Using retrieval contingencies to understand memory integration and inference. - Yu, Wangjing; Duncan, Katherine D.; Schlichting, Margaret L. (Memory & Cognition, 2025)
Past work has yielded mixed insights into how people draw upon their memories to make new inferences. While some studies have shown memories can be combined during encoding to store never-experienced, inferential associations, others have emphasized a retrieval-based mechanism in which separate, high-quality memories are recombined as inferences are needed. We hypothesized that there might be important individual differences to consider when reconciling these seemingly disparate findings. We set out to quantify these differences by measuring contingencies in people's memory recall behaviour. In Experiment 1, we first compared the performance of three memory contingency metrics using simulations and data from a task known to induce dependency. In doing so, we developed a correction to remove biases associated with general memory performance to isolate the representational structure of memories, and we selected the highest-fidelity option – corrected dependency – for subsequent analyses. Experiment 2 tested the sensitivity of our chosen metric: We manipulated the similarity across experiences to encourage integration for half of the memories. Consistent with prior work, we found reliable recall dependency in the high similarity condition. Finally, in Experiment 3, we used memory dependencies to reveal individual differences in inference approaches in exploratory analyses: While "separators" relied upon high-fidelity individual memories to make speeded inferences, "integrators" drew inferences faster than separators, but their judgements were not sped by recalling constituent experience details. Together, these findings highlight the importance of considering individual differences in memory representations when characterizing the mechanisms underlying memory-based inference.