Contrasting predictions of low- and high-threshold models for the detection of changing visual features

Burmester, Alex and Wallis, Guy (2012) Contrasting predictions of low- and high-threshold models for the detection of changing visual features. Perception, 41 5: 505-516. doi:10.1068/p7176

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Author Burmester, Alex
Wallis, Guy
Title Contrasting predictions of low- and high-threshold models for the detection of changing visual features
Journal name Perception   Check publisher's open access policy
ISSN 0301-0066
1468-4233
Publication date 2012-01-01
Year available 2012
Sub-type Article (original research)
DOI 10.1068/p7176
Open Access Status Not Open Access
Volume 41
Issue 5
Start page 505
End page 516
Total pages 12
Place of publication London, United Kingdom
Publisher Pion
Language eng
Abstract Change blindness is the failure of observers to notice otherwise obvious changes to a visual scene when those changes are masked in some way (eg by blotches or a blanking of the screen). Typically, change blindness is taken as evidence that our representation of the visual world is capacity limited. The locus of this capacity limit is thought to be visual short-term memory (vSTM). The capacity of vSTM is usually estimated with a high-threshold model which assumes that each element in the stimulus array is either fully encoded or not encoded at all, and, furthermore, that false alarms can arise only by guessing, not by noise. Low-threshold models, by contrast, suggest that false alarms can arise by noise at the level of detection/discrimination and/or decision. In this study, we use a well-controlled stimulus display in which a single element changes over a blanking of the screen and contrast predictions from a popular high-threshold model of vSTM with the predictions of a low-threshold model (specifically, the sample-size model) of visual search and vSTM. The data were better predicted by the low-threshold model.
Keyword Change blindness
Visual search
vSTM
Sample size
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2013 Collection
School of Human Movement and Nutrition Sciences Publications
 
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Created: Mon, 19 Nov 2012, 20:59:06 EST by Deborah Noon on behalf of School of Human Movement and Nutrition Sciences