MoMiLab, IMT School for Advanced Studies Lucca, Piazza S.Francesco, 19, Lucca 55100, Italy.
The BioRobotics Institute and Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Viale Rinaldo Piaggio 34, Pontedera 56025, Italy.
Cereb Cortex. 2024 Aug 1;34(8). doi: 10.1093/cercor/bhae317.
Acoustic, lexical, and syntactic information are simultaneously processed in the brain requiring complex strategies to distinguish their electrophysiological activity. Capitalizing on previous works that factor out acoustic information, we could concentrate on the lexical and syntactic contribution to language processing by testing competing statistical models. We exploited electroencephalographic recordings and compared different surprisal models selectively involving lexical information, part of speech, or syntactic structures in various combinations. Electroencephalographic responses were recorded in 32 participants during listening to affirmative active declarative sentences. We compared the activation corresponding to basic syntactic structures, such as noun phrases vs. verb phrases. Lexical and syntactic processing activates different frequency bands, partially different time windows, and different networks. Moreover, surprisal models based on part of speech inventory only do not explain well the electrophysiological data, while those including syntactic information do. By disentangling acoustic, lexical, and syntactic information, we demonstrated differential brain sensitivity to syntactic information. These results confirm and extend previous measures obtained with intracranial recordings, supporting our hypothesis that syntactic structures are crucial in neural language processing. This study provides a detailed understanding of how the brain processes syntactic information, highlighting the importance of syntactic surprisal in shaping neural responses during language comprehension.
大脑同时处理声学、词汇和句法信息，需要复杂的策略来区分它们的电生理活动。利用先前分离声学信息的研究成果，我们可以通过测试竞争统计模型，专注于词汇和句法对语言处理的贡献。我们利用脑电图记录，并在不同组合中比较了不同的显著度模型，这些模型选择性地涉及词汇信息、词性或句法结构。在 32 名参与者听肯定主动陈述句时记录了脑电图反应。我们比较了基本句法结构（如名词短语与动词短语）对应的激活情况。词汇和句法处理激活了不同的频带，部分时间窗口不同，涉及的网络也不同。此外，仅基于词性词汇的显著度模型不能很好地解释电生理数据，而包含句法信息的模型则可以。通过分离声学、词汇和句法信息，我们证明了大脑对句法信息的敏感性存在差异。这些结果证实并扩展了先前使用颅内记录获得的测量结果，支持我们的假设，即句法结构在神经语言处理中至关重要。这项研究提供了对大脑如何处理句法信息的详细理解，强调了句法显著度在塑造语言理解过程中的神经反应方面的重要性。
