Post-encoding Reactivation Is Related to Learning of Episodes in Humans

© 2022 Massachusetts Institute of Technology..

Prior animal and human studies have shown that post-encoding reinstatement plays an important role in organizing the temporal sequence of unfolding episodes in memory. Here, we investigated whether post-encoding reinstatement serves to promote the encoding of "one-shot" episodic learning beyond the temporal structure in humans. In Experiment 1, participants encoded sequences of pictures depicting unique and meaningful episodic-like events. We used representational similarity analysis on scalp EEG recordings during encoding and found evidence of rapid picture-elicited EEG pattern reinstatement at episodic offset (around 500 msec post-episode). Memory reinstatement was not observed between successive elements within an episode, and the degree of memory reinstatement at episodic offset predicted later recall for that episode. In Experiment 2, participants encoded a shuffled version of the picture sequences from Experiment 1, rendering each episode meaningless to the participant but temporally structured as in Experiment 1, and we found no evidence of memory reinstatement at episodic offset. These results suggest that post-encoding memory reinstatement is akin to the rapid formation of unique and meaningful episodes that unfold over time.

Medienart:

E-Artikel

Erscheinungsjahr:

2022

Erschienen:

2022

Enthalten in:

Zur Gesamtaufnahme - volume:35

Enthalten in:

Journal of cognitive neuroscience - 35(2022), 1 vom: 01. Dez., Seite 74-89

Sprache:

Englisch

Beteiligte Personen:

Wu, Xiongbo [VerfasserIn]
Viñals, Xavier [VerfasserIn]
Ben-Yakov, Aya [VerfasserIn]
Staresina, Bernhard P [VerfasserIn]
Fuentemilla, Lluís [VerfasserIn]

Links:

Volltext

Themen:

Journal Article
Research Support, Non-U.S. Gov't

Anmerkungen:

Date Completed 05.12.2022

Date Revised 28.02.2023

published: Print

Citation Status MEDLINE

doi:

10.1162/jocn_a_01934

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM34820566X