MPT模型在事件性前瞻记忆研究中的应用

摘要： 前瞻性记忆是指对将要进行的活动或事件的记忆。前瞻记忆中，包含了前瞻成分和回溯成分。前人研究中，缺乏对前瞻成分和回溯成分有效的分离手段，使得对前瞻记忆机制的探讨缺乏深入挖掘。本文将MPT模型与Cohen等人的研究范式对比，分析了该模型在事件性前瞻记忆研究中的优势。文章对模型的理论基础，模型的主要内容，模型的数据计算方法，模型的效度以及模型的应用等几个方面进行了介绍，同时对模型使用中需要注意的问题进行了讨论。
Abstract: Remembering to perform an action in the future is called prospective memory (PM). It contains time-based prospective memory(TBPM)and event-based prospective memory (TBPM ). TBPM refers to remembering to perform an action at a specific time or after a certain amount of time has elapsed. And EBPMA refers that one must be performed when a certain event occurs. Both of these memory constitute a crucial form of memory use in our daily lives. This paper mainly introduces EBPM. PM contains two components, the prospective component and the retrospective component. Remembering that you have to do something is the prospective component, whereas remembering what you have to do and when you have to do it is considered the retrospective component. Unfortunately, if a variable affects prospective memory,we cannot determine how the variable affects each of the two different components using traditional accuracy measures. We cannot disentangle the two components clearly and then cannot explore the latent cognitive processes of prospective memory deeply in previous studies. This article presents a detailed discussion and application of a methodology by comparing with the paradigm of Cohen and others in EBPM, called Multinomial process tree (MPT) models. In these models, it is assumed that there are discrete cognitive states that participants attain with certain probabilities during task performance. These probabilities are represented as model parameters that can be estimated from observed raw data via maximum likelihood parameter estimation. The fit of the resulting model to the empirical data can be evaluated via goodness-of-fit tests.MPT model is relatively uncomplicated, do not require advanced mathematical techniques, and have certain advantages over other, more traditional methods for studying cognitive processes. Smith and Bayen first introduced the MPT model for the measurement of EBPM . The model is based on the preparatory attentional processes and memory processes (PAM) theory , which proposes that the prospective component involves processes that draw on our limited resources, and, thus, that these processes are not automatic. And now this theory is supported by many studies.. The authors explained why we appoint the modle in EBPM at first, and then introduced the modle in detail including the theoretical basis, the main content, the