Predicting the Allocation of Attention: Using contextual guidance of eye movements to examine the distribution of attention

Abstract

Eye movements are often taken as a marker of where attention is allocated, but it is possible that the attentional window can be either tightly or broadly focused around the fixation point. Using target objects whose location could either be strongly predicted by scene context (High Certainty) or not (Low Certainty), we examined how attention was initially distributed across a scene image during search. To do so, an unexpected distractor object suddenly appeared either in the relevant or irrelevant scene region for each target type. Distractors will be more disruptive where attention is allocated. We found that for High Certainty targets, the distractors were fixated significantly more often when they appeared in relevant than irrelevant regions, but there was no such difference for Low Certainty targets. This finding demonstrated differential patterns of attentional distribution around the fixation point based on the predicted location of target objects within a scene.