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Episodic events are flexibility encoded in both integrated and separated neural representations

Liu, Zhenghao LU ; Johansson, Mikael LU orcid and Bramao, Ines LU orcid (2025)
Abstract
This study investigates how the brain encodes episodic events to support diverse memory functions. Thirty-six participants viewed movies simulating real-life interactions while EEG was recorded. They first watched movies featuring two characters (AB), followed by scenes where one original character interacted with a new one (BC). Memory was assessed for direct (AB and BC), indirect (AC) associations, and source memory about whether two characters had appeared together. Source memory was more accurate when participants correctly inferred indirect associations. Time-resolved representational similarity analysis (RSA) of EEG data revealed both neural pattern similarities and dissimilarities during AB and BC encoding. Pattern similarities,... (More)
This study investigates how the brain encodes episodic events to support diverse memory functions. Thirty-six participants viewed movies simulating real-life interactions while EEG was recorded. They first watched movies featuring two characters (AB), followed by scenes where one original character interacted with a new one (BC). Memory was assessed for direct (AB and BC), indirect (AC) associations, and source memory about whether two characters had appeared together. Source memory was more accurate when participants correctly inferred indirect associations. Time-resolved representational similarity analysis (RSA) of EEG data revealed both neural pattern similarities and dissimilarities during AB and BC encoding. Pattern similarities, indicating memory integration across episodes, predicted successful indirect associations. Conversely, dissimilarities predicted accurate source memory, indicating the preservation of distinct memory traces. These findings suggest that episodic events are flexibly encoded through both integrated and segregated neural representations, enabling the brain to support multiple memory functions depending on task demands. (Less)
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author
; and
organization
publishing date
type
Working paper/Preprint
publication status
published
subject
publisher
bioRxiv
DOI
10.1101/2025.04.30.651466
language
English
LU publication?
yes
id
908261f0-e6c4-4921-9b94-d8e85aafd20e
date added to LUP
2025-05-07 16:45:37
date last changed
2025-05-08 15:22:02
@misc{908261f0-e6c4-4921-9b94-d8e85aafd20e,
  abstract     = {{This study investigates how the brain encodes episodic events to support diverse memory functions. Thirty-six participants viewed movies simulating real-life interactions while EEG was recorded. They first watched movies featuring two characters (AB), followed by scenes where one original character interacted with a new one (BC). Memory was assessed for direct (AB and BC), indirect (AC) associations, and source memory about whether two characters had appeared together. Source memory was more accurate when participants correctly inferred indirect associations. Time-resolved representational similarity analysis (RSA) of EEG data revealed both neural pattern similarities and dissimilarities during AB and BC encoding. Pattern similarities, indicating memory integration across episodes, predicted successful indirect associations. Conversely, dissimilarities predicted accurate source memory, indicating the preservation of distinct memory traces. These findings suggest that episodic events are flexibly encoded through both integrated and segregated neural representations, enabling the brain to support multiple memory functions depending on task demands.}},
  author       = {{Liu, Zhenghao and Johansson, Mikael and Bramao, Ines}},
  language     = {{eng}},
  month        = {{05}},
  note         = {{Preprint}},
  publisher    = {{bioRxiv}},
  title        = {{Episodic events are flexibility encoded in both integrated and separated neural representations}},
  url          = {{http://dx.doi.org/10.1101/2025.04.30.651466}},
  doi          = {{10.1101/2025.04.30.651466}},
  year         = {{2025}},
}