Neural computation as a tool to differentiate perceptual from emotional processes: The case of anger superiority effect

Research findings in social and cognitive psychology imply that it is easier to detect angry faces than happy faces in a crowd of neutral faces [Hansen, C. H., & Hansen, R. D. (1988). Finding the face in the crowd – An anger superiority effect. Journal of Personality and Social Psychology, 54(6), 917–924]. This phenomenon has been held to have evolved over phylogenetic development because it was adaptive to quickly and accurately detect a potential threat in the environment. However, across recent studies, a controversy has emerged about the underlying perceptual versus emotional factors responsible for this so-called anger superiority effect [Juth, P., Lundqvist, D., Karlsson, A., & Ohman, A. (2005). Looking for foes and friends: Perceptual and emotional factors when finding a face in the crowd. Emotion, 5(4), 379–395; Purcell, D. G., Stewart, A. L., & Skov, R. B. (1996). It takes a confounded face to pop out of a crowd. Perception, 25(9), 1091–1108]. To tease apart emotional and perceptual processes, we used neural network analyzes of human faces in two different simulations. Results show that a perceptual bias is probably acting against faster and more accurate identification of anger faces compared to happy faces at a purely perceptual level. We suggest that a parsimonious hypothesis related to the simple perceptual properties of the stimuli might explain these behavioral results without reference to evolutionary processes. We discuss the importance of statistical or connectionist analysis for empirical studies that seek to isolate perceptual from emotional factors, but also learned vs. innate factors in the processing of facial expression of emotion.