Keshvari, S and van den Berg, R and Ma, WJ (2013) No evidence for an item limit in change detection. PLoS Comput Biol, 9. e1002927-.Full text not available from this repository.
Change detection is a classic paradigm that has been used for decades to argue that working memory can hold no more than a fixed number of items ("item-limit models"). Recent findings force us to consider the alternative view that working memory is limited by the precision in stimulus encoding, with mean precision decreasing with increasing set size ("continuous-resource models"). Most previous studies that used the change detection paradigm have ignored effects of limited encoding precision by using highly discriminable stimuli and only large changes. We conducted two change detection experiments (orientation and color) in which change magnitudes were drawn from a wide range, including small changes. In a rigorous comparison of five models, we found no evidence of an item limit. Instead, human change detection performance was best explained by a continuous-resource model in which encoding precision is variable across items and trials even at a given set size. This model accounts for comparison errors in a principled, probabilistic manner. Our findings sharply challenge the theoretical basis for most neural studies of working memory capacity.
|Uncontrolled Keywords:||Adult Bayes Theorem Computational Biology Female Humans Male Memory, Short-Term Models, Neurological Photic Stimulation Reproducibility of Results Task Performance and Analysis|
|Divisions:||Div F > Computational and Biological Learning|
|Depositing User:||Cron Job|
|Date Deposited:||09 Dec 2016 17:14|
|Last Modified:||24 Apr 2017 04:29|