When viewers are shown sets of similar objects (for example circles), they may extract summary information (e.g., average size) while retaining almost no information about the individual items. A similar observation can be made when using sets of unfamiliar faces: Viewers tend to merge identity or expression information from the set exemplars into a single abstract representation, the set average. Here, across four experiments, sets of well-known, famous faces were presented. In response to a subsequent probe, viewers recognized the individual faces very accurately. However, they also reported having seen a merged 'average' of these faces. These findings suggest abstraction of set characteristics even in circumstances which favor individuation of the items. Moreover, the present data suggest that, although seemingly incompatible, exemplar and average representations co-exist for sets consisting of famous faces. This result suggests that representations are simultaneously formed at multiple levels of abstraction.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.