Classification of Emotional Expressions Is Affected by Inversion: Behavioral and Electrophysiological Evidence - Song, Jian; Liu, Min; Yao, Shun; Yan, Yan; Ding, Huichao; Yan, Tianyi; Zhao, Lun; Xu, Guozheng (Frontiers in Behavioral Neuroscience, 2017)
It has been shown that emotionally positive facial expressions are recognized substantially faster than emotionally negative facial expressions, the positive classification advantage (PCA). In the current experiment we investigated the involvement of configural computations while processing positive and negative faces in an expression categorization task. Analyzing the performance, we found that the classification of happy faces was faster than the classification of sad faces (PCA) and this effect disappeared for inverted faces. ERP 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 reaction times (RTs) and the latency of the N170 was found not 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.