Asymmetries in self-face recognition
Kingston University London, United Kingdom
Self-face recognition (SFR) has been studied using morphed images of an individual’s face with another familiar or unfamiliar face, and revealed significant cerebral asymmetries (cf. Uddin et al., 2005). However, there are hardly any studies on how individuals process their own faces prior to morphing. We investigated SFR by using digitized facial features of each individual (eyes, nose or mouth areas), which were either increased or decreased in size in relation to the original image. In study 1 individuals (n = 35) had to choose which of two images showed their unaltered face (original vs. manipulated). In study 2 individuals (n = 11) view a set of faces while their eye movements to the eye region of self-faces (original or manipulated) and unfamiliar faces were monitored. In study 1 individuals were more accurate in recognizing unaltered self-faces when changes were configural rather than featural. SFR accuracy was higher when unaltered self-faces were presented to the left visual field (for both configural and featural changes). In study 2 individuals spent a greater proportion of viewing time fixating the eye region when looking at another individual’s face compared to their own (configural data being analysed). For both types of faces, significantly less time elapsed between image onset and the first fixation on the right eye region than on the left one. The right hemisphere advantage for SFR for featural changes to the eye region contrasts with a left hemisphere advantage for quick fixations. Such asymmetry may point to differences in featural processing strategies for self-face in comparison to faces of others.
XI International Conference on Cognitive Neuroscience (ICON XI), Palma, Mallorca, Spain, 25 Sep - 29 Sep, 2011.
Poster Sessions: Neural Bases of Memory and Learning
(2011). Asymmetries in self-face recognition.
Front. Hum. Neurosci.
XI International Conference on Cognitive Neuroscience (ICON XI).
24 Nov 2011;
28 Nov 2011.
Dr. Fatima Felisberti, Kingston University London, London, United Kingdom, firstname.lastname@example.org