Grant: Discovery Grants Program - Individual

Most humans can effortlessly recognize thousands of unique faces after a single glance [1, 2]. This is an impressive feat considering that all faces share the same features (i.e., two eyes, a nose and a mouth) arranged in a similar configuration (i.e., eyes above the nose above the mouth). My long-term objective is to better understand how humans recognize faces. This is a challenging question and despite a large body of literature on the topic, we are only beginning to understand this remarkable ability. Some have suggested that research in this area is progressing slowly because of a lack of focus on real-world recognition of familiar faces [15]. Indeed, most studies have focused on recognition of unfamiliar faces that are new to participants prior to the experiment and only shown once before participants are asked to recognize these `old' faces among `new' faces. This contrasts with recognition of acquaintances or famous people whose faces gradually become familiar with repeated exposure. A key difference between familiar and unfamiliar face recognition is that familiar face recognition is robust to transformations in appearance; we can recognize familiar faces despite changes in viewing pose or facial expression [13, 14]. My goal over the next five years is to advance our understanding of how robust familiar face representations are built. Visual information processing is driven by the properties of stimuli (bottom-up variables) and by the context within which stimuli appear (top-down variables). I will investigate how stimulus-driven information (Obj. 1) and contextual information (Obj. 2) support the formation of robust familiar face representations. Participants will learn a set of faces until they are familiar. Different experiments will be conducted where the type of stimulus-driven information conveyed by faces (Obj. 1) or the contextual information shown is varied (Obj. 2). When viewing a visual scene, our eyes are constantly in motion and there is evidence that eye movements are functionally relevant for the formation of memories [26, 27]. My third objective is to explore the role that eye movements play in the formation and retrieval of familiar face representations (Obj. 3). Familiar face representations are not only robust they are also durable, and most humans are able to recognize individuals they have not seen for more than 35 years [28, 29]. My fourth objective is to investigate the mechanisms that underlie long-term memory for faces (Obj. 4) by measuring face recognition after short- and long-retention delays. Impact. Understanding face recognition has important theoretical implications for models of episodic memory and specialized visual recognition systems. My research program also has practical implications for improving real-world problems such as the accuracy of eye-witness identification, face identification in security contexts (e.g., passport or police officers), and automatic facial recognition technology.