Semantic cognition: behavioural, computational, and EEG/ERP based analyses of semantic content, structure, and processing

语义认知：基于行为、计算和 EEG/ERP 的语义内容、结构和处理分析

• 批准号: 298168-2010
• 负责人: Cree, George
• 金额: $ 1.97万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2013
• 资助国家: 加拿大
• 起止时间: 2013-01-01 至 2014-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=525893
• 关键词: Semantic; cognition; behavioural; computational; EEG

The broad aim of this research program is to advance our fundamental understanding of how knowledge is stored and used in the brain. The research is designed to answer three questions that are central to this area: (1) What knowledge is represented in the mind/brain?; (2) How is that knowledge stored and organized?; and (3) How is that knowledge accessed and used when needed? My research combines a number of techniques in addressing these questions, including experiments conducted with human participants, the development of computer simulations of how the mind/brain stores and processes knowledge, and the use of electroencephalography (EEG) to measure electrical potentials at the scalp, which allow us to draw inferences about the time course of brain regions involved in processing knowledge. The research is designed to take place as three interrelated projects. First, I will be studying the content of people's conceptual representations by asking a very large number of participants to describe the information they think is important in representations of concepts. This information will be used to design stimuli for behavioral experiments that are designed to test among contemporary theories of semantic memory organization and processing, and for designing computer simulations intended to help us understand the behavioral patterns we observe in the human data. Finally, EEG will be used to help us understand the time course over which different types of semantic and word-based variables become active in the processing of words for meaning. This research extends what we already know in important ways: it will provide a deep understanding of how abstract knowledge is represented, it will provide a computer model of semantic cognition that can be used to derive predictions for future experiments and to understand patient behaviour, and it will significantly extend our understanding of when different aspects of semantic knowledge are computed, building on the rich knowledge fMRI has provided about where semantic knowledge is stored in the brain.

这项研究计划的广泛目标是促进我们对知识如何在大脑中存储和使用的基本理解。这项研究旨在回答这一领域的三个核心问题：(1)大脑/大脑中代表了什么知识？(2)这些知识是如何存储和组织的？(3)当需要时，这些知识是如何获取和使用的？我的研究结合了许多技术来解决这些问题，包括对人类参与者进行的实验，开发计算机模拟思维/大脑如何存储和处理知识，以及使用脑电(EEG)测量头皮的电位，这使我们能够推断参与处理知识的大脑区域的时间进程。这项研究被设计为三个相互关联的项目。首先，我将通过让大量参与者描述他们认为在概念表征中重要的信息来研究人们概念表征的内容。这些信息将被用来设计行为实验的刺激，这些实验旨在测试当代语义记忆组织和处理理论，并用于设计计算机模拟，旨在帮助我们理解我们在人类数据中观察到的行为模式。最后，EEG将帮助我们理解不同类型的语义和基于单词的变量在处理单词意义的过程中变得活跃的时间过程。这项研究在重要方面扩展了我们已经知道的内容：它将提供对抽象知识如何表示的深入理解，它将提供一个语义认知的计算机模型，可用于为未来的实验推导预测并理解患者行为，它将显著扩展我们对语义知识的不同方面何时被计算的理解，建立在fMRI提供的关于语义知识在大脑中存储在哪里的丰富知识的基础上。