Adaptive decision making relies on learning from feedback. Because feedback sometimes can be misleading, optimal learning requires that knowledge about the feedback's reliability be utilized to adjust feedback processing. Although previous research has shown that feedback reliability indeed influences feedback processing, the underlying mechanisms through which this is accomplished remain unclear. Here we propose that feedback processing is adjusted by the adaptive, top-down valuation of feedback. We assume that unreliable feedback is devalued relative to reliable feedback, thus reducing the reward prediction errors that underlie feedback-related brain activity and learning. A crucial prediction of this account is that the effects of feedback reliability are susceptible to contrast effects. That is, the effects of feedback reliability should be enhanced when both reliable and unreliable feedback are experienced within the same context, as compared to when only one level of feedback reliability is experienced. To evaluate this prediction, we measured the event-related potentials elicited by feedback in two experiments in which feedback reliability was varied either within or between blocks. We found that the fronto-central valence effect, a correlate of reward prediction errors during reinforcement learning, was reduced for unreliable feedback. But this result was obtained only when feedback reliability was varied within blocks, thus indicating a contrast effect. This suggests that the adaptive valuation of feedback is one mechanism underlying the effects of feedback reliability on feedback processing.
Keywords: Decision making; Feedback reliability; Feedback validity; Feedback-related negativity; P3.