Color distribution learning modulates saccade endpoints: a study of the global effect

In visual search, attention is affected by the features of targets and distractors encountered in preceding trials. Furthermore, the visual system can encode surprisingly detailed information about the distribution of these features. Notably, such feature distribution learning has been demonstrated in visual search tasks where observers learn the distribution that distractors from consecutive trials are drawn from. Finding a target on test trials depends on the difference in feature space between current target features and distractor distributions on preceding trials. Response times were slowed if the target feature was drawn from the previous distractor distribution and reflected the shape of the distribution. The present study assessed the impact of feature distribution learning on saccade endpoints. Participants performed a visual search task with distractors drawn from either a Gaussian or uniform color distribution. On a subsequent test trial, they had to make a saccade to a target with a distractor presented in close spatial proximity. We expected the endpoint of the first saccade to land in between the target and the distractor, a phenomenon known as the global effect. The deviation of the saccade endpoints as a function of the difference between the current target color and the distractor distribution in preceding trials was analyzed. Our findings reveal that endpoints deviated more toward the distractor when the target color was within the previous distractor's color distribution. The precise shape of the previous distractor's color distribution (uniform or Gaussian) had no impact on the endpoint deviation. Overall, our results suggest that previous distractor characteristics affect saccade endpoints, showing how feature distribution learning impacts motor behavior and visual selection.