Topic: limited memory

A key challenge in perception is to differentiate random noisy observations from structurally wrong beliefs when confronted with prediction errors. One should integrate out noise to improve precision, but simultaneously recognize when predictions are irrelevant due to environmental change. Bayesian inference prescribes a statistically optimal solution to this problem, but it is memory intensive and computationally complex, thus unlikely to be used continuously by humans.Here, we systematically investigated which hallmarks of Bayesian inference are present in previously published human response