This thesis investigated how familiarity can ease visual processing and promote
what Jacoby and Dallas (1981) called the fluency heuristic. I conducted a series of nine experiments that investigated the influence of familiarity on attention and visual working memory (WM). Attentional blink (AB) and visual search paradigms were employed to measure attention; a change detection task was employed to measure visual WM capacity. Familiarity effects were examined by comparing unfamiliar versus famous faces, and Hanzi experts versus Hanzi novices. Hanzi are Chinese characters, and represented complex, non-face objects. Whereas unfamiliar faces showed a significant AB effect, famous faces did not. Search for famous faces was significantly more efficient than search for unfamiliar faces; this familiarity benefit was replicated with Hanzi.
Change detection was significantly more accurate and WM capacity estimates were larger for famous than unfamiliar faces, suggesting that familiarity increased visual WM maintenance effectiveness; this familiarity benefit was replicated with Hanzi. When faces and Hanzi were inverted, the familiarity advantage was removed from the visual WM task and remained only for faces in the visual search task. In summary, (upright) familiar stimuli required less attention for processing, were more efficiently encoded, and were more effectively maintained in visual WM than unfamiliar stimuli. I propose that the
familiarity advantage reflects better within-item integration (binding between features and their configurations), perhaps enabled by enhanced neural synchrony, and supported by long-term memory representations. I present a new model - fluency-by-integration - to illustrate how familiarity might promote fluent visual processing and reduce the burden on attention and visual WM resources.