Face adaptation techniques have been used extensively to investigate how faces are processed. It has even been suggested that face adaptation is functional in calibrating the visual system to the diet of faces to which an observer is exposed. Yet most adaptation studies to date have used unfamiliar faces: few have used faces with real world familiarity. Familiar faces have more abstractive representations than unfamiliar faces. The experiments in this thesis therefore examined face adaptation for familiar faces. Chapters 2 and 3 explored the role of explicit recognition of familiar faces in producing face identity after-effects (FIAEs). Chapter 2 used composite faces (the top half of a celebrity's face paired with the bottom half of an unfamiliar face) as adaptors and showed that only recognised composites produced significant adaptation. In Chapter 3 the adaptors were cryptic faces (unfamiliar faces subtly transformed towards a celebrity's face) and faces of celebrity's siblings. Unrecognised cryptic and sibling faces produced FIAEs for their related celebrity, but only when adapting and testing on the same viewpoint. Adaptation only transferred across viewpoint when a face was explicitly recognised. Chapter 4 demonstrated that face adaptation could occur for ecologically valid, personally familiar stimuli, a necessary pre-requisite if adaptation is functional in calibrating face processing mechanisms. A video of a lecturer's face produced FIAEs equivalent to that produced by static images. Chapters 5 and 6 used a different type of after-effect, the face distortion after-effect (FDAE), to explore the stability of our representations for personally familiar faces, and showed that even representations of highly familiar faces can be affected by exposure to distorted faces. The work presented here shows that it is important to take facial familiarity into account when investigating face adaptation effects, as well as increasing our understanding of how familiarity affects the representations of faces.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:589066 |
Date | January 2013 |
Creators | Laurence, Sarah |
Publisher | University of Sussex |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | http://sro.sussex.ac.uk/id/eprint/47140/ |
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