Stochastic sampling provides a unifying account of working memory limits
Sebastian Schneegans, Robert T. Taylor, Paul M. Bays
This study uses a stochastic sampling framework to unify models of working memory limits, showing random variability in sample counts, not discrete/continuous nature, explains human performance.
Proceedings of the National Academy of Sciences · Aug 11, 2020Peer-reviewedNeuroscience