Kauf Carina, Kim Hee So, Lee Elizabeth J, Jhingan Niharika, Selena She Jingyuan, Taliaferro Maya, Gibson Edward, Fedorenko Evelina
Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139 USA.
McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139 USA.
bioRxiv. 2024 Jun 21:2024.06.21.599332. doi: 10.1101/2024.06.21.599332.
Human language comprehension is remarkably robust to ill-formed inputs (e.g., word transpositions). This robustness has led some to argue that syntactic parsing is largely an illusion, and that incremental comprehension is more heuristic, shallow, and semantics-based than is often assumed. However, the available data are also consistent with the possibility that humans always perform rule-like symbolic parsing and simply deploy error correction mechanisms to reconstruct ill-formed inputs when needed. We put these hypotheses to a new stringent test by examining brain responses to a) stimuli that should pose a challenge for syntactic reconstruction but allow for complex meanings to be built within local contexts through associative/shallow processing (sentences presented in a backward word order), and b) grammatically well-formed but semantically implausible sentences that should impede semantics-based heuristic processing. Using a novel behavioral syntactic reconstruction paradigm, we demonstrate that backward-presented sentences indeed impede the recovery of grammatical structure during incremental comprehension. Critically, these backward-presented stimuli elicit a relatively low response in the language areas, as measured with fMRI. In contrast, semantically implausible but grammatically well-formed sentences elicit a response in the language areas similar in magnitude to naturalistic (plausible) sentences. In other words, the ability to build syntactic structures during incremental language processing is both necessary and sufficient to fully engage the language network. Taken together, these results provide strongest to date support for a generalized reliance of human language comprehension on syntactic parsing.
人类语言理解对结构不良的输入(例如单词换位)具有显著的鲁棒性。这种鲁棒性使得一些人认为句法剖析在很大程度上是一种错觉,并且增量理解比通常所认为的更具启发性、更浅显且基于语义。然而,现有数据也与以下可能性一致:人类总是进行类似规则的符号剖析,并在需要时简单地部署纠错机制来重构结构不良的输入。我们通过检查大脑对以下两种刺激的反应,对这些假设进行了一项新的严格测试:a)应该对句法重构构成挑战,但允许通过联想/浅层处理在局部语境中构建复杂意义的刺激(以倒序呈现的句子),以及b)语法结构良好但语义不合理的句子,这类句子应该会阻碍基于语义的启发式处理。使用一种新颖的行为句法重构范式,我们证明了倒序呈现的句子在增量理解过程中确实会阻碍语法结构的恢复。至关重要的是,用功能磁共振成像测量,这些倒序呈现的刺激在语言区域引发的反应相对较低。相比之下,语义不合理但语法结构良好的句子在语言区域引发的反应与自然(合理)句子在幅度上相似。换句话说,在增量语言处理过程中构建句法结构的能力对于充分激活语言网络既是必要的也是充分的。综上所述,这些结果为人类语言理解普遍依赖句法剖析提供了迄今为止最有力的支持。