了解隐含性作为一个内在模拟演讲者的语境检索检索
Shingo Tokimoto1, Naoko Tokimoto2
1Department of English Language Studies, Mejiro University, Shinjuku City, Tokyo, Japan.
Frontiers in human neuroscience
|June 20, 2025
概括
听众使用自传记忆检索和思维理论 (ToM) 来理解间接语音,挑战传统的语言模型. 这个过程涉及到积极寻找上下文,以整合对话中的隐含含义.
科学领域:
- 认知神经科学 认知神经科学
- 心理语言学 心理语言学
- 神经成像是一种神经成像.
背景情况:
- 每天的谈话依赖于推断说话者的间接意图,而不仅仅是字面意义.
- 隐性沟通的实用推理背后的神经机制尚未得到充分理解.
- 了解间接表达对于有效的社交互动至关重要.
研究的目的:
- 研究涉及理解间接发言的认知和神经过程.
- 检查语境明确性和时间参考对间接语音理解的影响.
- 通过使用脑电图 (EEG) 探索实用推理的神经基础.
主要方法:
- 电脑电图 (EEG) 在参与者倾听口语对话时录制.
- 对上下文的明确性 (明确与隐含) 和时间引用 (现在与过去) 的操作.
- 分析与事件相关的潜力 (ERP),与事件相关的光谱扰动 (ERSP) 和使用源本地化EEG数据的有效连接.
- 与自闭症谱系系数得分的相关性.
主要成果:
- 语境的明确性在过去的经验对话中显著影响了EEG反应.
- 与明确的背景相比,隐性背景显示ERP正偏移的增加和抑制的 θ 和 β 频段.
- 在隐含的过去经验背景中,观察到增加了信息流向副海马环的信息流,这表明了自传记忆检索.
- 连接性与自闭症谱系系数得分有关,特别是想象力和沟通子表 (与心智理论相关).
结论:
- 自传记忆检索,以二次思维理论 (ToM) 过程为指导,促进了间接发言的理解.
- 听众内部模拟说话者的上下文检索,挑战语言理解的逐步命题模型.
- 研究结果支持一种"作为上下文搜索的实用推断"模型,用于理解话语中的隐含含义.
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