Boundary extension: Insights from signal detection theory

Author(s)Liu,Zili
Author(s)Yang,Xiaoyang
Author(s)Intraub,Helene
Ordered AuthorZili Liu, Xiaoyang Yang, Helene Intraub
UD AuthorIntraub, Helene
Date Accessioned2017-07-13T20:01:50Z
Date Available2017-07-13T20:01:50Z
Copyright DateThe Author(s) 2016
Publication Date6/9/16
DescriptionPublisher's PDF
AbstractAfter viewing a scene, people often remember having seen more of the world than was originally visible, an error referred to as boundary extension. Despite the large number of studies on this phenomenon, performance has never been considered in terms of signal detection theory (SDT). We report two visual memory experiments that allowed us to explore boundary extension in terms of SDT. In our experiments, participants first studied pictures presented as close-up or wide-angle views. At test, either the identical view or a different view (a closer or wider angle version of the same scene) were presented and participants rated the test image as being the same or different than before on a 6-point scale. We found that both discrimination sensitivity and bias contributed to the boundary extension effect. The discrimination sensitivity difference was at least 28%, and its presence refuted the hypothesis that boundary extension was due solely to participants' response bias to label test pictures as more wide-angled. Instead, our results support the idea that participants' responses reflect false memory beyond the view (i.e., a more wide-angle view of the world).
DepartmentUniversity of Delaware, Department of Psychology
CitationLiu, Z., Yang, X., & Intraub, H. (2016). Boundary extension: Insights from signal detection theory. Journal of Vision, 16(8), 7. doi:10.1167/16.8.7
DOI10.1167/16.8.7
ISSN1534-7362
URLhttp://udspace.udel.edu/handle/19716/21543
LanguageEnglish
PublisherThe Association for Research in Vision and Ophthalmology, Inc
dc.rightsCC BY NC ND 4.0
dc.sourceJournal of Vision
dc.source.urihttp://jov.arvojournals.org/article.aspx?articleid=2528088
TitleBoundary extension: Insights from signal detection theory
TypeArticle
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