A detection theory account of change detection

Document Type: 
Article
Article Type: 
Experimental
Disciplines: 
Psychology
Topics: 
Attention
Keywords: 
feature judgment, visual short-term memory (VSTM), signal detection theory, change blindness, high-thresholdtheory, capacity limitations
Deposited by: 
patrick wilken
Date of Issue: 
2004
Authors: 
Patrick Wilken, Wei Ji Ma
Journal/Publication Title: 
Journal of Vision
Volume: 
4
Page Range: 
1120-1135
ID number: 
10.1167/4.12.11
Official URL: 
http://journalofvision.org/4/12/11/
Abstract: 
Previous studies have suggested that visual short-term memory (VSTM) has a storage limit of approximately four items. However, the type of high-threshold (HT) model used to derive this estimate is based on a number of assumptions that have been criticized in other experimental paradigms (e.g., visual search). Here we report findings from nine experiments in which VSTM for color, spatial frequency, and orientation was modeled using a signal detection theory (SDT) approach. In Experiments 1-6, two arrays composed of multiple stimulus elements were presented for 100 ms with a 1500 ms ISI. Observers were asked to report in a yes/no fashion whether there was any difference between the first and second arrays, and to rate their confidence in their response on a 1-4 scale. In Experiments 1-3, only one stimulus element difference could occur (T = 1) while set size was varied. In Experiments 4-6, set size was fixed while the number of stimuli that might change was varied (T = 1, 2, 3, and 4). Three general models were tested against the receiver operating characteristics generated by the six experiments. In addition to the HT model, two SDT models were tried: one assuming summation of signals prior to a decision, the other using a max rule. In Experiments 7-9, observers were asked to directly report the relevant feature attribute of a stimulus presented 1500 ms previously, from an array of varying set size. Overall, the results suggest that observers encode stimuli independently and in parallel, and that performance is limited by internal noise, which is a function of set size.
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