title: Working memory management and predicted utility.
abstract: Given the limited capacity of working memory (WM), its resources should be allocated strategically. One strategy is filtering, whereby access to WM is granted preferentially to items with the greatest utility. However, reallocation of WM resources might be required if the utility of maintained information subsequently declines. Here, we present behavioral, computational, and neuroimaging evidence that human participants track changes in the predicted utility of information in WM. First, participants demonstrated behavioral costs when the utility of items already maintained in WM declined and resources should be reallocated. An adapted Q-learning model indicated that these costs scaled with the historical utility of individual items. Finally, model-based neuroimaging demonstrated that frontal cortex tracked the utility of items to be maintained in WM, whereas ventral striatum tracked changes in the utility of items maintained in WM to the degree that these items are no longer useful. Our findings suggest that frontostriatal mechanisms track the utility of information in WM, and that these dynamics may predict delays in the removal of information from WM.
authors.affiliation: Cognitive, Linguistic & Psychological Sciences, Brown University, Providence RI, USA.
authors.forename: Christopher H
authors.initials: CH
authors.lastname: Chatham
authors.forename: David
authors.initials: D
authors.lastname: Badre
keywords: Q-learning; filtering; gating; predicted utility; working memory