The number of objects determines visual working memory capacity allocation for complex items

We examined whether visual working memory (WM) capacity allocation is determined solely by complexity, with the number of objects being redundant, as suggested by flexible resource models. Participants performed the change detection task with random polygons as stimuli, while we monitored the contralateral delay activity (CDA), an electrophysiological marker whose amplitude rises as WM capacity load increases. In Experiment 1, we presented random polygons together with other complex items (e.g., shaded cubes and Chinese characters) and decreased the resolution with which random polygons need to be maintained in WM by introducing only between-category changes (e.g., polygon to cube). The results indicated that the polygon still consumed more WM capacity relative a simple object. In Experiment 2, we compared the WM maintenance of one whole polygon to two halves of a polygon, thus equating complexity but manipulating the number of items. Additionally, we compared the whole polygon to a single half of a polygon, equating the number of items but varying the complexity level. The results suggested that only the number of objects determined WM capacity allocation: the CDA amplitude was lower in the whole polygon condition relative to the two halves condition, even though both contained the same amount of information. Furthermore, the CDA was identical when comparing one whole polygon to one polygon half, even though these conditions differed in complexity. Experiment 3 extended these results by showing that two polygon-halves moving separately but then meeting and moving together, were gradually integrated to consume similar WM capacity as one polygon half. Interestingly, we also found an object benefit in accuracy, corroborating the important role of objects in WM. Our results demonstrate that WM capacity allocation is highly sensitive to objecthood, as suggested by discrete slot models. Meeting abstract presented at VSS 2015.