Classification of Emotional Expressions Is Affected by Inversion: Behavioral and Electrophysiological Evidence

It has been shown that emotionally positive facial expressions are recognized substantially faster than emotionally negative facial expressions, the positive classification advantage (PCA). In this experiment we explored the involvement of configural computations while processing positive and negative faces in an expression categorization task using artificial faces. Analyzing the reaction times (RTs), we found that happy faces were categorized more quickly than sad faces (PCA) and this effect disappeared for inverted faces. Event-related potentials (ERPs) data showed that the face-sensitive N170 component was larger for sad than for happy faces only at upright condition and that face inversion significantly enhanced N170 amplitudes only for happy faces. Moreover, the happy faces elicited shorter N170 latency than did the sad faces, whereas for inverted condition the N170 latency did not differ between happy and sad faces. Finally, the significant positive correlation between the RTs and the latency of the N170 was not found for N170 amplitudes. Because the configural computation was task-irrelevant in the present study, these behavioral and ERP data indicated that one of the sources of PCA is the configural analysis applied by default while categorizing facial emotions.