Surprisingly inflexible: Statistically learned suppression of distractors generalizes across contexts

Abstract

The present study investigates the flexibility of statistically learned distractor suppression between different contexts. Participants performed the additional singleton task searching for a unique shape, while ignoring a uniquely colored distractor. Crucially, we created two contexts within the experiments, and each context was assigned its own high-probability distractor location, so that the location where the distractor was most likely to appear depended on the context. Experiment 1 signified context through the color of the background. In Experiment 2, we aimed to more strongly differentiate between the contexts using an auditory or visual cue to indicate the upcoming context. In Experiment 3, context determined the appropriate response ensuring that participants engaged the context in order to be able to perform the task. Across all experiments, participants learned to suppress both high-probability locations, even if they were not aware of these spatial regularities. However, these suppression effects occurred independent of context, as the pattern of suppression reflected a de-prioritization of both high-probability locations which did not change with the context. We employed Bayesian analyses to statistically quantify the absence of context-dependent suppression effects. We conclude that statistically learned distractor suppression is robust and generalizes across contexts.