Dongjae Kim

Reward prediction error neurons implement an efficient code for reward

The paper shows that reward prediction error neurons encode rewards efficiently, aligning with principles from sensory neuroscience and reinforcement learning.

Prefrontal solution to the bias-variance tradeoff during reinforcement learning

The paper describes how the brain resolves the bias-variance tradeoff during reinforcement learning through adaptive control of model-based and model-free learning, supported by behavioral, computational, and neural evidence.

Task complexity interacts with state-space uncertainty in the arbitration process between model-based and model-free reinforcement-learning at both behavioral and neural levels

The paper investigates how task complexity and state-space uncertainty influence the arbitration between model-based and model-free reinforcement learning at both behavioral and neural levels.