Culturally diverse facial expression signals diminish the precision of emotion communication across cultures

Abstract

Communicating emotional intensity provides rich information both about the nature and likelihood of helpful or harmful behaviors. How human facial expressions achieve this complex signalling task remains unknown. Here, using the six classic emotions—happy, surprise, fear, disgust, anger, sad—in two distinct cultures (East Asian, Western European; total N = 120 individual observers), we mathematically modelled the specific facial movements that signal emotion categories and emotion intensity. In both cultures, specific facial movements cascade emotion category and intensity information over time via a distinct temporal structure. Cross-cultural analysis revealed systematic cultural variance in these facial signals that diminishes cross-culture communication but preserves communication of priority threat-related information. Together, our results provide new insights into how facial expressions can achieve complex signalling tasks via compositional and dynamic structures.

Vocal expressions differentially transmit emotion categories and affective intensity

“…Looking at the result through the lens of emotion research more broadly, the data indicate that the representation of emotion is built from pieces; intensity and category information are, to some extent, communicated in a decoupled fashion. This is in line with recent evidence from facial emotion showing that some facial signal components can multiplex categorical and dimensional information, whereas some uniquely signal one or the other (Chen et al, 2023;Liu et al, 2022). Moreover, the results connect to the long-standing debate whether discrete categories or continuous dimensions provide better accounts to conceptualize emotion.…”

“…Next, we used an information-theoretic approach to identify the specific features of the signals which communicate either emotion, or intensity, or both-and to assay their composition at different intensities. We first assessed the statistical relationship between individual acoustic characteristics and the communication of emotion categories and, separately, their intensity, using mutual information (MI) (Chen et al, 2023;Ince et al, 2017;Liu et al, 2022). This yields a model of the acoustic features that share information with each expressed emotion category and within each category the intended intensity.…”