André G. Mendonça

This study shows that learning influences speed-accuracy tradeoffs in decision-making by combining reinforcement learning with sensory evidence accumulation in rats.

The paper derives a Bayesian learning rule for diffusion decision models that incorporates confidence and prior biases to improve decision-making under uncertainty.

This study shows that Weber's law arises from bounded evidence accumulation in rats, as evidenced by level-invariant discrimination accuracy and reaction times.