Learning to recognize face shapes through serial exploration

Human observers are experts at visual face recognition due to specialized visual mechanisms for face processing that evolve with perceptual expertize. Such expertize has long been attributed to the use of configural processing, enabled by fast, parallel information encoding of the visual information in the face. Here we tested whether participants can learn to efficiently recognize faces that are serially encoded—that is, when only partial visual information about the face is available at any given time. For this, ten participants were trained in gaze-restricted face recognition in which face masks were viewed through a small aperture controlled by the participant. Tests comparing trained with untrained performance revealed (1) a marked improvement in terms of speed and accuracy, (2) a gradual development of configural processing strategies, and (3) participants’ ability to rapidly learn and accurately recognize novel exemplars. This performance pattern demonstrates that participants were able to learn new strategies to compensate for the serial nature of information encoding. The results are discussed in terms of expertize acquisition and relevance for other sensory modalities relying on serial encoding