The neurotransmitter dopamine is crucial for decision-making under uncertainty, but its computational role is still a subject of intense debate. To test its potential roles, we invited patients with Parkinson's disease (PD), who have less internally generated dopamine, to participate in a visual decision-making task in which uncertainty in both prior and current sensory information was varied. Behaviour during these tasks is often predicted by Bayesian statistics. We found that many aspects of uncertainty processing were conserved in PD patients: They could learn the prior uncertainty and utilize both prior and current sensory information. As predicted by prominent theories, we found that dopaminergic medication influenced the weight given to sensory information. However, as PD patients learned, this bias disappeared. In addition, throughout the experiment the patients exhibited lower sensitivity to current sensory uncertainty compared with age-matched controls. Our results provide empirical evidence for the idea that dopamine levels, which are affected by PD and the drugs used for its treatment, influence the reliance on new information.