Exploring the relationship between features calculated from contextual embeddings and EEG band power during sentence reading in Chinese

The mixed yet intriguing results invite a deeper discussion of the directional associations (positive/negative) observed in Gamma and other frequency bands, their cognitive implications, and the potential influence of textual characteristics on these findings. While observed effects may be somehow text- or dataset- dependent, our analyses revealed associations between various distance metrics and neural responses, consistent with predictions derived from the vector-based neural coding framework.

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Publication Details

Journal
Frontiers in Neuroscience
Published
2025-07-30
DOI
https://doi.org/10.3389/fnins.2025.1656519
Citations
2
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
2.86

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article

Exploring the relationship between features calculated from contextual embeddings and EEG band power during sentence reading in Chinese

Xiaojing Yao, T. Xue, Yang Xing-yu
2 citations
Frontiers in Neuroscience
EEG and Brain-Computer Interfaces
2.86
article

Exploring the relationship between features calculated from contextual embeddings and EEG band power during sentence reading in Chinese

Xiaojing Yao, T. Xue, Yang Xing-yu
article en
2 citations

Abstract

The mixed yet intriguing results invite a deeper discussion of the directional associations (positive/negative) observed in Gamma and other frequency bands, their cognitive implications, and the potential influence of textual characteristics on these findings. While observed effects may be somehow text- or dataset- dependent, our analyses revealed associations between various distance metrics and neural responses, consistent with predictions derived from the vector-based neural coding framework.

Frontiers in NeuroscienceVol. 19
Beijing Language and Culture University (CN)
Beijing Language and Culture University, Fundamental Research Funds for the Central Universities
Quality Education
Openalex Percentile: Top 9%
EEG and Brain-Computer Interfaces
2.86
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