5/29/2010 PERMALINK
Learning strategies are associated with distinct neural signatures. California Institute of Technology : The process of learning requires the sophisticated ability to constantly update our expectations of future rewards so we may make accurate predictions about those rewards in the face of a changing environment. Although exactly how the brain orchestrates this process remains unclear, a new study suggests that a combination of two distinct learning strategies guides our behavior. One accepted learning strategy, called model-free learning, relies on trial-and-error comparisons between the reward we expect in a given situation and the reward we actually get. The result of this comparison is the generation of a "reward prediction error," which corresponds to that difference. For example, a reward prediction error might correspond to the difference between the projected monetary return on a financial investment and our real earnings. In the second mechanism, called model-based learning, the brain generates a cognitive map of the environment that describes the relationship between different situations. "Model-based learning is associated with the generation of a 'state prediction error,' which represents the brain's level of surprise in a new situation given its current estimate of the environment," says Jan Glascher, a postdoctoral scholar at Caltech and the lead author of the study.