Abstract
Attentional capture is a well-studied phenomenon where task-irrelevant stimuli are erroneously selected for processing. While stimulus features that cause attentional capture have been extensively documented, the ability of the attentional system to attenuate the effects of capture remains largely unknown. In Experiment 1 (N=24), we identified three saccade metrics that were adjusted to limit processing of the irrelevant distractor. We recorded eye-movements during a visual search task in which a target was simultaneously presented with a distractor that was the same color as the target (similar distractor) or was a different color (dissimilar distractor). Applying a machine-learning algorithm (support vector machines) to within-subjects data, we found that first-saccades to dissimilar distractors had shorter saccade latencies, saccade amplitudes, and distractor fixation durations. This suggested that corrective mechanisms operate at multiple levels of processing, even as an erroneous saccade is being executed. In Experiment 2, we manipulated the distractor-target onset asynchrony (SOA; N=24) and found that the degree of saccade correction scaled with SOA. In Experiment 3, we varied target-distractor color similarity (N=24) and again found a scaling of correction, now based on feature similarity. Together these results demonstrated that the ability to initiate corrective mechanisms to limit distractor processing depended on the strength of evidence that the planned saccade was erroneous.
Meeting abstract presented at VSS 2014