Dissociating models of visual working memory by reaction-time distribution analysis

Abstract

There have been heated debates on whether visual working memory (VWM) represents information in discrete-slots or a reservoir of flexible-resources. However, one key aspect of the models has gone unnoticed, the speed of processing when stored information in memory is assessed for accuracy. The present study evaluated contrasting predictions from the two models regarding the change detection decision times spent on the assessment of stored information by estimating the ex-Gaussian parameters from change detection RT distributions across different set sizes (2, 4, 6, or 8). The estimation showed that the Gaussian components μ and σ became larger as the set size increased from 2 to 4, but stayed constant as it reached 6 and 8, with an exponential component τ increasing at above-capacity set sizes. Moreover, we found that an individual's capacity limit correlates with the memory set size where the Gaussian μ reaches a plateau. These results indicate that the decision time for assessing in-memory items is constant regardless of memory set sizes whereas the time for the remaining not-in-memory items increases as the set size exceeds VWM storage capacity. The findings suggest that the discrete-slot model explains the observed RT distributions better than the flexible-resource model.