2014
DOI: 10.1167/14.10.1060
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Effect of object-substitution masking on the perceptual quality of object representations

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Cited by 2 publications
(2 citation statements)
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“…We adopted the statistical models that have been previously used in modeling VSTM (Bays, Catalao, & Husain, 2009;Zhang & Luck, 2008) and several visual phenomena such as crowding (Ester, Zilber, & Serences, 2015) and masking (Agaoglu, Agaoglu, Breitmeyer, & Ogmen, 2015;Harrison, Rajsic, & Wilson, 2014). The simplest model is a single Gaussian (referred to as the G model from now on) whose mean and standard deviation may be modulated by attention and/or masking.…”
Section: Statistical Modeling Of Response Errorsmentioning
confidence: 99%
“…We adopted the statistical models that have been previously used in modeling VSTM (Bays, Catalao, & Husain, 2009;Zhang & Luck, 2008) and several visual phenomena such as crowding (Ester, Zilber, & Serences, 2015) and masking (Agaoglu, Agaoglu, Breitmeyer, & Ogmen, 2015;Harrison, Rajsic, & Wilson, 2014). The simplest model is a single Gaussian (referred to as the G model from now on) whose mean and standard deviation may be modulated by attention and/or masking.…”
Section: Statistical Modeling Of Response Errorsmentioning
confidence: 99%
“…In several studies, it was noted that a mixture of statistical models (e.g., combined Gaussian and Uniform distributions) provide a better account of data compared to a single one (e.g., Gaussian), even when the difference in the number of parameters is taken into account. Mixture models have been used in modeling VSTM [14,59,60,61], visual encoding [14,60], crowding [62,63], and masking [64,65]. An upshot of this approach is that it can provide a meaningful interpretation for the parameters of the model.…”
Section: Methodsmentioning
confidence: 99%