PT - JOURNAL ARTICLE AU - Michelle L. Eisenberg AU - Jeffrey M. Zacks AU - Shaney Flores TI - Dynamic Prediction During Perception of Everyday Events AID - 10.1101/348946 DP - 2018 Jan 01 TA - bioRxiv PG - 348946 4099 - http://biorxiv.org/content/early/2018/06/22/348946.short 4100 - http://biorxiv.org/content/early/2018/06/22/348946.full AB - The ability to predict what is going to happen in the near future is integral for daily functioning. Previous research suggests that predictability varies over time, with increases in prediction error at those moments that people perceive as boundaries between meaningful events. These moments also tend to be points of rapid change in the environment. Eye tracking provides a method for continuous measurement of prediction as participants watch a movie of an actor performing a series of actions. In two studies, we used eye tracking to study the time course of prediction around event boundaries. In both studies, viewers looked at objects that were about to be touched by the actor shortly before the objects were contacted, demonstrating predictive looking. However, this behavior was modulated by event boundaries: looks to to-be-contacted objects near event boundaries were less likely to be early and more likely to be late, compared to looks to objects contacted within events. This result is consistent with theories proposing that event segmentation results from transient increases in prediction error.Significance Statement The ability to predict what will happen in the near future is integral for adaptive functioning, and although there has been extensive research on predictive processing, the dynamics of prediction at the second by second level during the perception of naturalistic activity has never been explored. The current studies therefore describe results from a novel task, the Predictive Looking at Action Task (PLAT) that can be used to investigate the dynamics of predictive processing. Demonstrating the utility of this task to investigate predictive processing, this task was applied to study the predictions made by Event Segmentation Theory, which suggests that people experience event boundaries at times of change and unpredictability in the environment. The results of these studies are of interest to communities investigating the dynamic comprehension and segmentation of naturalistic events and to communities studying visual perception of naturalistic activity.