PROJECT SUMMARY/ABSTRACT Attention-deficit/hyperactivity disorder (ADHD) is the most commonly diagnosed developmental disorder of childhood, affecting ~9% of children nationwide. Although ADHD dramatically increases the risk for poor academic achievement, substance abuse, and criminal behavior, particularly in adolescence, too little is known regarding how neurobiological developmental trajectories underlie these behavioral and clinical outcomes. This remains the case in spite of the importance of such work for earlier identification of risk factors, more targeted treatment models, and, in turn, education, juvenile justice, and healthcare savings for individuals, families, and society. The goal of the current project, therefore, is to characterize longitudinal neural, behavioral, and clinical trajectories of youth with ADHD from late childhood to mid-adolescence. Brain systems underlying cognitive control and motivation in particular have been identified as centrally important both to the neural etiology of ADHD and to the general increase in risk-taking behavior and poor decision-making observed in typically developing (TD) adolescents. An important aspect of these models is how brain regions underlying these processes form coherent networks, as well as how these networks interact and influence each other to produce behavior. Here we bring together these two disparate literatures to gain understanding of the transition to adolescence in youth with ADHD. Thus, this proposal focuses on the maturational course of the cognitive control and motivation systems, individually and in interaction, in youth with and without ADHD in a multi-session longitudinal design. The aims of this proposal include: 1) Characterize behavioral trajectories of cognitive control, motivation, and their interaction in ADHD and TD youth from childhood into adolescence; 2) Characterize the development of structural and functional brain network organization during the same time period, focusing on brain networks underlying cognitive control and motivation; and 3) Identify neural, behavioral, and clinical features of pre-adolescent ADHD that predict clinical outcomes and risk-taking behavior during adolescence. To address these aims, innovative network analytic tools based on graph theory and structural equation modeling will be applied to structural and functional connectivity estimates of MRI data during diffusion-weighted imaging (structural) and during rest, cognitive control, motivation, and risk-taking tasks (functional). These techniques are uniquely able to simultaneously characterize the strength and coherence of within-network structural/functional connectivity and across-network interactions, as well as to identify important brain network features that differentiate across groups. Additionally, behavioral performance on the cognitive control, motivation and risk- taking tasks, ADHD symptomatology, and risk-taking attitudes and behavior will be assessed. This program of research is directly in line with the NIH Strategic Plan and builds on the RDoC framework. Together, these findings will provide the groundwork that can lead to early identification and, ultimately, prevention of ADHD trajectories that are more likely to lead to adverse outcomes in adolescence.

PROJECT NARRATIVE ADHD is a common and debilitating disorder that contributes to increased chance of deleterious risky behaviors that emerge or exacerbate in adolescence, leading to long-term negative outcomes such as addiction or incarceration. This grant proposes a comprehensive, longitudinal, multilevel (neural, behavioral, clinical) and multimodal (functional MRI, diffusion MRI) study in youth with ADHD across the transition to adolescence. By incorporating innovative brain network analytic tools and sophisticated longitudinal modeling techniques, this proposal will characterize developmental trajectories and identify childhood features that contribute to increased risk for negative outcomes in adolescence, leading to biomarker development for earlier detection of risk and more targeted treatment models for ADHD.