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Associations between motivated learning and iron in brain tissue across adolescence

Poster Session C - Sunday, March 8, 2026, 5:00 – 7:00 pm PDT, Fairview/Kitsilano Ballrooms

Brianna M. Aubrey¹ (aubrey.b@northeastern.edu), Nicholas Kathios¹, Kelsie L. Lopez¹, Erica Niemiec¹, Haley M. Hegefeld¹, Valur Olafsson¹, Francesca Morfini^2,3, Rebecca R. Hennessy⁴, Laurel J. Gabard-Durnam¹, Psyche Loui¹, Juliet Y. Davidow¹; ¹Northeastern University, ²McLean Hospital, ³Harvard Medical School, ⁴Emory University

Adolescence is a crucial period of neurocognitive development for motivated learning. The dopamine system, including major projections from midbrain structures to the striatum, is central to motivated learning. Maturation of the dopamine system is a putative mechanism underlying normative increases in adolescent reward-driven behaviors, such as better learning. However, limited or invasive measurement of dopaminergic processes have hindered investigation of the neurodevelopment of reward systems in youth. MRI-derived R2’ is a promising non-invasive inferential measure of past dopamine activity. Specifically, R2’ indirectly quantifies brain-tissue iron, which co-localizes with dopamine vesicles as a byproduct of past dopamine synthesis. Here, we leverage this innovative measure (R2’) and a non-concurrent probabilistic reinforcement learning task to investigate developmental associations in a cross-sectional sample (N = 70, 12-24 years old). We fit a series of mixed-effect logistic binomial regression models on learning, finding a winning model including age, time, and interaction terms (χ²(2) = 9.74, p < .01). Learning improved across youth, plateauing in adolescence into young adulthood. We calculated R2’ from regions of interest, including the ventral striatum, caudate, and putamen. Across all striatal regions, R2’ had significant positive correlations with age (all ps < .05), suggesting that striatal tissue iron increases with age. These results inform our understanding of the development of the dopaminergic reward learning system using non-invasive brain imaging. Applications include improving education, mitigating risky behaviors, and diagnosis and treatment of mental health disorders.

Topic Area: THINKING: Development & aging