Doctoral dissertation research: The encoding, maintenance and retrieval of complex linguistic representations in working memory

博士论文研究：工作记忆中复杂语言表征的编码、维护和检索

• 批准号: 2116952
• 负责人: Ming Xiang
• 金额: $ 1.76万
• 依托单位: University of Chicago
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2116952&HistoricalAwards=false
• 关键词: Doctoral; dissertation; research; encoding; maintenance

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).Human language comprehension relies on the support from working memory (WM), but it is known that WM capacity is limited. To combat this limitation, comprehenders form structured representations (chunks) comprising multiple words at various levels of complexity. How the WM encoding, maintenance and retrieval processes support structures of varying complexity remains poorly understood. This dissertation project examines how linguistic representations are formed and stored in WM by identifying the costs and benefits associated with supporting complex representations in WM. While there has been previous work on complexity, this project aims to provide a more nuanced perspective by examining different aspects of linguistic complexity. By contributing to the body of work on the interplay between WM and language comprehension, the project also has potential clinical implications for language-related disorders such as specific language impairment and various forms of aphasia.The project investigates the relatively unexplored interaction between representational complexity and the three working memory processes (encoding, maintenance, and retrieval). The first set of studies investigates whether forming complex representations with more features can facilitate or hinder one or more of the three core WM processes. The second set of studies further examines how the facilitation or interference effects are modulated by the similarity between elements within a chunked representation. Finally, the third set of studies examines how the formation of a hierarchically chunked structure affects the retrieval of its individual components. To provide a multidimensional view of the interaction between WM processes and linguistic complexity, the project employs both behavioral (self-paced reading) and electrophysiological (EEG) methodologies.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该奖项的全部或部分资金来源于《2021 年美国救援计划法案》（公法 117-2）。人类语言理解依赖于工作记忆（WM）的支持，但众所周知，WM 容量有限。为了克服这一限制，理解者形成了包含不同复杂程度的多个单词的结构化表示（块）。 WM 编码、维护和检索过程如何支持不同复杂性的结构仍然知之甚少。本论文项目通过确定与支持 WM 中的复杂表示相关的成本和收益，研究了语言表示是如何在 WM 中形成和存储的。虽然之前已经有关于复杂性的工作，但该项目旨在通过检查语言复杂性的不同方面来提供更细致的视角。通过对 WM 和语言理解之间相互作用的研究工作做出贡献，该项目还对语言相关疾病（例如特定语言障碍和各种形式的失语症）具有潜在的临床意义。该项目研究了表征复杂性和语言理解之间相对未经探索的相互作用。三个工作记忆过程（编码、维护和检索）。第一组研究调查了形成具有更多特征的复杂表示是否可以促进或阻碍三个核心 WM 过程中的一个或多个。第二组研究进一步研究了分块表示中元素之间的相似性如何调节促进或干扰效应。最后，第三组研究探讨了分层分块结构的形成如何影响其各个组件的检索。为了提供 WM 过程和语言复杂性之间相互作用的多维视图，该项目采用了行为（自定进度阅读）和电生理 (EEG) 方法。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准。

项目成果

Noun phrase representational complexity reduces maintenance cost in working memory by increasing distinctiveness between referents

名词短语表征复杂性通过增加所指对象之间的独特性来降低工作记忆的维护成本

• 发表时间: 2022
• 期刊: Proceedings of the Annual Conference of the Cognitive Science Society
• 作者: Lam, Chi-Dat;Xiang, Ming
• 通讯作者: Xiang, Ming