Going to extremes: the influence of unsupervised categories on the mental caricaturization of faces and asymmetries in perceptual discrimination

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dc.contributor.authorHendrickson, A.
dc.contributor.authorCarvalho, P.
dc.contributor.authorGoldstone, R.
dc.contributor.conferenceThe 34th Annual Meeting of the Cognitive Science Society (CogSci 2012) (1 Aug 2012 - 4 Aug 2012 : Sapporo, Japan)
dc.contributor.editorMiyake, N.
dc.contributor.editorPeebles, D.
dc.contributor.editorCooper, R.
dc.date.issued2012
dc.description.abstractRecent re-analysis of traditional Categorical Perception (CP) effects show that the advantage for between category judgments may be due to asymmetries of within-category judgments (Hanley & Roberson, 2011). This has led to the hypothesis that labels cause CP effects via these asymmetries due to category label uncertainty near the category boundary. In Experiment 1 we demonstrate that these “within-category” asymmetries exist before category training begins. Category learning does increase the within-category asymmetry on a category relevant dimension but equally on an irrelevant dimension. Experiment 2 replicates the asymmetry found in Experiment 1 without training and shows that it does not increase with additional exposure in the absence of category training. We conclude that the within-category asymmetry may be a result of unsupervised learning of stimulus clusters that emphasize extreme instances and that category training increases this caricaturization of stimulus representations.
dc.description.statementofresponsibilityAndrew T. Hendrickson, Paulo F. Carvalho, Robert L. Goldstone
dc.identifier.citationProceedings of the 34th Annual Meeting of the Cognitive Science Society: Building bridges across cognitive sciences aournd the world, 2012 / Miyake, N., Peebles, D., Cooper, R. (ed./s), pp.1662-1667
dc.identifier.isbn9780976831884
dc.identifier.orcidHendrickson, A. [0000-0002-5690-2412]
dc.identifier.urihttp://hdl.handle.net/2440/102334
dc.language.isoen
dc.rightsCopyright status unknown
dc.source.urihttps://mindmodeling.org/cogsci2012/
dc.subjectCategorical perception; category labels; perceptual learning; category learning; language
dc.titleGoing to extremes: the influence of unsupervised categories on the mental caricaturization of faces and asymmetries in perceptual discrimination
dc.typeConference paper
pubs.publication-statusPublished

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