Landscaping analyses of the ROC predictions of discrete-slots and signal-detection models of visual working memory

Abstract

A fundamental issue concerning visual working memory is whether its capacity limits are better characterized in terms of a limited number of discrete slots (DSs) or a limited amount of a shared continuous resource. Rouder et al. (2008) found that a mixed-attention, fixed-capacity, DS model provided the best explanation of behavior in a change detection task, outperforming alternative continuous signal detection theory (SDT) models. Here, we extend their analysis in two ways: first, with experiments aimed at better distinguishing between the predictions of the DS and SDT models, and second, using a model-based analysis technique called landscaping, in which the functional-form complexity of the models is taken into account. We find that the balance of evidence supports a DS account of behavior in change detection tasks but that the SDT model is best when the visual displays always consist of the same number of items. In our General Discussion section, we outline, but ultimately reject, a number of potential explanations for the observed pattern of results. We finish by describing future research that is needed to pinpoint the basis for this observed pattern of results.