| Title: |
Double-decision response time models of recall and recognition support resource accounts of visual working memory |
| Authors: |
Garrett, Paul Michael; Lua, Anthony; Feuerriegel, Daniel; Little, Daniel R.; Smith, Philip L. |
| Publisher Information: |
Center for Open Science |
| Publication Year: |
2025 |
| Description: |
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 of 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 these correlations, particularly for drift rates at larger set sizes, implying that the tail responses represent meaningful low-precision memory traces rather than guesses. This finding is consistent with a variable precision or resource account of VWM and inconsistent with a slot model account of VWM. 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. |
| Document Type: |
other/unknown material |
| Language: |
unknown |
| DOI: |
10.31234/osf.io/uzrpa_v1 |
| Availability: |
https://doi.org/10.31234/osf.io/uzrpa_v1 |
| Rights: |
https://creativecommons.org/licenses/by/4.0/legalcode |
| Accession Number: |
edsbas.FF4BB004 |
| Database: |
BASE |