When the outcome is different than expected: Subjective expectancy shapes reward prediction error at the FRN level. (12th August 2019) - Walentowska, Wioleta; Severo, Mario Carlo; Moors, Agnes; Pourtois, Gilles
Abstract: Converging evidence in human electrophysiology suggests that evaluative feedback provided during performance monitoring (PM) elicits two distinctive and successive ERP components: the feedback‐related negativity (FRN) and the P3b. Whereas the FRN has previously been linked to reward prediction error (RPE), the P3b has been conceived as reflecting motivational or attentional processes following the early processing of the RPE, including action value updating. However, it remains unclear whether these two consecutive neurophysiological effects depend on the direction of the unexpectedness (better‐ or worse‐than‐expected outcomes; signed RPE) or instead only on the degree of unexpectedness irrespective of direction (i.e., unsigned RPE). To address this question, we devised an experiment in which we manipulated the objective reward probability and the subjective reward expectancy (via instructions) in a factorial within‐subject design and explored amplitude changes of the FRN and the P3b. A 64‐channel EEG was recorded while 32 participants performed a speeded go/no‐go task in which evaluative feedback based on the reward probability either violated expectancy (thereby creating a RPE) or did not. This violation corresponded either to better‐ or worse‐than‐expected events. Results showed that the FRN was larger when RPE occurred than when it did not, but irrespective of the direction of this violation. Interestingly, in these two conditions, action value was updated for the positive feedback selectively, as shown by the P3b amplitude. These results obey a two‐stage model of PM assuming that unsigned RPE is first rapidly detected (FRN level) before the positive feedback's value is updated selectively (P3b effect). Abstract : It is debated in the literature whether the feedback‐related negativity (FRN) codes for a signed or an unsigned reward prediction error (RPE). In this study, we found that the FRN size was similar for worse‐ and better‐than‐expected events, suggesting that salience drives the detection of mismatches between outcome and expectancy. Following the FRN, the P3b was selectively increased for positive feedback when outcome and expectancy mismatched. These results call for a two‐stage performance monitoring (PM) model: early detection of violations between action and prediction at the FRN level is followed by an update of the positive feedback's value at the P3b level.