2026-10-10T16:21:37Z https://www.scidb.cn/oai

10.57760/sciencedb.20611 2025-11-20T12:23:45Z

2025-11-20 ChineseEEG-2:An EEG Dataset for Multimodal Semantic Alignment and Neural Decoding during Reading and Listening doi:10.57760/sciencedb.20611 en Now-existing Electroencephalography (EEG) datasets are mainly based on English, which encounters difficulty when representing Chinese. While there have been EEG datasets related to linguistic stimuli, the existing resources are limited, and many faces the problem of teacher-forcing. In our future studies, we plan to promote a unified encoder of multi-modalities for semantic decoding, which suggests the need of more data support. To bridge this gap, we introduce ChineseEEG-2, a high-density EEG dataset that extends ChineseEEG containing both reading aloud and auditory listening tasks. As a unique multimodal EEG dataset featuring synchronized reading and listening tasks based on the same corpus, ChineseEEG-2 dataset enables the exploration of how the brain processes language across both visual and auditory modalities in the context of Chinese natural language. It offers valuable insights into multimodal semantic alignment, neural decoding, and the alignment between large language models and neural processes, contributing to the development of BCI systems for language decoding*Important Note: This version of the dataset is no longer maintained. For the latest data and updates, please refer to the official and maintained version at: https://doi.org/10.57760/sciencedb.CHNNeuro.00001 EEG; natural language processing; Semantic Decoding Sitong Chen Beiqianyi Li Cuilin He Dongyang Li Mingyang Wu Xinke Shen Song Wang Xuetao Wei Xindi Wang Haiyan Wu Quanying Liu PUBLIC https://creativecommons.org/publicdomain/zero/1.0/ dataset Science Data Bank