Poskanzer Craig, Tarder-Stoll Hannah, Javid Raheema, Spolaore Edoardo, Aly Mariam
Department of Psychology, Columbia University, New York, NY, USA.
Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada.
Open Mind (Camb). 2025 Jul 26;9:959-991. doi: 10.1162/opmi.a.15. eCollection 2025.
Forming memories requires a focus on the external world; retrieving memories requires attention to our internal world. Computational models propose that the hippocampus resolves the tension between encoding and retrieval by alternating between states that prioritize one over the other. We asked whether the success of a retrieval state affects the success of an encoding state, when both are measured in behavior. Across 3 Experiments ( = 197), we operationalized retrieval as the use of memories to make predictions about the future, and tested whether successful (vs. unsuccessful) prediction affected the likelihood of successful encoding. Participants viewed a series of scene categories that contained structure (e.g., beaches are followed by castles), which enabled memory retrieval to guide prediction. After structure learning, they completed a simultaneous prediction and encoding task. They were shown trial-unique category exemplars and made predictions about upcoming scene categories. Finally, participants completed a surprise memory test for the trial-unique images. Accurate (vs. inaccurate) predictions were associated with better encoding, and increasing prediction distance hurt both prediction and encoding. This association between encoding and prediction could not be explained by generic on- vs. off-task states. We propose that, in addition to stimulus and endogenous factors that modulate switches between encoding and retrieval, the success of one state can facilitate a switch to the other. Thus, although encoding and prediction depend on distinct and competitive computational mechanisms, the success of one in behavior can increase the likelihood of success for the other.
形成记忆需要关注外部世界;提取记忆则需要关注我们的内部世界。计算模型提出,海马体通过在优先处理其中一方的状态之间交替,来解决编码与提取之间的矛盾。我们探讨了在行为层面测量时,提取状态的成功与否是否会影响编码状态的成功。在3项实验(N = 197)中,我们将提取操作化为利用记忆对未来进行预测,并测试成功(与不成功)的预测是否会影响成功编码的可能性。参与者观看了一系列包含结构的场景类别(例如,海滩之后是城堡),这使得记忆提取能够引导预测。在结构学习之后,他们完成了一项同时进行预测和编码的任务。他们会看到每次试验独有的类别示例,并对即将出现的场景类别进行预测。最后,参与者对每次试验独有的图像进行了一次突击记忆测试。准确(与不准确)的预测与更好的编码相关联,并且增加预测距离会对预测和编码都产生不利影响。编码与预测之间的这种关联无法用一般的任务执行与未执行状态来解释。我们提出,除了调节编码与提取之间转换的刺激和内源性因素外,一种状态的成功可以促进向另一种状态的转换。因此,尽管编码和预测依赖于不同且相互竞争的计算机制,但一种在行为上的成功可以增加另一种成功的可能性。