Pupil sizes scale with attentional load and task experience in a multiple object tracking task

Abstract

Previous studies have related changes in attentional load to pupil size modulations. However, studies relating changes in attentional load and task experience on a finer scale to pupil size modulations are scarce. Here, we investigated how these changes affect pupil sizes. To manipulate attentional load, participants covertly tracked between zero and five objects among several randomly moving objects on a computer screen. To investigate effects of task experience, the experiment was conducted on three consecutive days. We found that pupil sizes increased with each increment in attentional load. Across days, we found systematic pupil size reductions. We compared the model fit for predicting pupil size modulations using attentional load, task experience, and task performance as predictors. We found that a model which included attentional load and task experience as predictors had the best model fit while adding performance as a predictor to this model reduced the overall model fit. Overall, results suggest that pupillometry provides a viable metric for precisely assessing attentional load and task experience in visuospatial tasks.This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.