For day-to-day decisions, multiple factors influence our choice between alternatives. Two dimensions of decision making that substantially affect choice are the objective perceptual properties of the stimulus (e.g., salience) and its subjective value. Here we measure EEGs in human subjects to relate their feedback-evoked EEG responses to estimates of prediction error given a neurally derived expected value for each trial. Unlike in traditional reinforcement learning paradigms, in our experiment the reward itself is not probabilistic; rather, it is a fixed value, which, when combined with the variable stimulus salience, yields uncertainty in the choice. We find that feedback-evoked event-related potentials (ERPs), specifically those classically termed feedback-related negativity, are modulated by both the reward level and stimulus salience. Using single-trial analysis of the EEG, we show stimulus-locked EEG components reflecting perceived stimulus salience can be combined with the level of reward to create an estimate of expected reward. This expected reward is used to form a prediction error that correlates with the trial-by-trial variability of the feedback ERPs for negative, but not positive, feedback. This suggests that the valence of prediction error is more important than the valence of the actual feedback, since only positive rewards were delivered in the experiment (no penalty or loss). Finally, we show that these subjectively defined prediction errors are informative of the riskiness of the subject’s choice on the subsequent trial. In summary, our work shows that neural correlates of stimulus salience interact with value information to yield neural representations of subjective expected reward.
How we make perceptual decisions depends on sensory evidence and the value of our options. These two factors often interact to yield subjective decisions; i.e., individuals integrate sensory evidence and value to form their own estimates of expected reward. Here, we use electroencephelography to identify trial-by-trial neural activity of perceived stimulus salience, showing that this activity can be combined with the value of choice options to form a representation of expected reward. Our results provide insight into the neural processing governing the interaction between salience and value and the formation of subjective expected reward and prediction error. This work is potentially important for identifying neural markers of abnormal sensory/value processing, as is seen in some cases of psychiatric illnesses.