谈话内容在大脑中的多个时间尺度中被组织起来
Masahiro Yamashita1,2, Rieko Kubo2,3, Shinji Nishimoto4,5
1Graduate School of Frontier Biosciences, The University of Osaka, Suita, Japan.
Nature human behaviour
|June 11, 2025
概括
通过功能磁共振成像 (fMRI) 和大型语言模型来探索对话的神经机制. 分享的大脑对语言的表现发生在短时间范围内,而不同的表现因生产和理解而有所不同,揭示了对话意义是如何出现的.
科学领域:
- 神经科学是一个神经科学.
- 语言学的语言学.
- 认知科学 认知科学
背景情况:
- 交谈使复杂的思想和情感交换成为可能.
- 意义构造整合了跨时间尺度 (单词,句子,话语) 的语言.
- 在谈话中交互意义化的神经支柱尚未得到充分理解.
研究的目的:
- 研究在自发对话中交互意义的神经机制.
- 在不同的时间尺度上模拟对话内容的神经表示.
- 了解如何共享和不同的神经过程有助于语言的生产和理解.
主要方法:
- 功能磁共振成像 (fMRI) 用于记录在数小时的自发对话期间的大脑活动.
- 来自大型语言模型 (GPT) 的上下文嵌入被用来建模对话内容的神经表示.
- 通过多个时间尺度 (词,句子,话语) 分析神经表征.
主要成果:
- 大脑中的语言表达在语音产生和理解之间既有共同之处,又有区别.
- 在较短的时间尺度 (单词,句子) 中发现了共享表示,主要是在语言选择性区域.
- 模式特定的表示显示了时间尺度的差异:生产时间较短,理解时间较长,表明了不同的整合机制.
结论:
- 对话意义来自于共享的语言代码和模式特定的时间整合的相互作用.
- 独特的神经机制支持上下文依赖的理解和自适应性语音生成.
- 这些发现揭示了人类如何在实时对话中处理和生成语言的神经基础.
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