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Garga Chatterjee, Robert Luedeman, Ken Nakayama; A test to explore the learning of multiple novel faces. Journal of Vision 2008;8(6):183. doi: https://doi.org/10.1167/8.6.183.
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© ARVO (1962-2015); The Authors (2016-present)
In the world, encoding and learning of faces does not occur in isolation. We are exposed to and need to learn multiple faces, including encoding and learning in the presence of other faces. We developed the Progressive Face Learning Test to characterize individual differences in learning multiple novel faces in a short period as well as the effect of interference from other faces learned on learning rates.The test starts with a single face to be learned, which after presentation, is to be identified from a choice of faces, containing the target face and numerous foils.The number of faces to be learned is progressively increased by adding a new face after testing all the faces presented in the previous round.Faces to be learned as well as foils were chosen to be of comparable subjective distinctiveness.The test was used to characterize and compare different aspects of learning of faces like overall performance, learning rates and rate of change of learning rates for individual faces as well as with progressively increasing number of faces.Comparisons were done between people who have normal face recognition ability, above normal face recognition ability (“super-recognizers”) and below normal face recognition ability, including prosopagnosics.
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