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Identifying causal subsequent memory effects

Over 40 y of accumulated research has detailed associations between neuroimaging signals measured during a memory encoding task and later memory performance, across a variety of brain regions, measurement tools, statistical approaches, and behavioral tasks. But the interpretation of these subsequent...

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Autores principales: Halpern, David J., Tubridy, Shannon, Davachi, Lila, Gureckis, Todd M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10068819/
https://www.ncbi.nlm.nih.gov/pubmed/36952384
http://dx.doi.org/10.1073/pnas.2120288120
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author Halpern, David J.
Tubridy, Shannon
Davachi, Lila
Gureckis, Todd M.
author_facet Halpern, David J.
Tubridy, Shannon
Davachi, Lila
Gureckis, Todd M.
author_sort Halpern, David J.
collection PubMed
description Over 40 y of accumulated research has detailed associations between neuroimaging signals measured during a memory encoding task and later memory performance, across a variety of brain regions, measurement tools, statistical approaches, and behavioral tasks. But the interpretation of these subsequent memory effects (SMEs) remains unclear: if the identified signals reflect cognitive and neural mechanisms of memory encoding, then the underlying neural activity must be causally related to future memory. However, almost all previous SME analyses do not control for potential confounders of this causal interpretation, such as serial position and item effects. We collect a large fMRI dataset and use an experimental design and analysis approach that allows us to statistically adjust for nearly all known exogenous confounding variables. We find that, using standard approaches without adjustment, we replicate several univariate and multivariate subsequent memory effects and are able to predict memory performance across people. However, we are unable to identify any signal that reliably predicts subsequent memory after adjusting for confounding variables, bringing into doubt the causal status of these effects. We apply the same approach to subjects’ judgments of learning collected following an encoding period and show that these behavioral measures of mnemonic status do predict memory after adjustments, suggesting that it is possible to measure signals near the time of encoding that reflect causal mechanisms but that existing neuroimaging measures, at least in our data, may not have the precision and specificity to do so.
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spelling pubmed-100688192023-09-23 Identifying causal subsequent memory effects Halpern, David J. Tubridy, Shannon Davachi, Lila Gureckis, Todd M. Proc Natl Acad Sci U S A Biological Sciences Over 40 y of accumulated research has detailed associations between neuroimaging signals measured during a memory encoding task and later memory performance, across a variety of brain regions, measurement tools, statistical approaches, and behavioral tasks. But the interpretation of these subsequent memory effects (SMEs) remains unclear: if the identified signals reflect cognitive and neural mechanisms of memory encoding, then the underlying neural activity must be causally related to future memory. However, almost all previous SME analyses do not control for potential confounders of this causal interpretation, such as serial position and item effects. We collect a large fMRI dataset and use an experimental design and analysis approach that allows us to statistically adjust for nearly all known exogenous confounding variables. We find that, using standard approaches without adjustment, we replicate several univariate and multivariate subsequent memory effects and are able to predict memory performance across people. However, we are unable to identify any signal that reliably predicts subsequent memory after adjusting for confounding variables, bringing into doubt the causal status of these effects. We apply the same approach to subjects’ judgments of learning collected following an encoding period and show that these behavioral measures of mnemonic status do predict memory after adjustments, suggesting that it is possible to measure signals near the time of encoding that reflect causal mechanisms but that existing neuroimaging measures, at least in our data, may not have the precision and specificity to do so. National Academy of Sciences 2023-03-23 2023-03-28 /pmc/articles/PMC10068819/ /pubmed/36952384 http://dx.doi.org/10.1073/pnas.2120288120 Text en Copyright © 2023 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Biological Sciences
Halpern, David J.
Tubridy, Shannon
Davachi, Lila
Gureckis, Todd M.
Identifying causal subsequent memory effects
title Identifying causal subsequent memory effects
title_full Identifying causal subsequent memory effects
title_fullStr Identifying causal subsequent memory effects
title_full_unstemmed Identifying causal subsequent memory effects
title_short Identifying causal subsequent memory effects
title_sort identifying causal subsequent memory effects
topic Biological Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10068819/
https://www.ncbi.nlm.nih.gov/pubmed/36952384
http://dx.doi.org/10.1073/pnas.2120288120
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