Postdoctoral Fellowship: SPRF: Characterizing Links Between Childhood Environment and Cortical Neuroplasticity Across Adolescence

About This Grant

Under the sponsorship of Dr. Theodore Satterthwaite at the University of Pennsylvania, this award supports an early-career scientist who will study how brain development is shaped by experiences that happen during childhood and adolescence. The things that kids experience as they grow up, particularly hard or stressful things, can affect how and when their brains mature. However, how exactly the brain adapts to experiences is less well understood. Recent scientific breakthroughs have made it possible to use magnetic resonance imaging (MRI) to measure features of the brain that are sensitive to experiences. Using a large sample of youth who completed MRI scans, we will show how such experience-sensitive features of the brain develop over time. We will then validate these findings in large, independent datasets. Finally, we will examine how experiences during childhood influence individual patterns of brain development during adolescence. This research will provide new information about how the brain grows, as well as how experiences can impact these patterns of growth. This project will leverage state-of-the art machine learning and artificial intelligence techniques to model individual variability in neurodevelopment, with the goal of understanding how experiences can sculpt the developing brain. Specifically, using massive neuroimaging data resources, we will apply machine learning methods to map personalized functional networks that accurately capture each individual’s unique brain organization. We will also compute separate factor scores that capture individual variability in the childhood environment across multiple measures. Finally, we will flexibly model nonlinear age-related changes in measures indexing neuroplasticity over the course of adolescence and evaluate how age may interact with environmental factors to alter the developmental timing of these measures. Results from this project will clarify how experiences during childhood may shape the timing of neuroplasticity during development and may hold key insight for translational research seeking to improve personalized treatments for youth mental health problems. Further, this project will facilitate the development of the early career researcher’s skills in harnessing both big data and the power of artificial intelligence methods to study developmental neuroplasticity as they prepare to lead an independent lab focused on clarifying the neurobiological mechanisms linking the childhood environment with mental health outcomes. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.