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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01wp988n55g
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dc.contributor.advisorTodorov, Alexander-
dc.contributor.authorTegopoulou, Ariadni-
dc.date.accessioned2018-08-16T18:32:52Z-
dc.date.available2018-08-16T18:32:52Z-
dc.date.created2018-05-14-
dc.date.issued2018-08-16-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp01wp988n55g-
dc.description.abstractExtensive literature implicates increased fear generalization as a neural mechanism involved in symptoms of anxiety. However, most human studies focus on this effect in the classical conditioning context, which involves unrealistic measures of fear. The purpose of this study was to investigate how effects of anxiety on the perceptual discrimination of similar faces is modulated by perceived social reputation, in an attempt to investigate fear generalization in a more socially meaningful context. A computerized perceptual discrimination task was used to quantify anxiety-related fear generalization in face perception. The hypothesis predicted that trait anxiety would be positively correlated with broader fear generalization of faces with negative social reputations and would have no effect on stimulus generalization of faces with positive social reputation. Individual discrimination gradients were estimated as a relative measure of fear generalization in the perceptual discrimination of faces. Results showed no effect of trait anxiety on discrimination gradients for either negative reputation or positive reputation. Plausible limitations and future directions for research in the field are discussed.en_US
dc.format.mimetypeapplication/pdf-
dc.language.isoenen_US
dc.titleThe Good, the Bad and the Ugly: An Investigation of Trait Anxiety Factors in the Perceptual Discrimination of Faces with Negative Social Reputationen_US
dc.typePrinceton University Senior Theses-
pu.date.classyear2018en_US
pu.departmentNeuroscienceen_US
pu.pdf.coverpageSeniorThesisCoverPage-
pu.contributor.authorid960862658-
Appears in Collections:Neuroscience, 2017-2020

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