STEMorph: A Set of Morphed Emotional Face Stimuli from Angry to Happy Derived fromNimStim

Abstract

AbstractEmotion recognition is crucial for interpreting social cues, with facial expressions being the primary channel for such communication. Despite its importance, emotion recognition is often influenced by biases, in which we show a systematic recognition advantage for a particular emotion. These biases, however, are inconsistently reported across studies, likely due to methodological variations, underlining the necessity for a standardized approach. Traditional face morphing methods, although widely used, can create unnatural-looking stimuli, which may confound the interpretation of emotions. Addressing this issue, we here introduceSTEMorph, a validated stimulus set based on theNimStimfacial expression set. Our approach utilizes neutral-anchored morphing and neural-network-generated masks to ensure the natural appearance and integrity of the depicted emotions. we validated our stimulus set by presenting morphed emotional faces to participants and asking them to rate the emotional valence of each stimulus. TheSTEMorph’svalidity was confirmed through linear regression analysis, showing a strong correlation between subjective ratings and targeted emotional states. Additionally, subgroup analysis by gender of both the depicted faces and the participants showed uniform results. Moreover, we confirmed the reliability ofSTEMorphby asking the same participants to rate the stimuli two weeks later. In conclusion, by introducing a controlled, validated, and ecologically valid stimulus set of emotional faces, our study paves the way for further investigations aimed at unraveling the complexities of facial emotion recognition and deepening our understanding of this vital aspect of human interaction.