Toward a theory of variability discrimination: finding differences.

We sketch the outlines of a theory of variability discrimination that aggregates localized differences to mediate variability discrimination. This Finding Differences Model was compared to a Positional Entropy Model across four different data sets. Although the two models provide strong and similar fits across three of the data sets, only the Finding Differences Model is applicable to investigations involving multidimensional variability. Furthermore, the Finding Differences Model is based on an activation map that has been shown to have utility for visual search tasks, thus establishing its generality across task domains.