P-2A.13

Forgone, but not forgotten: separate episodic memories underlie explicit reports and eye movements

Yul Kang, Queen Mary University of London, United Kingdom; Johannes Mahr, Harvard University, United States; Márton Nagy, Krisztina Andrási, Eötvös Loránd University, Hungary; Gergely Csibra, Central European University, Austria; Máté Lengyel, University of Cambridge, United Kingdom

Session:
Posters 2A Poster

Track:
Cognitive science

Location:
North Schools

Presentation Time:
Fri, 25 Aug, 13:00 - 15:00 United Kingdom Time

Abstract:
Episodic memories are thought to integrate multiple aspects of a past experience into a unified engram. A key prediction is that such integrated memories should drive behavior consistently across different response modalities (e.g., explicit/implicit). This however, has remained largely untested, as previous approaches couldn’t resolve the content of memories underlying implicit responses. Here we used ideal observer-based trial-by-trial/gaze-by-gaze analyses of explicit reports and spontaneous eye movements to reconstruct participants’ memories underlying different response modalities. We used a false memory paradigm, where human participants studied a sequence of object-location pairings, followed by suggestions (50% false). After participants judged the correctness of all suggestions, they recalled each object’s location while their gazes were recorded. Our analyses revealed that explicit recall reflected ‘conditioned memory’: the recalled location reflected only either the suggested or the original location, depending on whether the suggestion had been deemed correct. In contrast, eye movements did not show this effect, and reflected a combination of memories distinct from those underlying explicit recall. Challenging the notion of unified engrams, these results suggest the formation of multiple distinct memory traces of the same experience that are maintained independently, show different vulnerability to false suggestions, and control different response modalities.

Manuscript:
License:
Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 Unported License.
DOI:
10.32470/CCN.2023.1472-0
Publication:
2023 Conference on Cognitive Computational Neuroscience
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