脑电信号与多模态AI融合，解码人类动作理解的前沿研究。
arXiv:2506.01353v3 Announce Type: replace Abstract: The integration of brain-computer interfaces (BCIs), in particular electroencephalography (EEG), w…
轻量级CNN+Mamba框架精准自动睡眠分期，专攻小样本EEG数据集，高效实用。
arXiv:2607.04934v1 Announce Type: new Abstract: Automatic sleep staging is a key technology for precise diagnosis and treatment of sleep disorders as …
EEG基础模型存在跨编码器属性泄露风险，研究揭示现有单端点审计的不足。
arXiv:2606.09189v1 Announce Type: cross Abstract: EEG foundation-model releases are usually audited one endpoint at a time: raw-reconstruction, member…
大脑信号解码新突破：用语义压缩实现无创脑电转文本，准确率大幅提升
arXiv:2604.16370v2 Announce Type: replace-cross Abstract: Decoding natural language from non-invasive electroencephalography (EEG) remains constrained…
首个标准化EEG基础模型评估基准，覆盖多任务与多数据集，推动脑电AI研究规范化。
arXiv:2606.00815v1 Announce Type: new Abstract: Electroencephalography (EEG) supports a variety of brain-computer interface (BCI) tasks ranging from b…
突破性将生成式视觉基础引入EEG理解，保留脑电信号中的视觉细节，赋能多模态大模型实现通用脑机接口。
arXiv:2605.18172v2 Announce Type: replace Abstract: Leveraging the universal representations of pre-trained LLMs and MLLMs offers a promising path tow…
首个纵向专注冥想脑电图数据集与基准，助力冥想神经机制研究。
arXiv:2605.22893v1 Announce Type: cross Abstract: We introduce a novel Longitudinal Focused Attention Meditation Electroencephalography (L-FAME) datas…
首个系统评估基础模型在临床EEG和脑机接口任务中的泛化能力，为领域提供标准化基准
arXiv:2605.14698v1 Announce Type: cross Abstract: Foundation models (FMs) promise to extract unified representations that generalize across downstream…
脑电信号直接转文字？RAG+大模型解码思维的新方法，IEEE论文干货满满
arXiv:2605.17503v1 Announce Type: cross Abstract: The decoding of linguistic information from electroencephalography (EEG) signals remains an extremel…
提出TFM-Tokenizer，从单通道脑电信号学习时频模式并编码为离散token，为EEG基础模型提供新思路。
arXiv:2502.16060v5 Announce Type: replace-cross Abstract: Foundation models are reshaping EEG analysis, yet an important problem of EEG tokenization r…
新方法LAtte用双曲罗伦兹注意力突破跨被试EEG分类瓶颈，抗噪声与个体差异表现亮眼。
arXiv:2603.10881v2 Announce Type: replace Abstract: Electroencephalogram (EEG) classification plays a key role in medical diagnosis and brain-computer…
首个统一多模态脑基础模型，横跨fMRI、EEG、MEG，打破单一模态局限。
arXiv:2602.23410v3 Announce Type: replace-cross Abstract: Brain foundation models have achieved remarkable advances across a wide range of neuroscienc…
首个临床EEG到语言的基础模型，让长时程脑电图自动生成临床报告，告别繁琐人工总结。
arXiv:2601.22197v3 Announce Type: replace-cross Abstract: Generating clinical reports that summarize abnormal patterns, diagnostic findings, and clini…
揭秘EEG基础模型如何直接从原始脑电信号自监督学习，挑战传统手工特征范式，为神经科学和AI融合提供新视角。
arXiv:2605.11410v2 Announce Type: replace Abstract: Clinical electroencephalogram (EEG) analysis rests on a hand-crafted feature catalog refined over …