人工语法任务中的表现示例模型：全息表征
An exemplar model of performance in the artificial grammar task: holographic representation.
作者信息
Jamieson Randall K, Hauri Brian R
机构信息
Department of Psychology, University of Manitoba, Winnipeg, Canada.
出版信息
Can J Exp Psychol. 2012 Jun;66(2):98-105. doi: 10.1037/a0027023.
We apply a multitrace model of memory to explain performance in the artificial grammar task. The model blends the convolution method for representation from Jones and Mewhort's BEAGLE model (Jones, M. N., & Mewhort, D. J. K. (2007). Representing word meaning and order information in a composite holographic lexicon. Psychological Review, 114, 1-37) of semantic memory with the multitrace storage and retrieval model from Hintzman's MINERVA 2 model (Hintzman, D. L. (1986). "Schema abstraction" in a multiple-trace memory model. Psychological Review, 93, 411-428) of episodic memory. We report an artificial grammar experiment, and we fit the model to those data at the level of individual items. We argue that performance in the artificial grammar task is best understood as a process of retrospective inference from memory.
我们应用一种记忆多痕迹模型来解释人工语法任务中的表现。该模型将琼斯和梅霍特的BEAGLE模型（琼斯，M.N.，& 梅霍特，D.J.K.（2007）。在复合全息词典中表示词义和顺序信息。《心理学评论》，114，1 - 37）中用于语义记忆表征的卷积方法与欣茨曼的MINERVA 2模型（欣茨曼，D.L.（1986）。多痕迹记忆模型中的“图式抽象”。《心理学评论》，93，411 - 428）中用于情景记忆的多痕迹存储和检索模型相结合。我们报告了一项人工语法实验，并在单个项目层面将该模型与这些数据进行拟合。我们认为，人工语法任务中的表现最好被理解为一个从记忆中进行追溯推理的过程。
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