Retrieval from long-term memory reduces working memory representations for visual features and their bindings

The ability to remember feature bindings is an important measure of the ability to maintain objects in working memory (WM). In this study, we investigated whether both object- and feature-based representations are maintained in WM. Specifically, we tested the hypotheses that retaining a greater number of feature representations (i.e., both as individual features and bound representations) results in a more robust representation of individual features than of feature bindings, and that retrieving information from long-term memory (LTM) into WM would cause a greater disruption to feature bindings. In four experiments, we examined the effects of retrieving a word from LTM on shape and color-shape binding change detection performance. We found that binding changes were more difficult to detect than individual-feature changes overall, but that the cost of retrieving a word from LTM was the same for both individual-feature and binding changes.