Causality and continuity close the gaps in event representations
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Updated: Dec 6, 2025

Author Spotlight: Unlocking New Insights in fNIRS Studies - A Novel Framework for Inter-Brain Synchrony Analysis
Published on: October 6, 2023
Jonathan F Kominsky1, Lewis Baker2, Frank C Keil3
1Department of Psychology, Rutgers University, 101 Warren St. Rm. 301, Newark, NJ, 07102, USA. jonathan.kominsky@rutgers.edu.
Abstract:
Imagine you see a video of someone pulling back their leg to kick a soccer ball, and then a soccer ball soaring toward a goal. You would likely infer that these scenes are two parts of the same event, and this inference would likely cause you to remember having seen the moment the person kicked the soccer ball, even if that information was never actually presented (Strickland & Keil, 2011, Cognition, 121[3], 409-415). What cues trigger people to "fill in" causal events from incomplete information? Is it due to the experience they have had with soccer balls being kicked toward goals? Is it the visual similarity of the object in both halves of the video? Or is it the mere spatiotemporal continuity of the event? In three experiments, we tested these different potential mechanisms underlying the "filling-in" effect. Experiment 1 showed that filling in occurs equally in familiar and unfamiliar contexts, indicating that familiarity with specific event schemas is unnecessary to trigger false memory. Experiment 2 showed that the visible continuation of a launched object's trajectory is all that is required to trigger filling in, regardless of other occurrences in the second half of the scene. Finally, Experiment 3 found that, using naturalistic videos, this filling-in effect is more heavily affected if the object's trajectory is discontinuous in space/time compared with if the object undergoes a noticeable transformation. Together, these findings indicate that the spontaneous formation of causal event representations is driven by object representation systems that prioritize spatiotemporal information over other object features.
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