在自然主义语言理解过程中减少不确定性的独特贡献
Ming Song1, Jing Wang1, Qing Cai1
1Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), Affiliated Mental Health Center (ECNU), Institute of Brain and Education Innovation, School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China; Shanghai Changning Mental Health Center, Shanghai, China; Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai, China.
概括
缩,在语言理解过程中减少不确定性,独特地预测大脑活动. 这一发现表明大脑寻求信息获取,与处理困难分开.
科学领域:
- 神经科学是一个神经科学.
- 认知科学 认知科学
- 计算语言学 计算语言学
背景情况:
- 语言理解是增量和预测性的.
- 缩缩量量化了语言处理过程中的不确定性下降.
- 像surprisal这样的现有指标可能会将处理难度与信息内容混为一谈.
研究的目的:
- 为了区分缩与神经反应中的处理困难.
- 为了研究语言理解过程中减少的独特的神经相关物.
- 使用信息理论指标建模大脑活动.
主要方法:
- 使用GPT-2来描述信息理论指标.
- 在语言理解过程中分析功能磁共振成像 (fMRI) 数据.
- 与神经激活相关的降低.
主要成果:
- 缩减少独特预测的fMRI时间序列.
- 激活的大脑区域包括左下额叶,腹中前额叶皮质,胰岛,丘脑,基底,和中间环状皮质.
- 不确定性的减少,而不是它的波动,有效地模拟了神经反应.
结论:
- 缩反映了信息获取的认知神经过程,与处理困难不同.
- 与缩相关的神经基质表明大脑有寻求信息的机制.
- 这为语言理解的神经基础提供了新的视角.
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