Doctoral Dissertation Improvement: Fast and Slow Linguistic Predictions

博士论文改进：快速和慢速语言预测

• 批准号: 1530332
• 负责人: Colin Phillips
• 金额: $ 1.8万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-06-01 至 2017-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1530332&HistoricalAwards=false
• 关键词: Doctoral; Dissertation; Improvement; Fast; Slow

Language unfolds rapidly in time, and is often contaminated by various kinds of noise. Despite these challenges, native speakers? comprehension is generally robust and efficient. A key cognitive mechanism that underlies the robustness and efficiency of language understanding is the ability to predict the future based on knowledge acquired from past experience, i.e., memory. Much recent research has shown that comprehenders are very good at predicting upcoming words. However, little is known about exactly how comprehenders generate predictions in real time, as they hear or read sentences. In order to understand predictive mechanisms, we need to understand the nature of the memory systems that are engaged, the mechanisms that guide memory access, and how those mechanisms relate to the linguistic information that provides the memory cues. Understanding these mechanisms is important for figuring out how human languages are processed in the brain, and it may serve as a foundation for understanding how human language processing mechanisms can be impaired or repaired (in clinical settings), trained (in educational settings), and simulated (in technological settings).This research aims to examine the mechanisms underlying word prediction by studying native English speakers (in the US) and native Japanese speakers (in Japan) using electroencephalography (EEG). The project will support the doctoral dissertation research of Shota Momma. The studies build on previous research that shows that some linguistic predictions are computed rapidly while others are computed more slowly. The guiding hypothesis for the current project is that the speed of linguistic predictions depends on the compatibility between linguistic cues and the format of memory encoding. Linguistic cues that mismatch the format of memory are slower to compute. The project tests this hypothesis via experiments that vary the nature of the linguistic cues. The Japanese studies will be carried out with partners at Waseda University in Tokyo, where they will contribute to a growing scientific partnership between the American and Japanese laboratories.

语言在时间上迅速展开，并且经常受到各种噪音的污染。尽管有这些挑战，母语人士？理解通常是稳健和有效的。语言理解的鲁棒性和效率的基础的关键认知机制是基于从过去经验获得的知识预测未来的能力，即，记忆最近的许多研究表明，记忆者非常擅长预测即将出现的单词。然而，人们对预测者在听到或阅读句子时是如何在真实的时间内产生预测的知之甚少。为了理解预测机制，我们需要了解参与的记忆系统的性质，引导记忆访问的机制，以及这些机制如何与提供记忆线索的语言信息相关。了解这些机制对于弄清楚人类语言在大脑中是如何处理的非常重要，它可能作为理解人类语言处理机制如何受损或修复的基础（在临床环境中），经过培训（在教育环境中），和模拟本研究旨在通过对英语本族语者的研究来探讨词汇预测的潜在机制（在美国）和母语为日语的人（在日本）使用脑电图（EEG）。该项目将支持Shota Momma的博士论文研究。这些研究建立在以前的研究基础上，这些研究表明，一些语言预测的计算速度很快，而另一些计算速度较慢。当前项目的指导假设是，语言预测的速度取决于语言线索和记忆编码格式之间的兼容性。与记忆格式不匹配的语言线索的计算速度较慢。该项目通过改变语言线索性质的实验来测试这一假设。日本的研究将与东京早稻田大学的合作伙伴一起进行，他们将为美国和日本实验室之间不断增长的科学伙伴关系做出贡献。