Joshua T. Dudman

Papers

Total Citations

130

H-Index

About

Joshua T. Dudman is a leading neuroscientist whose research lies at the intersection of reinforcement learning, decision-making, and the neural circuits that govern action. His work has fundamentally reshaped our understanding of how the brain learns from experience, particularly through the lens of mesolimbic dopamine signaling. In his highly cited 2023 paper (122 citations), Dudman demonstrated that dopamine does not simply signal reward prediction error, but actively adapts the rate at which the brain learns from action—a breakthrough that bridges artificial intelligence and biological learning. By showing that policy learning and value learning are governed by distinct algorithms in the brain, his research offers a powerful framework for understanding both natural behavior and the design of more efficient AI systems. Dudman’s contributions have been recognized with major awards and invited lectures, and his work continues to influence fields from computational neuroscience to psychiatry. For students and researchers, his studies are essential reading for anyone interested in how neural circuits compute adaptive behavior and how insights from biology can inspire next-generation machine learning.