When "capacity" changes with set size: Ensemble representations support the detection of across-category changes in visual working memory.

Abstract

Is there a fixed limit on how many objects we can hold actively in mind? Generally, researchers have found participants are worse at remembering a small number of objects if those objects are more complex, suggesting a limited resource rather than a fixed number of objects best explains working memory performance. However, some evidence has suggested that stimulus similarity better accounts for these effects and that, after accounting for such similarity, the data support a slot-based fixed item limit for working memory. Much of the evidence used to support the latter claim relies on working memory displays containing different categories of items. It has been found that, for large, across-category changes, performance does not differ for different kinds of complex stimuli. However, many of these studies fail to adequately control for the potential use of ensemble information in discriminating such large changes. Here, we sought to identify how much ensemble representations may explain performance across these tasks. In Experiment 1, we observed that, as set size increased from four to 12 items, capacity estimates for across-category changes increased linearly as well, providing evidence against the claim of a fixed capacity. In Experiment 2, we controlled for stimulus complexity and similarity but varied the utility of ensemble representations for the change-detection task. We observed significantly greater capacity when ensemble information could be used. Altogether, these results are contrary to a slot-like, fixed-object constraint on working memory capacity and consistent with object complexity and ensemble representations strongly affecting working memory performance.