Data from: A resource-rational theory of set size effects in human visual working memory
Van den Berg, Ronald, Uppsala University
Ma, Wei Ji, New York University
Publication date: August 16, 2018
Publisher: Dryad
https://doi.org/10.5061/dryad.nf5dr6c
Van den Berg, Ronald; Ma, Wei Ji (2018), Data from: A resource-rational theory of set size effects in human visual working memory, Dryad, Dataset, https://doi.org/10.5061/dryad.nf5dr6c
Encoding precision in visual working memory decreases with the number of encoded items. Here, we propose a normative theory for such set size effects: the brain minimizes a weighted sum of an error-based behavioral cost and a neural encoding cost. We construct a model from this theory and find that it predicts set size effects. Notably, these effects are mediated by probing probability, which aligns with previous empirical findings. The model accounts well for effects of both set size and probing probability on encoding precision in nine delayed-estimation experiments. Moreover, we find support for the prediction that the total amount of invested resource can vary non-monotonically with set size. Finally, we show that it is sometimes optimal to encode only a subset or even none of the relevant items in a task. Our findings raise the possibility that cognitive “limitations” arise from rational cost minimization rather than from constraints.
This zip file contains the data of experiments E1-E7 and Matlab code to fit the resource-rational model to a dataset and to create figures 2D, 2E, 3A, and 6 from the paper.
This dataset is supplement to https://doi.org/10.7554/elife.34963