Identifying Causal Subsequent Memory Effects

Over 40 years 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 a novel experimental design and analysis approach that allows us to statistically adjust for all 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 during an encoding period, and show that these behavioral measures of encoding quality do predict memory after adjustments, suggesting that it is possible to measure signals at the time of encoding that reflect causal mechanisms but that existing neuroimaging measures may not have the precision and specificity to do so.