TY - JOUR
T1 - Identifying causal subsequent memory effects
AU - Halpern, David J.
AU - Tubridy, Shannon
AU - Davachi, Lila
AU - Gureckis, Todd M.
N1 - Funding Information:
We thank Hong Yu Wang, Camille Gasser, and Steven Mikal for helpful assistance with stimulus development, scanning, and data processing. We additionally thank Daniel Schonhaut, Noa Herz, John Sakon, Michael Kahana, Joseph Halpern, Cate Hartley, and Eero Simoncelli for helpful comments on previous drafts of this manuscript and Rich Shiffrin, Anthony Wagner, and two anonymous reviewers for their insightful critiques and suggestions during the review process. This work was supported by NSF grant DRL-1631436 and seed funds from the NYU Dean for Science.
Funding Information:
ACKNOWLEDGMENTS. We thank Hong Yu Wang, Camille Gasser, and Steven Mikal for helpful assistance with stimulus development, scanning, and data processing. We additionally thank Daniel Schonhaut, Noa Herz, John Sakon, Michael Kahana, Joseph Halpern, Cate Hartley, and Eero Simoncelli for helpful comments on previous drafts of this manuscript and Rich Shiffrin, Anthony Wagner, and two anonymous reviewers for their insightful critiques and suggestions during the review process. This work was supported by NSF grant DRL-1631436 and seed funds from the NYU Dean for Science.
Publisher Copyright:
© 2023 the Author(s).
PY - 2023/3/28
Y1 - 2023/3/28
N2 - 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.
AB - 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.
KW - causal inference
KW - encoding
KW - Long-term memory
KW - memorability
KW - neuroimaging
UR - http://www.scopus.com/inward/record.url?scp=85151043208&partnerID=8YFLogxK
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U2 - 10.1073/pnas.2120288120
DO - 10.1073/pnas.2120288120
M3 - Article
C2 - 36952384
AN - SCOPUS:85151043208
SN - 0027-8424
VL - 120
JO - Proceedings of the National Academy of Sciences of the United States of America
JF - Proceedings of the National Academy of Sciences of the United States of America
IS - 13
M1 - e2120288120
ER -