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Transformative neural representations support long-term episodic memory

delete2021-10-08
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刘婧 cover
刘婧 (Jing Liu)
张会 (Hui Zhang)
T
Tao Yu
L
Liankun Ren
D
Duanyu Ni
Q
Qinhao Yang
B
Baoqing Lu
L
Liang Zhang
N
Nikolai Axmacher
G
Gui Xue *
DOI:10.1126/sciadv.abg9715delete
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Abstract

Abstract

En 中文
Memory is often conceived as a dynamic process that involves substantial transformations of mental representations. However, the neural mechanisms underlying these transformations and their role in memory formation and retrieval have only started to be elucidated. Combining intracranial EEG recordings with deep neural network models, we provide a detailed picture of the representational transformations from encoding to short-term memory maintenance and long-term memory retrieval that underlie successful episodic memory. We observed substantial representational transformations during encoding. Critically, more pronounced semantic representational formats predicted better subsequent long-term memory, and this effect was mediated by more consistent item-specific representations across encoding events. The representations were further transformed right after stimulus offset, and the representations during long-term memory retrieval were more similar to those during short-term maintenance than during encoding. Our results suggest that memory representations pass through multiple stages of transformations to achieve successful long-term memory formation and recall.
Keywords:
WORKING-MEMORY
PATTERN SIMILARITY
SEMANTIC REPRESENTATIONS
MAINTENANCE CONTRIBUTES
REINSTATEMENT
RETRIEVAL
HIPPOCAMPAL
INFORMATION
REPLAY
CONSOLIDATION
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Journal

Science Advances cover
Science Advances
IF:
12.5
Papers:
2.0W
Citations:
18.1W

Organization

B
Beijing Normal University
Scholars:
3.3W
Papers: 2.7W
Citations: 4.2W
C
Capital Medical University
Scholars:
5.3W
Papers: 3.3W
Citations: 3.2W
R
ruhr university bochum
Scholars:
2.3W
Papers: 1.9W
Citations: 14
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