Facial movements have over twenty dimensions of perceived meaning that are only partially captured with traditional methods

Central to science and technology are questions about how to measure facial expression. The current gold standard is the facial action coding system (FACS), which is often assumed to account for all facial muscle movements relevant to perceived emotion. However, the mapping from FACS codes to perceived emotion is not well understood. Six prototypical configurations of facial action units (AU) are sometimes assumed to account for perceived emotion, but this hypothesis remains largely untested. Here, using statistical modeling, we examine how FACS codes actually correspond to perceived emotions in a wide range of naturalistic expressions. Each of 1456 facial expressions was independently FACS coded by two experts (r = .84, κ = .84). Naive observers reported the emotions they perceived in each expression in many different ways, including emotions (N = 666); valence, arousal and appraisal dimensions (N =1116); authenticity (N = 121), and free response (N = 193). We find that facial expressions are much richer in meaning than typically assumed: At least 20 patterns of facial muscle movements captured by FACS have distinct perceived emotional meanings. Surprisingly, however, FACS codes do not offer a complete description of real-world facial expressions, capturing no more than half of the reliable variance in perceived emotion. Our findings suggest that the perceived emotional meanings of facial expressions are most accurately and efficiently represented using a wide range of carefully selected emotion concepts, such as the Cowen & Keltner (2019) taxonomy of 28 emotions. Further work is needed to characterize the anatomical bases of these facial expressions.