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Michael A. Cohen, Ken Nakayama, Talia Konkle, George Alvarez; Competition for working memory resources depends on the kind of stimuli being remembered. Journal of Vision 2011;11(11):1247. doi: https://doi.org/10.1167/11.11.1247.
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© ARVO (1962-2015); The Authors (2016-present)
The limits of visual working memory have been well established for simple colored shapes, where it is typically assumed that all stimuli compete equally for this limited memory resource. Here we examined whether different stimulus categories (faces, bodies, objects, scenes) draw equally on working memory resources or if the kind of stimuli to be remembered show more or less competition for memory storage.
Participants performed a change detection task in which four items were presented on the screen. Following a short delay, the display reappeared with a single item cued and observers indicated whether or not that item changed. Four items from the same category were presented (e.g. four scenes or four faces), or two items from two categories (e.g. two faces and two scenes). For each pair of categories, performance was compared between remembering four items from the same category and the mixed category trials.
Overall, we found a “mix effect”: performance with two categories was systematically higher than performance with only one category. Interestingly, the effect was graded: three different pairs of stimuli – Faces/Scenes, Bodies/Scenes, and Faces/Object – yielded a large mix effect (Cohen's D > 1.7), while other pairs – Faces/Bodies and Objects/Bodies – yielded a smaller mix effect (Cohen's D > 0.6). Only the Objects/Scenes pairing did not show an increase in performance in the mix condition (Cohen's D < .1, p = 0.84).
This pattern of results is generally consistent with the similarity of patterns of activation observed across the ventral visual cortex for these categories. These results demonstrate that the capacity of visual working memory depends on what is being remembered, and suggest that the amount of information that can be stored increases as a function of the independence of the underlying neural resources used to encode that information.
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