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Poster D47

Temporal Order Memory in Naturalistic Events Is Influenced by Semantic Knowledge and Hierarchical Event Structure

Poster Session D - Monday, April 15, 2024, 8:00 – 10:00 am EDT, Sheraton Hall ABC

Yining Ding1 (, Devon R. Alperin1, Jeffrey M. Zacks1; 1Washington University in St. Louis

Previous studies on temporal order memory (TOM) using discrete pictorial stimuli showed that people are sometimes better at remembering the temporal order of items occurring within the same perceptual event than items spanning across a perceptual boundary (Heusser et al., 2018, JEP:LMC), but that the opposite can also occur if supporting contextual cues are present during test (Wen & Egner, 2022, Cognition). However, it is hard to generalize this result to naturalistic events without considering how semantic knowledge and hierarchical event structure may support the encoding and retrieval of temporal order information. To investigate these possibilities, we created hierarchically organized narrative stimuli describing everyday events, with semantic order constraints among events either on the coarse-level or on the fine-level. We found that participants could use semantic order constraints at either level to improve TOM. This led to better across-event TOM when coarse-level semantic constraints were provided, but better within-event TOM when fine-level semantic constraints were provided. In addition, when participants could not leverage semantic order constraints, they were more confident about temporal order across events than within events, independent of accuracy. Their distance rating of event pairs was inflated when the two events spanned across an event boundary. Finally, in serial recall, participants frequently chunked their recall based on coarse-level event membership. These results suggested that the role event boundaries play in shaping temporal order memory task performance depends on people’s ability to use information other than episodic memory.

Topic Area: LONG-TERM MEMORY: Episodic


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April 13–16  |  2024