Department of Psychology, Columbia University.
Baycrest Health Sciences, Rotman Research Institute, Toronto, Canada.
Psychol Sci. 2024 Oct;35(10):1178-1199. doi: 10.1177/09567976241256617. Epub 2024 Aug 7.
Many experiences unfold predictably over time. Memory for these temporal regularities enables anticipation of events multiple steps into the future. Because temporally predictable events repeat over days, weeks, and years, we must maintain-and potentially transform-memories of temporal structure to support adaptive behavior. We explored how individuals build durable models of temporal regularities to guide multistep anticipation. Healthy young adults (Experiment 1: = 99, age range = 18-40 years; Experiment 2: = 204, age range = 19-40 years) learned sequences of scene images that were predictable at the category level and contained incidental perceptual details. Individuals then anticipated upcoming scene categories multiple steps into the future, immediately and at a delay. Consolidation increased the efficiency of anticipation, particularly for events further in the future, but diminished access to perceptual features. Further, maintaining a link-based model of the sequence after consolidation improved anticipation accuracy. Consolidation may therefore promote efficient and durable models of temporal structure, thus facilitating anticipation of future events.
许多经验随着时间的推移而可预测地展开。对这些时间规律的记忆使我们能够预测未来多步的事件。由于时间上可预测的事件会在几天、几周和几年内重复发生,我们必须维持——并有可能改变——时间结构的记忆,以支持适应性行为。我们探讨了个体如何构建持久的时间规律模型来指导多步预测。健康的年轻成年人(实验 1:=99,年龄范围=18-40 岁;实验 2:=204,年龄范围=19-40 岁)学习了场景图像序列,这些序列在类别级别上是可预测的,并且包含偶然的感知细节。然后,个体立即和延迟地预测未来多步的场景类别。巩固提高了预测的效率,特别是对于更远的未来事件,但削弱了对感知特征的访问。此外,在巩固后保持序列的基于链接的模型可以提高预测准确性。因此,巩固可能会促进时间结构的高效和持久模型,从而促进对未来事件的预测。