The role of spatial frequency in emotional face classification

Previous studies with emotional face stimuli have revealed that our ability to identify different emotional states is dependent on the faces’ spatial frequency content. However, these studies typically only tested a limited number of emotional states. In the present study, we measured the consistency with which 24 different emotional states are classified when the faces are unfiltered, high-, or low-pass filtered, using a novel rating method that simultaneously measures perceived arousal (high to low) and valence (pleasant to unpleasant). The data reveal that consistent ratings are made for every emotional state independent of spatial frequency content. We conclude that emotional faces possess both high- and low-frequency information that can be relied on to facilitate classification.