Corrugator activity reflects integrated simulation and multifaceted evaluation when processing affective language: Frowning responses to reading about emotions of morally good and bad characters.

Abstract

Corrugator supercilii ("frowning muscle") activity tracks affective valence of linguistic stimuli. According to embodied cognition accounts, this reflects simulation of the emotion at lexical and/or situational levels. Additionally, it may indicate evaluation, i.e., how we feel about an affective event within a context. This study used facial electromyography (fEMG) to examine corrugator responses as participants read short stories. Each story included segments, describing some character's morally good or bad behavior, a behavior rating, and sentence-initial phrases describing the character's positive or negative affective states (e.g., "Mark is frustrated"), followed by the reason for this. Our prior studies showed substantially more frowning when good characters were "frustrated" compared with "happy" but minimal differences for bad characters, suggesting a multiple-drivers account where both simulation and evaluation influence responses. Crucially, they can counteract in the context of bad characters, e.g., "happy" has positive valence but is unfair in context and the opposite applies to "frustrated." To emphasize characters' moral status and amplify fairness-based evaluations, an embedded morality judgment rating task was introduced. We hypothesized stronger frowning for "happy" than "frustrated" bad characters due to fairness considerations now outweighing simulation. However, results revealed increased frowning for "frustrated" bad characters. The rating task might have unexpectedly reduced, rather than boosted, evaluative processing through cognitive interference. Nevertheless, previously observed frowning patterns for moral characters were replicated. These findings support a multiple-drivers model but suggest that evaluative processes are more complex and multifaceted than current models capture, calling for revisions to incorporate these complexities into affective processing theories.