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The precision of visual working memory (WM) representations declines monotonically with increasing storage load. Two distinct models of WM capacity predict different shapes for this precision-by-set-size function. Flexible-resource models, which assert a continuous allocation of resources across an unlimited number of items, predict a monotonic decline in precision across a large range of set sizes. Conversely, discrete-resource models, which assert a relatively small item limit for WM storage, predict that precision will plateau once this item limit is exceeded. Recent work has demonstrated such a plateau in mnemonic precision. Moreover, the set size at which mnemonic precision reached asymptote has been strongly predicted by estimated item limits in WM. In the present work, we extend this evidence in three ways. First, we show that this empirical pattern generalizes beyond orientation memory to color memory. Second, we rule out encoding limits as the source of discrete limits by demonstrating equivalent performance across simultaneous and sequential presentations of the memoranda. Finally, we demonstrate that the analytic approach commonly used to estimate precision yields flawed parameter estimates when the range of stimulus space is narrowed (e.g., a 180º rather than a 360º orientation space) and typical numbers of observations are collected. Such errors in parameter estimation reconcile an apparent conflict between our findings and others based on different stimuli. These findings provide further support for discrete-resource models of WM capacity.

RETRACTED ARTICLE: The plateau in mnemonic resolution across large set sizes indicates discrete resource limits in visual working memory