Deciphering Developmental Origin of Neural Connectivity Associated with Substance Use Disorder by Learning Natural Trajectory of Functional Connectivity
2026 Award: $59,939
Substance use disorder is often rooted in early brain changes that remain hidden until clinical symptoms emerge. Using our “digital bridge” framework, we reconstruct brain maturation trajectories to trace adult neural patterns back to adolescence and identify early precursors of addiction. Our goal is to support proactive, precision-based prevention before substance use problems fully develop.
Need/Problem:Substance use disorder (SUD) research is limited by a major gap between adolescent development and adult clinical outcomes. This makes it hard to separate early vulnerability from substance-related brain changes and slows progress toward proactive, precision-based prevention.
Grant Summary:SUD is a major public health crisis, but early intervention is limited by the gap between adolescent brain development and adult clinical outcomes. This project uses our flow-based generative framework (i.e., “digital bridge”) to reconstruct brain maturation trajectories, trace adult neural signatures back to early life, and identify early circuit-level precursors of addiction. The long-term goal is to enable proactive, precision-based prevention.
Goals & Projected Outcomes:This project aims to identify the neural circuit alterations underlying SUD, clarify how early network disruptions interact with stress and anxiety to shape risk, and determine whether reconstructed brain maturation trajectories can provide early imaging biomarkers of adverse substance use. The outcome is a generative modeling toolkit for modeling connectivity trajectories and identifying early-life neural precursors to support proactive, precision-based SUD prevention.
Tingting Dan, PhD
Grant Details: First, we will establish a unified computational framework to reconstruct continuous functional connectivity maturation trajectories by transporting connectivity distributions across adjacent age groups. Second, we will elucidate the mechanistic impact of developmental risks (e.g., anxiety and stress) on functional network organization, quantifying how they alter neural maturation. Third, we will identify protective and risk factors that have causal effects on the progression of SUD, specifically assessing sex differences and how a combination of healthy environmental exposures could substantially delay or prevent the onset of developing SUD.
