.png){kind=icon}
.png){kind=icon}
Return
EEG decoders track memory dynamics
.png){kind=icon}
OA
AI
DOI：10.1038/s41467-024-46926-0.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Encoding- and retrieval-related neural activity jointly determine mnemonic success. We ask whether electroencephalographic activity can reliably predict encoding and retrieval success on individual trials. Each of 98 participants performed a delayed recall task on 576 lists across 24 experimental sessions. Logistic regression classifiers trained on spectral features measured immediately preceding spoken recall of individual words successfully predict whether or not those words belonged to the target list. Classifiers trained on features measured during word encoding also reliably predict whether those words will be subsequently recalled and further predict the temporal and semantic organization of the recalled items. These findings link neural variability predictive of successful memory with item-to-context binding, a key cognitive process thought to underlie episodic memory function. Successful memorization could be decoded from brain activity. Here the authors decode human memory success from EEG recordings, suggesting memory is linked to context.
Keywords:
THETA OSCILLATIONS
RETRIEVAL
PREDICT
GAMMA
CONTEXT
TESTS
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
15.7
Papers:
9.2W
Citations:
91.2W