Gray Koudinova¹, Bozana Meinhardt-Injac², Isabelle Boutet¹; ¹University of Ottawa, Ontario, Canada, ²Catholic University of Applied Social Sciences, Berlin, Germany

Introduction: Within memory research, encoding strategies that encourage participants to think about how distinctive a semantic item is can facilitate said item’s recognition (e.g. Hertzog et al., 2018). To our knowledge, only two studies have shown a similar benefit for face recognition (Winograd, 1981; Carr et al., 2015). However, these studies used identical images at learning and test, which (1) may promote image-based rather than identity-based recognition and (2) does not reflect how familiar faces vary across real-world viewing conditions (Burton, 2016). Furthermore, other encoding strategies (e.g. social encoding) have been shown to improve face recognition even when the image format changes (e.g., Schwartz & Yovel, 2019). The present study therefore examined whether a distinctiveness encoding strategy also enhances recognition of faces presented in different formats at test. Methods: 43 undergraduate students (17-35 y/o) completed the study. In the Encoding phase, participants were shown photos of faces (each shown 5 times). Each face was accompanied by rating questions about either distinctiveness, physical features, or social traits. In the Testing phase, participants were asked to discriminate learned faces from new faces. All faces were presented twice: once with a lighting change and once with an orientation change. Analyses of recognition performance at test (d’) and reaction times during the rating task at encoding were performed. Results: Participants recognized faces better when they were encoded while rating distinctiveness and social traits compared to physical features. Participants took the longest to rate distinctiveness during the rating task at encoding. Conclusion: This study suggests that performing a distinctiveness rating task during encoding contributes to the formation of invariant face representations, as the recognition benefit extended to different testing image formats. As such, adopting a distinctiveness-based encoding strategy could be a practical support for face recognition in everyday interactions.

Acknowledgements: Supported by the Natural Sciences and Engineering Research Council of Canada Discovery Grant (2022-03998) to IB.