Abstract
Previous studies have suggested that visual short-term memory (VSTM) has a storage limit of approximately 4 items. However, the type of high-threshold model (HTM) used to derive this estimate is based on a number of unattractive assumptions, and has been criticized in other experimental paradigms (e.g., visual search). Here we report findings from three experiments in which VSTM for colored stimuli was modelled using a signal detection theory (SDT) approach. In Experiments 1 and 2, two arrays composed of colored squares arranged on an imaginary circle were presented sequentially, each for 100 ms, with a 1500 ms ISI. The color of each square was randomly assigned from a palette of 9 highly discriminable colors. Observers were asked to report in a yes/no fashion whether there were any color differences between the first and second arrays, and to rate their confidence in their response on a 1–4 scale. In Experiment 1 only one color difference could occur (T = 1) while set size was varied (N = 2,4,6,8). In Experiment 2, set size was fixed (N = 8) while the number of stimuli which might change was varied (T = 1,2,3,4). Three general models were tested against the ROCs generated by the two experiments. In addition to the HTM, two SDT models were tried: one assuming summation of signals prior to a decision, the other using a max rule. Only the max model was shown to provide a good fit for the ROCs of both Experiments 1 and 2. A third experiment was performed in which observers were asked to directly report (via a color wheel) the color of a stimulus presented 1500 ms previously, from an array of varying set size (N = 2,4,6,8). Overall our results suggest observers encode stimuli independently in parallel, and that performance is limited by internal noise, which is a function of set size. The ‘4-item limit’ reported using HTMs of VSTM appears to be an artefact derived from asymptotic performance as a function of increasing noise as set size is increased.
PW is funded by the Rosamund Alcott Fellowship, California Institute of Technology. WJM is funded by a grant of the Swartz Foundation.