will allow for determination of the additional utility of neural markers for predicting risk beyond previously identified self-report indicators. We expect this project to lead to identification of predictors of risk for PTSD following victimization that are linked to underlying processes ...