Michigan State University, Michigan, MI, USA.
University of North Carolina at Greensboro, Greensboro, NC, USA.
Mem Cognit. 2024 Jan;52(1):163-181. doi: 10.3758/s13421-023-01453-z. Epub 2023 Oct 2.
Recent events are easy to recall, but they also interfere with the recall of more distant, non-recent events. In many computational models, non-recent memories are recalled by using the context associated with those events as a cue. Some models, however, do little to explain how people initially activate non-recent contexts in the service of accurate recall. We addressed this limitation by evaluating two candidate mechanisms within the Context-Maintenance and Retrieval model. The first is a Backward-Walk mechanism that iteratively applies a generate/recognize process to covertly retrieve progressively less recent items. The second is a Post-Encoding Pre-Production Reinstatement (PEPPR) mechanism that formally implements a metacognitive control process that reinstates non-recent contexts prior to retrieval. Models including these mechanisms make divergent predictions about the dynamics of response production and monitoring when recalling non-recent items. Before producing non-recent items, Backward-Walk cues covert retrievals of several recent items, whereas PEPPR cues few, if any, covert retrievals of that sort. We tested these predictions using archival data from a dual-list externalized free recall paradigm that required subjects to report all items that came to mind while recalling from the non-recent list. Simulations showed that only the model including PEPPR accurately predicted covert recall patterns. That same model fit the behavioral data well. These findings suggest that self-initiated context reinstatement plays an important role in recall of non-recent memories and provides a formal model that uses a parsimonious non-hierarchical context representation of how such reinstatement might occur.
近期事件很容易被回忆起来,但它们也会干扰对更久远、非近期事件的回忆。在许多计算模型中,非近期记忆是通过使用与这些事件相关的上下文作为线索来回忆的。然而,有些模型几乎没有解释人们最初如何为了准确回忆而激活非近期的上下文。我们通过在上下文维护和检索模型中评估两个候选机制来解决这个局限性。第一个是回溯机制,它通过迭代应用生成/识别过程,来秘密地检索越来越不近期的项目。第二个是后编码前产生再激活(PEPPR)机制,它正式实现了一种元认知控制过程,即在检索之前恢复非近期的上下文。包括这些机制的模型对回忆非近期项目时的反应产生和监测的动态做出了不同的预测。在产生非近期项目之前,回溯线索会秘密地检索几个近期项目,而 PEPPR 线索则很少,甚至没有那种类型的秘密检索。我们使用要求被试在回忆非近期列表时报告所有出现在脑海中的项目的双列表外部自由回忆范式的档案数据来检验这些预测。模拟表明,只有包括 PEPPR 的模型准确地预测了秘密回忆模式。同样的模型也很好地拟合了行为数据。这些发现表明,自我启动的上下文再激活在非近期记忆的回忆中起着重要作用,并提供了一个正式的模型,该模型使用一种简洁的非分层上下文表示来解释这种再激活是如何发生的。