The process by which multiple items within an object grouping are rapidly summarized along a given visual dimension into a single mean value (i.e., perceptual averaging) has increasingly been shown to interact dynamically with visual working memory (VWM). Commonly, this interaction is studied with respect to the influence of perceptual averaging over VWM, but it is also the case that VWM can support perceptual averaging. Here, we argue that, in the presence of memory-matching elements, VWM exerts an obligatory influence over perceptual averaging even when it is detrimental to do so. Over four experiments, we tested our hypothesis by having individuals perform a mean orientation estimation task while concurrently maintaining a colored object in VWM. We anticipated that mean orientation reports would be attracted to the local mean of memory-matching items if such items are prioritized in perceptual average judgments. This was indeed the case as we observed a persistent bias in mean orientation judgments toward the subset mean of items matching the VWM item color, despite color being entirely irrelevant to the mean orientation task. Our results thus highlight a goal-invariant influence of VWM over perceptual averaging, which we attribute to amplification through memory-driven selection.
Public Significance StatementCurrent understanding of the interaction between perceptual averaging and visual working memory (VWM) has largely centered on the influence of the former over the latter, with much less consideration of a potential bidirectional relationship between these two systems. In this study, we show that not only does VWM alter perceptual averaging judgments but that it also does so automatically (i.e., even when it is costly to do so). More broadly, this work provides confirmatory support to the idea that the amplification of items within object ensembles is set by an underlying priority map, which guides selective attention on the basis of physical salience, top-down goals, emotional valence, and reward history.