The feedback-related negativity indexes prediction error in active but not observational learning

Item does not contain fulltextReinforcement learning (RL) theory states that learning is driven by prediction errors (PEs) - the discrepancy between the predicted and actual outcome of an action. When participants learn from their own actions, PEs correlate with the feedback-related negativity (FRN), but it is not clear if the FRN reflects a PE in observational learning. We use a model-based regression analysis of single-trial event-related potentials to determine if the FRN in observational learning is PE driven. Twenty participants (16 female) learned the stimulus-outcome contingencies for a probabilistic three-armed bandit task. They played in pairs, with the acting and observing player switching every one to three trials. An RL-learning algorithm was fit to participants' choices in the task to extract individual PE estimates for every trial of the experiment. In the acting condition, model-estimated PEs covaried positively with neural signal at electrode FCz, 200-350 ms after outcome presentation, which is a typical time frame for the FRN. There was no PE effect in the observation condition in the same time frame. From 300 ms the outcome correlated negatively with the frontal P300 component at FCz and parietal P300 at Pz. At Pz the effect was greater in the acting than the observing condition. The frontal and parietal P300 components have been linked to attentional reorienting and stimulus value updating, respectively. These findings indicate that observed outcomes undergo processing that is distinguishable from directly experienced outcomes in the time windows of the FRN and P3b but that attention dedicated to the two outcomes types is comparable.17 p