Facial identity influences facial expression recognition: A high-density ERP study

Abstract

The relationship between facial identity and facial expression processing has long been debated. Although previous facial recognition models indicate that facial identity and facial expression processing are independent, psychological studies using the selective attention task (the Garner paradigm) have revealed an asymmetrical relationship between the perception of identity and emotional expressions in faces: while facial expression does not influence facial identity recognition, facial identity influences facial expression recognition. We used the Garner paradigm and recorded high-density event-related potentials (ERPs) to investigate the influence of facial identity on facial expression recognition. Twenty participants judged the expression of faces, while the irrelevant dimension of identity was either held constant (control condition) or varied (orthogonal condition). We recorded 128-channel EEGs while participants completed the facial expression task. We analyzed the two major components of early visual stages: P1 and N170. ERP results revealed a significant main effect of condition on the N170 latency. These results suggest that facial identity influences facial expression recognition in the N170 that reflects the structural encoding of faces. Thus, information on facial expression might be computed based on the unique structure of individual faces.