Bein O, Duncan K, Davachi L. Mnemonic prediction errors bias hippocampal states.
Nat Commun 2020;
11:3451. [PMID:
32651370 PMCID:
PMC7351776 DOI:
10.1038/s41467-020-17287-1]
[Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2019] [Accepted: 06/16/2020] [Indexed: 11/10/2022] Open
Abstract
When our experience violates our predictions, it is adaptive to upregulate encoding of novel information, while down-weighting retrieval of erroneous memory predictions to promote an updated representation of the world. We asked whether mnemonic prediction errors promote hippocampal encoding versus retrieval states, as marked by distinct network connectivity between hippocampal subfields. During fMRI scanning, participants were cued to internally retrieve well-learned complex room-images and were then presented with either an identical or a modified image (0-4 changes). In the left hemisphere, we find that CA1-entorhinal connectivity increases, and CA1-CA3 connectivity decreases, with the number of changes. Further, in the left CA1, the similarity between activity patterns during cued-retrieval of the learned room and during the image is lower when the image includes changes, consistent with a prediction error signal in CA1. Our findings provide a mechanism by which mnemonic prediction errors may drive memory updating—by biasing hippocampal states.
When our expectations are violated, it is adaptive to update our internal models to improve predictions in the future. Here, the authors show that during mnemonic violations, hippocampal networks are biased towards an encoding state and away from a retrieval state to potentially update these predictions.
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