Data from: A resource-rational theory of set size effects in human visual working memory - Van den Berg, Ronald; Ma, Wei Ji (Dryad, 2018)
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.
Experimental data and Matlab codeThis 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.VandenBerg_Ma_2018_data_and_code.zip