Double-decision Response Time Models of Recall and Recognition Support Resource Accounts of Visual Working Memory

We use response time decision models to determine whether visual working memory (VWM) is best described by a fixed-capacity 'slot' model or a continuously allocated 'resource' model. We used a double-decision paradigm that combined continuous-outcome recall and two-choice recognition to characterize performance in a VWM task. Participants viewed one to six colored items, recalled the color of a cued target using a color wheel, and then identified the target color from two options in a recognition task. We used continuous-outcome and two-choice EZ diffusion models to analyze the speed and accuracy of the two decisions. The models provided estimates of the latent cognitive parameters, drift rate and boundary separation, with the former providing measures of the memory strengths in the two decisions. We found significant correlations in both drift rate and boundary separation for the two decisions, indicating that continuous recall and two-choice recognition tasks engage similar memory and decision processes. Removing responses within the highly inaccurate 'heavy tails' of the recall distribution reduced, rather than increased, drift rate correlations - especially in the six item condition - implying that the heavy tails of the response distribution represent meaningful low-precision memory traces rather than guesses. Simulations showed that only a small fraction of the heavy tailed memory trace could be accounted for by swap errors. Our results are consistent with variable precision and resource accounts of VWM and inconsistent with slot-based accounts. Our findings underscore the value of joint modeling response time and accuracy data, and highlight the utility of double-decision tasks in clarifying theoretical accounts of memory processes.