Reshaping the happy face advantage with reinforcement learning

Recognising emotional expressions is important for successful social interactions. Prior research has demonstrated that emotion recognition is influenced by evaluative associations people have with different social categories. Here, we systematically investigate whether reinforcement learning can modify social category biases in emotion recognition. Previous research has shown that reinforcement learning is a promising method for altering evaluative associations. In Experiment 1 (<i>N</i> = 40), we replicated that the Happy Face Advantage is influenced by social category membership. People were faster at recognising happiness as happiness than anger as anger⁠ for White - Dutch faces, while no difference was found for Moroccan - Dutch faces. In Experiments 2-3 (<i>Ntotal</i> <i>=</i> 144), we used a reinforcement learning go/no-go task, in which people learned to act to images of Moroccan - Dutch faces to obtain rewards and to not act to images of White - Dutch faces to avoid punishments before participating in the emotion recognition task. Results show that reinforcement learning influences emotion recognition. Instead of the commonly observed interaction effect between social category and expression valence (e.g. in Experiment 1 and previous work), we consistently found a main effect of valence on emotion recognition. These findings suggest that aligning (in)actions with rewards/punishments changes emotion recognition.