Yael Niv
Papers
1
Total Citations
13
H-Index
1
About
Yael Niv is a leading figure in computational and cognitive neuroscience, whose work bridges reinforcement learning, decision-making, and psychiatric disorders. Her research focuses on how the brain learns from reward and punishment, particularly in uncertain environments. Niv's major contributions include developing computational models that explain how dopamine and the basal ganglia guide adaptive behavior, and how these processes break down in conditions like addiction and schizophrenia. Her most-cited work, "Evolution of Reinforcement Learning in Uncertain Environments: Emergence of Risk-Aversion and Matching" (2001), has garnered 13 citations and laid foundational insights into risk-sensitive learning. Beyond this, her broader body of work has been cited thousands of times, reflecting her profound impact on understanding the neural mechanisms of learning and choice. Niv is also known for her influential role in advancing open science and reproducible research practices in neuroscience. Her achievements include being a recipient of the prestigious James S. McDonnell Foundation Scholar Award and serving as a professor at Princeton University, where she leads the Computational Cognitive Neuroscience Lab.
Research Focus
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Top Papers
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