Literature DB >> 32147702

Neural Patterns are More Similar across Individuals during Successful Memory Encoding than during Failed Memory Encoding.

Griffin E Koch1,2,3, John P Paulus1,2, Marc N Coutanche1,2,3,4.   

Abstract

After experiencing the same episode, some people can recall certain details about it, whereas others cannot. We investigate how common (intersubject) neural patterns during memory encoding influence whether an episode will be subsequently remembered, and how divergence from a common organization is associated with encoding failure. Using functional magnetic resonance imaging with intersubject multivariate analyses, we measured brain activity as people viewed episodes within wildlife videos and then assessed their memory for these episodes. During encoding, greater neural similarity was observed between the people who later remembered an episode (compared with those who did not) within the regions of the declarative memory network (hippocampus, posterior medial cortex [PMC], and dorsal Default Mode Network [dDMN]). The intersubject similarity of the PMC and dDMN was episode-specific. Hippocampal encoding patterns were also more similar between subjects for memory success that was defined after one day, compared with immediately after retrieval. The neural encoding patterns were sufficiently robust and generalizable to train machine learning classifiers to predict future recall success in held-out subjects, and a subset of decodable regions formed a network of shared classifier predictions of subsequent memory success. This work suggests that common neural patterns reflect successful, rather than unsuccessful, encoding across individuals.
© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.

Entities:  

Keywords:  MVPA; encoding; episodic memory; hippocampus; recall

Mesh:

Year:  2020        PMID: 32147702      PMCID: PMC7264691          DOI: 10.1093/cercor/bhaa003

Source DB:  PubMed          Journal:  Cereb Cortex        ISSN: 1047-3211            Impact factor:   5.357


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