Probabilistic rejection templates in visual working memory
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Description: Our interactions with the visual world are guided by attention and visual working memory. Things that we look for and those we ignore are stored as templates that reflect our goals and the tasks at hand. The nature of such templates has been widely debated. A recent proposal is that these templates can most straightforwardly be thought of as probabilistic representations of task-relevant features. We assessed observers’ representations by measuring the slowing of visual search when distractor templates unexpectedly match the target. To provide a strong test of the templates’ probabilistic nature, distractor stimuli were heterogeneous, randomly drawn on each trial from a bimodal probability distribution. Using two targets on each trial, we tested whether observers encode the full distribution, only one peak of it, or the average of the two peaks. Search was slower when the two targets corresponded to the two modes of previous distractor distributions than when one target was at one of the modes and another between the modes or outside the distribution range. Furthermore, targets on the modes were reported later than targets between the modes that, in turn, were reported later than targets outside this range. These results show that observers represent both distribution modes using templates based on probability distributions rather than single features or simple summary statistics. Our findings indicate that visual working memory templates guiding attention are probabilistic and dynamically adapt to task requirements, reflecting the probabilistic nature of the input.