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超高速意义和形式预测:基于脑电图的表征相似性分析。

Hyper-speed meaning and form predictions: An EEG-based representational similarity analysis.

作者信息

Angulo-Chavira Armando Quetzalcóatl, Castellón-Flores Alejandra Mitzi, Carrasco-Ortiz Haydee, Arias-Trejo Natalia

机构信息

Facultad de Psicología, Universidad Nacional Autónoma de México, C-10, Av. Universidad 3004, Col. Copilco Universidad, Delegación Coyoacán, C.P. 04510, CdMx, México.

Facultad de Lenguas y Letras, Universidad Autónoma de Querétaro, Querétaro, México.

出版信息

Psychon Bull Rev. 2025 Jul 25. doi: 10.3758/s13423-025-02731-4.

DOI:10.3758/s13423-025-02731-4
PMID:40715685
Abstract

Language comprehension involves predictive processing, in which comprehenders anticipate both semantic and form-related attributes of upcoming words. This predictive mechanism is crucial as it enables efficient real-time language processing, allowing listeners and readers to keep pace with rapid information streams and quickly correct potential errors. Using electroencephalography (EEG) and representational similarity analysis (RSA), we investigated whether predictions follow a hierarchical, top-down process or occur in parallel, facilitated by associative mechanisms. In this study, native Spanish-speaking undergraduate students read highly constrained sentences designed to elicit specific target words. RSA was applied to evaluate the similarity between all possible pairs of expected words, and signals were classified into semantic, form-related, or specific-word effects based on their relationship to the expected word. The results revealed a rapid transition between effects, with semantic predictions consistently preceding form-related and specific-word predictions. While the sequential order aligns with hierarchical processing, this rapid predictive transition is better understood in the context of associative mechanisms and predictive coding.

摘要

语言理解涉及预测性处理,即理解者会预测即将出现的单词的语义和形式相关属性。这种预测机制至关重要,因为它能实现高效的实时语言处理,使听众和读者跟上快速的信息流,并迅速纠正潜在错误。我们使用脑电图(EEG)和表征相似性分析(RSA),研究了预测是遵循自上而下的层次化过程,还是在联想机制的促进下并行发生。在本研究中,以西班牙语为母语的本科学生阅读了旨在引出特定目标单词的高度受限的句子。应用RSA来评估所有可能的预期单词对之间的相似性,并根据信号与预期单词的关系将其分类为语义、形式相关或特定单词效应。结果显示,这些效应之间存在快速转换,语义预测始终先于形式相关预测和特定单词预测。虽然这种顺序与层次化处理一致,但在联想机制和预测编码的背景下,这种快速的预测转换更容易理解。

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