Yu Wangjing, Duncan Katherine D, Schlichting Margaret L
Department of Psychology, University of Toronto, Toronto, Canada.
Department of Psychology, New York University, New York, NY, USA.
Mem Cognit. 2025 May 13. doi: 10.3758/s13421-025-01727-8.
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.
过去的研究对于人们如何利用记忆进行新的推理得出了复杂的见解。虽然一些研究表明,记忆可以在编码过程中进行组合,以存储从未经历过的推理关联,但另一些研究则强调了一种基于检索的机制,即在需要进行推理时,将单独的高质量记忆重新组合起来。我们假设,在调和这些看似不同的发现时,可能需要考虑重要的个体差异。我们着手通过测量人们记忆回忆行为中的偶然性来量化这些差异。在实验1中,我们首先使用模拟和来自一个已知会引发依赖性的任务的数据,比较了三种记忆偶然性指标的表现。在此过程中,我们开发了一种校正方法,以消除与一般记忆表现相关的偏差,从而分离出记忆的表征结构,并选择了保真度最高的选项——校正后的依赖性——用于后续分析。实验2测试了我们所选指标的敏感性:我们操纵了不同经历之间的相似度,以促使一半的记忆进行整合。与先前的研究一致,我们在高相似度条件下发现了可靠的回忆依赖性。最后,在实验3中,我们在探索性分析中使用记忆依赖性来揭示推理方法上的个体差异:“分离者”依靠高保真的个体记忆进行快速推理,而“整合者”比分离者推理得更快,但他们的判断并没有因为回忆构成经历的细节而加快。总之,这些发现凸显了在描述基于记忆的推理背后的机制时,考虑记忆表征中个体差异的重要性。