Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/2633
Title: Comparison of two weighted integration models for the cueing task: Linear and likelihood.
Authors: Shimozaki, S. S.
Eckstein, M. P.
Abbey, C. K.
First Published: 2003
Citation: Journal of Vision, 2003, 3, pp.209-229
Abstract: In a task in which the observer must detect a signal at two locations, presenting a precue that predicts the location of a signal leads to improved performance with a valid cue (signal location matches the cue), compared to an invalid cue (signal location does not match the cue). The cue validity effect has often been explained with a limited capacity attentional mechanism improving the perceptual quality at the cued location. Alternatively, the cueing effect can also be explained by unlimited capacity models that assume a weighted combination of noisy responses across the two locations. We compare two weighted integration models, a linear model and a sum of weighted likelihoods model based on a Bayesian observer. While qualitatively these models are similar, quantitatively they predict different cue validity effects as the signal-to-noise ratios (SNR) increase. To test these models, 3 observers performed in a cued discrimination task of Gaussian targets with an 80% valid precue across a broad range of SNR’s. Analysis of a limited capacity attentional switching model was also included and rejected. The sum of weighted likelihoods model best described the psychophysical results, suggesting that human observers approximate a weighted combination of likelihoods, and not a weighted linear combination.
DOI Link: 10.1167/3.3.3
ISSN: 1534-7362
Links: http://hdl.handle.net/2381/2633
http://jov.arvojournals.org/article.aspx?articleid=2192557
Type: Article
Appears in Collections:Published Articles, School of Psychology

Files in This Item:
There are no files associated with this item.


Items in LRA are protected by copyright, with all rights reserved, unless otherwise indicated.