Multiple Systems in Decision Making: A Neurocomputational Perspective

Various psychological models posit the existence of two systems that contribute to decision making. The first system is bottom-up, automatic, intuitive, emotional, and implicit, while the second system is top-down, controlled, deliberative, and explicit. It has become increasingly evident that this dichotomy is both too simplistic and too vague. Here we consider insights gained from a different approach, one that considers the multiple computational demands of the decision-making system in the context of neural mechanisms specialized to accomplish some of that system's more basic functions. The use of explicit computational models has led to (a) identification of core trade-offs imposed by a single-system solution to cognitive problems that are solved by having multiple neural systems, and (b) novel predictions that can be tested empirically and that serve to further refine the models.