Retrieved context in episodic and semantic memory

在情景和语义记忆中检索上下文

• 批准号: 6848326
• 负责人: Marc W Howard
• 金额: $ 22.1万
• 依托单位: SYRACUSE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-02-01 至 2009-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6848326
• 关键词: association learning; behavioral /social science research tag; clinical research; human subject; mathematical model; memory; model design /development; psychological models; semantics; verbal learning; vocabulary

DESCRIPTION (provided by applicant): The relationship between episodic and semantic memory has been a source of much controversy in recent years. Previous work has established the Temporal Context Model (TCM) as a viable model of episodic recall. TCM uses retrieved context to model episodic associations. Latent Semantic Analysis (LSA) builds a semantic representation by using information about the contexts in which different words occur in large bodies of text to approximate their meanings. In LSA, the representation of two words becomes similar if they occur in similar textual contexts. This is reminiscent of the mediated associations (A-B, B-C) paradigm, in which A and C become associated by virtue of having been presented in a similar context (B). The proposed research examines the relationship between episodic and semantic memory using experiment and theory. Experiments study the ability of episodic memory to mimic the context-sensitive property of semantic memory. Using double-function lists (long chains of pairs, A-B, B-C, C-D, etc), we will explore the mediated association paradigm in new depth, testing specific predictions of TCM. Theoretically, TCM will be "trained on" large bodies of text. The resulting semantic representation will be compared to the semantic structure predicted by LSA, the semantic structure of English, and free association norms. By applying a quantitative model of episodic recall to semantic learning, the proposed research could provide considerable insight into the bases of episodic and semantic memory.

描述（由申请人提供）：近年来，情景记忆和语义记忆之间的关系一直是许多争议的来源。以往的研究已经建立了时间背景模型（TCM）作为情景回忆的可行模型。中医使用检索上下文来模拟情景关联。潜在语义分析（LSA）通过使用大量文本中不同单词出现的上下文信息来近似其含义，从而构建语义表示。在LSA中，如果两个单词出现在相似的文本上下文中，它们的表示就会变得相似。这让人想起中介关联（A-B, B-C）范式，其中A和C通过在相似的背景下呈现而联系起来(B)。本研究采用实验与理论相结合的方法探讨情景记忆与语义记忆的关系。实验研究情景记忆模仿语义记忆的上下文敏感特性的能力。利用双功能表（长对链，A-B, B-C， C-D等），我们将在新的深度探索介导的关联范式，测试中医的具体预测。理论上，中医将在大量文本上进行“训练”。得到的语义表示将与LSA预测的语义结构、英语的语义结构和自由关联规范进行比较。通过将情景回忆的定量模型应用于语义学习，本研究可以对情景记忆和语义记忆的基础提供相当深入的了解。