In conclusion, there is an impressive agreement from a wide variety of animal and human paradigms for the involvement of at least two systems in decision-making and control. The simpler of these two, associated with habits and model-free RL, has attracted a huge wealth of work, and there are ample studies (also confirmed here) elucidating its basic learning mechanisms driven by a reward prediction error. By comparison, the more sophisticated, model-based, system, with its rich adaptability and flexibility, has been more sparsely studied. Here, we have pinned down what is perhaps the most critical and basic signal for this system, namely the state prediction error. In particular, we showed that the two error signals are computed in partially distinct brain areas and illustrated how human choice behavior may emerge through the combination of the systems.
