Priming effects on subsequent episodic memory: Testing attentional accounts

Abstract

Previous work has shown that priming improves subsequent episodic memory, i.e, memory for the context in which an item is presented is improved if that item has been seen previously. We previously attributed this effect of "Priming on Subsequent Episodic Memory" (PSEM) to a sharpening of the perceptual/conceptual representation of an item, which improves its associability with an (arbitrary) background context, by virtue of increasing prediction error (Greve et al, 2017). However, an alternative explanation is that priming reduces the attentional resources needed to process an item, leaving more residual resources to encode its context. We report four experiments that tested this alternative, resource-based hypothesis, based on the assumption that reducing the available attentional resources by a concurrent load would reduce the size of the PSEM. In no experiment did we find a significant interaction between attentional load and priming on mean memory performance, and nor did we find a consistent correlation across participants between priming and PSEM, failing to support the resource account. However, formal modelling revealed that a resource account is not, in fact, inconsistent with our data, by confirming that nonlinear (sigmoidal) resource-performance functions can reproduce any interaction with load, and, more strikingly, any pattern of correlation between priming and PSEM. This work reinforces not only the difficulty of refuting attentional resource accounts of memory encoding, but also questions the value of load manipulations more generally.

Share the code, not just the data: A case study of the reproducibility of articles published in the Journal of Memory and Language under the open data policy

“…This is because the failure may be driven by many factors that are external to the research question under investigation: differences in the population and/or language studied, the natural variability in the dependent variable, lab settings, equipment, and protocols can come together to lead to very different outcomes. Indeed, it is possible that when it comes to studying subtle and highly variable aspects of human (IR)REPRODUCIBILITY IN PSYCHOLOGY AND PSYCHOLINGUISTICS (IR)REPRODUCIBILITY IN PSYCHOLOGY AND PSYCHOLINGUISTICS (2020), Brandt et al (2020), Brewer et al (2021), Bristol and Rossano (2020), Brothers and Kuperberg (2021), Brysbaert (2019), Bürki et al (2020), Chan et al (2020), Chetail (2020), Collins et al (2020), Corps and Rabagliati (2020), Dıéez-Álamo et al (2020), Falandays et al (2020), Fellman et al (2020), Floccia et al (2020), Fox et al (2020), Fujita and Cunnings (2020), Gagné et al (2020), Garnham et al (2020), Günther, Nguyen, et al (2020), Günther, Petilli, et al (2020), Hesse and Benz (2020), Hollis (2020), Humphreys et al (2020), Hwang and Shin (2019), Isarida et al (2020), Jäger et al (2020), Johns et al (2020), Kaula and Henson (2020), Lauro et al (2020), Lelonkiewicz et al (2020), Li et al (2020), Liang et al (2021), McKinley and Benjamin (2020),…”