Abstract: Outcome evaluation is one of the important functions of the cognitive system. It can provide rapid and efficient information about the outcomes of one’s behavior in order to facilitate the performance of the behavior. Recently, researchers have shown great interest in the neural mechanisms of outcome evaluation. Many studies have confirmed that a significant ERP component—feedback-related negativity (FN)—could be elicited by negative performance feedback compared to positive outcomes. The purpose of this study was to investigate the mechanisms of the outcome evaluation reflected by FN and to explore whether FN is affected by the magnitude information carrying different intensity levels of the expectation.
To observe the outcome evaluation following complex cognitive processes, a deception task was conducted in a simulated experimental situation involving the identification of currency. The participants were required to identify pictures of genuine Renminbi (RMB) from a set of pictures of fake ones. The participants were asked to press the left key to indicate genuine RMB pictures and the right key to indicate fake ones. However, we told them that for each genuine RMB picture, they could decide whether to “declare” (tell the truth) or “smuggle” (lie) and that telling the truth would result in them receiving a small but certain monetary reward, whereas lying may lead to a potential gain if they escaped being caught or a risk of double penalty if their lie was detected by the software.
Seventeen healthy undergraduates who had never participated in any electroencephalography (EEG) experiment before volunteered for this study. The EEG was recorded from 64 scalp channels using electrodes mounted in an elastic cap. Feedback-related ERPs were calculated for an 800 ms epoch including a 100 ms pre-feedback baseline. The outcome valences (gain when deception was successful and loss when deception was unsuccessful) by the magnitudes (pictures of the RMB worth 1, 5, and 10) resulted in six waveforms. The brain electrical source analysis (BESA) technique was also adopted in order to estimate the dipole sourcing of FN.
The ERPs of the truthful condition were obviously distinct from those of the two deceptive conditions. With regard to the deceptive conditions, compared with the “gain” feedback, the “loss” outcomes elicited a more negative deflection at the frontocentral sites in the time windows of 230–450 ms. A repeated-measures ANOVA on the mean amplitudes of this time window revealed significant main effects of the outcome valences and the magnitudes; however, the interaction between these two factors did not reach significance. Further tests indicated that the “loss” outcomes elicited larger FN than did the gain outcomes and the magnitudes did not affect the FN. Finally, sourcing analysis showed that FN may be generated from brain regions near the anterior cingulated cortex (ACC).
These results suggested that the FN was sensitive to the valance rather than the magnitude of the outcome information. This finding is in agreement with the contemporary theories of outcome evaluation as well as the developed concept of the “adaptive critic” in the reinforcement learning error-related negativity (ERN) hypothesis, which suggested that FN reflected a binary evaluation of good versus bad outcomes based on whether the outcomes were consistent with the expectation

Key words: Feedback Negativity, outcome evaluation, contemporary theories of dichotomy, ERP