Mapping the time course of the positive classification advantage: an ERP study

Abstract

The aim of the present study was to investigate the time course of the positive advantage in the expression classification of faces by recording event-related potentials (ERPs). Although neutral faces were classified more quickly than either happy or sad faces, a significant positive classification advantage (PCA)-that is, faster classification for happy than for sad faces-was found. For ERP data, as compared with sad faces, happy faces elicited a smaller N170 and a larger posterior N2 component. The P3 was modulated by facial expressions with higher amplitudes and shorter latencies for both happy and neutral stimuli than for sad stimuli, and the reaction times were significantly correlated with the amplitude and latency of the P3. Overall, these data showed robust PCA in expression classification, starting when the stimulus has been recognized as a face revealed by the N170 component.