Children process the self face using configural and featural encoding: Evidence from eye tracking

• Published in: Cognitive development Vol. 48; pp. 82 - 93
• Main Author: Hills, Peter J.
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01-10-2018
• Subjects: Configural processing; Development; Eye-tracking; Featural processing; Holistic processing; Own-face; Perceptual expertise; Pupilometry; Self face recognition; Configural processing; Self face recognition; Featural processing; Own-face; Eye-tracking; Development; Perceptual expertise; Pupilometry; Holistic processing
• ISSN: 0885-2014; 1879-226X
• DOI: 10.1016/j.cogdev.2018.07.002

•Self faces were processed with more fixations than familiar and unfamiliar faces.•This indicates enhanced use of featural processing.•Self faces were processed with more central fixations than unfamiliar faces.•This indicates enhanced use of configural processing.•Self faces were processed with more efficiency than other faces.
Much is known about how the self-face is processed neurologically, however there has been little work exploring how self, familiar, and unfamiliar faces are viewed differently. Eye-movement data provides insights for how these stimuli are encoded and pupilometry provides information regarding the amount of effort put in when processing these stimuli. In this study, we utilise eye-tracking to explore differences in the encoding of self, age- and gender-matched personally familiar faces and age- and gender-matched unfamiliar faces in school-aged children. The self face was processed using more fixations than familiar and unfamiliar faces, specifically to the most diagnostic features, indicating enhanced and efficient use of featural processing. Furthermore, the self face was processed with more and longer central fixations than unfamiliar faces, indicating enhanced use of configural processing. Finally, the self face seemed to be processed the most efficiently as revealed through our pupilometry data. These results are incorporated into a model of self face processing that is based on efficient and robust processing consistent with the neurological data indicating that multiple brain areas are used to process faces.