Implicit recognition of one's own and familiar faces

Introduction Behavioral evidence suggests that personally familiar faces (PFF) are processed in prioritized way (Gobbini et al., 2013; Visconti di Oleggio Castello et al., 2014; 2017; Visconti di Oleggio Castello & Gobbini, 2015). However, the mechanisms for facilitated detection of PFF is still matter of investigation. Moreover, the advantage of one's own face over other familiar faces has not been confirmed (Bortolon et al., 2017). Here, we tested if fast detection of PFF precedes explicit recognition of identity. Fast responses toward one's own and PFF were measured with a saccadic choice task and explicit recognition of identity – with a manual response. Method In a saccadic choice task two images of faces (familiar target and unfamiliar distracter) were presented simultaneously in the left and right visual fields (Crouzet et al., 2010, Visconti di Oleggio Castello & Gobbini, 2015). Participants were instructed to move their eyes towards familiar face (among them one's own face was presented). Stimuli were presented for 16, 32, or 80 ms, followed by a mask. Saccadic responses were measured with an eye-tracker. After a saccadic response, participants reported the identity of the familiar face. Results Preliminary data indicated that the accuracy of saccadic responses towards PFF was significantly higher than accuracy for manual responses for 16 ms presentation. Explicit identification of participants' own faces was more accurate compared to familiar faces recognition at the presentation time of 32 ms. For 80 ms presentation saccadic and manual responses remained highly accurate for both PFF and self-face. Conclusions Participants were able to detect familiar faces without explicit recognition. The advantage of one's own face detection over familiar faces was found only for the 32 ms presentation. Lack of differences in shorter and longer times of exposure (16 & 80 ms) suggests that PFF are perceived as efficiently as self-face. Meeting abstract presented at VSS 2018