A distributed representation of temporal context
A distributed representation of temporal context
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DOI：
10.1006/jmps.2001.1388
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发表时间：
2002-06-01
影响因子：
1.8
通讯作者：
Kahana, MJ
中科院分区：
文献类型：
--
作者：
Howard, MW;Kahana, MJ
新近度和连续性的原理是人类记忆的理论和经验分析的两个基石。衰减，位移和追溯干扰的机制可以解释新颖性。新近度的另一个说明是基于可变上下文的思想（Estes，1955; Mensink＆Raaijmakers，1989）。这种概念通常是根据反映环境或受试者精神状态的微妙变化的随机波动人群来施放的。这种随机上下文视图最近已被纳入分布式和神经网络记忆模型（Murdock，1997; Murdock，Smith和Bai，2001年）。在这里，我们提出了一个替代模型。该公式，即时间上下文模型（TCM），而不是由随机波动驱动，而是使用先前上下文状态的检索来驱动上下文漂移。在TCM中，检索的上下文是一种固有的不对称检索提示。这使该模型可以在自由和串行召回中对远期召回的广泛优势提供原则上的解释。对单次免费召回的数据进行建模，我们证明了TCM可以同时解释跨时间尺度的重新度和连续性效应。 （C）2001 Elsevier Science（美国）。
The principles of recency and contiguity are two cornerstones of the theoretical and empirical analysis of human memory. Recency has been alternatively explained by mechanisms of decay, displacement, and retroactive interference. Another account of recency is based on the idea of variable context (Estes, 1955; Mensink & Raaijmakers, 1989). Such notions are typically cast in terms of a randomly fluctuating population of elements reflective of subtle changes in the environment or in the subjects' mental state. This random context view has recently been incorporated into distributed and neural network memory models (Murdock, 1997; Murdock, Smith, & Bai, 2001). Here we propose an alternative model. Rather than being driven by random fluctuations, this formulation, the temporal context model (TCM), uses retrieval of prior contextual states to drive contextual drift. In TCM, retrieved context is an inherently asymmetric retrieval cue. This allows the model to provide a principled explanation of the widespread advantage for forward recalls in free and serial recall. Modeling data from single-trial free recall, we demonstrate that TCM can simultaneously explain recency and contiguity effects across time scales. (C) 2001 Elsevier Science (USA).