Schematic information influences memory and generalisation behaviour for schema-relevant and -irrelevant information

Abstract

Schemas modulate memory performance for schema-congruent and -incongruent information. However, it is typically assumed they do not influence behaviour for information irrelevant to themselves. We assessed memory and generalisation behaviour for information related to an underlying pattern, where a schema could be extracted (schema-relevant), and information that was unrelated and therefore irrelevant to the extracted schema (schema-irrelevant). Using precision measures of long-term memory, where participants learnt associations between words and locations around a circle, we assessed memory and generalisation for schema-relevant and -irrelevant information. Words belonged to two semantic categories: human-made and natural. For one category, word-locations were clustered around one point on the circle (clustered condition), while the other category had word-locations randomly distributed (non-clustered condition). The presence of an underlying pattern in the clustered condition allows for the extraction of a schema that can support both memory and generalisation. At test, participants were presented with old (memory) and new (generalisation) words, requiring them to identify a remembered location or make a best guess. The presence of the clustered pattern modulated memory and generalisation. In the clustered condition, participants placed old and new words in locations consistent with the underlying pattern. In contrast, for the non-clustered condition, participants were less likely to place old and new non-clustered words in locations consistent with the clustered condition. We therefore provide evidence that the presence of schematic information modulates memory and generalisation for schema-relevant and -irrelevant information. Our results highlight the need to carefully construct appropriate schema-irrelevant control conditions such that behaviour in these conditions is not modulated by the presence of a schema. Theoretically, models of schema processing need to account for how the presence of schematic information can have consequences for information that is technically irrelevant to itself.

A registered report testing the effect of sleep on Deese-Roediger-McDermott false memory: greater lure and veridical recall but fewer intrusions after sleep

“…Some have argued that generalization, like gist extraction, is selectively facilitated by sleep consolidation ( [59], but see also [60,61]). However, retrievalbased models of generalization would show sleep benefits on generalization only if sleep also strengthened the individual memories on which the generalization operated [62,63]. Given these theoretical discrepancies, a feature of our planned experiment was to assess the effect of sleep versus wake on both studied words and critical lures, although our focus is on the latter given the critical lures have been the primary focus of previous DRM studies reporting sleep effects.…”

A registered report testing the effect of sleep on DRM false memory: Greater lure and veridical recall but fewer intrusions after sleep

“…Some have argued that generalisation, like gist extraction, is selectively facilitated by sleep consolidation (Nieuwenhuis et al, 2013, but see also Mirković & Gaskell, 2016;Tamminen et al, 2012). However, retrieval-based models of generalisation would show sleep benefits on generalisation only if sleep also strengthened the individual memories on which the generalisation operated (Cockcroft et al, 2022;Kumaran & McClelland, 2012). Given these theoretical discrepancies, a feature of our planned experiment was to assess the effect of sleep versus wake on both studied words and critical lures, although our focus is on the latter given the critical lures have been the primary focus of previous DRM studies reporting sleep effects.…”

Précis of Berens, Richards, and Horner (2020): Dissociating memory accessibility and precision in forgetting

“…If you know where the apple trees are located in a forest, you might be able to use this knowledge to make an accurate prediction about where a new apple tree might be located. In a series of four new preregistered experiments (both in-person and online), we used a similar design to Berens et al (2020) but embedded 'novel' words at retrieval (Cockcroft et al, 2021). These words weren't seen at encoding but did belong to the same semantic categories as the clustered and non-clustered condition.…”