脑机接口 / BCI

Pioneering EEG Motor Imagery Classification Through Counterfactual Analysis

Kang Yin, Hye-Bin Shin, Hee-Dong Kim, Seong-Whan Lee

专题命中 EEG解码 ：EEG(title,abstract)；motor imagery(title)；分类 eess.SP、cs.LG

Classification of BCI-EEG based on augmented covariance matrix

Igor Carrara, Théodore Papadopoulo

专题命中 EEG解码 ：BCI(title)；EEG(title)；motor imagery(abstract)；分类 cs.LG、cs.HC

ZIPBrain: Can EEG Foundation Models Be Faster, Locally Deployable, but Accurate?

ZIPBrain：脑电基础模型能否更快、可本地部署且仍保持准确？

Lingwei Li, Yirong Kan, Peng Chen, Xu Cao, Zheng Chen, Yasuhiko Nakashima

专题命中 EEG解码 ：EEG(title,summary_cn)

AI总结 本研究提出即插即用模块ZIPBrain，利用EEG低SNR特性减少token数量，使EEG基础模型推理速度提升32.7%（最高41.8%）且平均准确率提升1.3%-10.5%，可本地部署。

Comments 7 pages(14 pages including appendix), 5 figures

Does EEG Foundation Models Transfer to Speech? A Benchmark on Overt and Imagined Speech Decoding

脑电基础模型能否迁移至语音？显性与想象语音解码的基准测试

Owais Mujtaba Khanday, Mohamed Baha Ben Ticha, Sanae Belfrouh, Marc Ouellet, Jose A. Gonzalez-Lopez

机构 * University of Granada, Spain（格拉纳达大学） ； Research Centre for Information and Communication Technologies (CITIC-UGR), Spain（信息与通信技术研究中心） ； University of Chouaib Doukkali, Morocco（舒艾卜·杜卡利大学） ； Brain, Mind, and Behavior Research Center (CIMCYC), University of Granada, Spain（大脑、心智与行为研究中心） 纠错

专题命中 EEG解码 ：EEG(title,abstract)；BCI(abstract,abstract_cn)；motor imagery(abstract)

AI总结 本文开展首个脑电基础模型语音解码基准测试，对比LaBraM等模型与EEGNet等基线，发现通用脑电预训练未在语音任务上展现一致优势，为语音专用基础模型研究提供依据。

Comments 6 pages, 1 figure, 3 tables, submitted to IberSPEECH 2026

MSBraM: A Multi-scale Self-supervised Brain Foundation Model for Hierarchical EEG Dynamics Learning

MSBraM：用于分层脑电动力学学习的多尺度自监督脑基础模型

Tao Zhou, Jing Han, Lingyu Shu, Zixing Zhang

机构 * Hunan University（湖南大学） 纠错

专题命中 EEG解码 ：EEG(title,summary_cn)

AI总结 针对现有方法难捕捉EEG信号多尺度时间结构的问题，提出MSBraM模型。该模型采用两阶段预训练框架，经多尺度神经分词器和课程多尺度掩码策略学习分层EEG表征。实验显示其在多个下游任务中性能优越，证明显式建模多尺度时间动态对EEG基础模型的重要性。

Multimodal Pretraining for Generalizable EEG Representation Learning

用于可泛化脑电信号表征学习的多模态预训练

Targol Bakhtiarvand, Jugal Kalita, Adham Atyabi

机构 * University of Colorado Colorado Springs（科罗拉多大学科罗拉多斯普林斯分校） 纠错

专题命中 EEG解码 ：EEG(title,summary_cn)

AI总结 研究针对癫痫EEG模型应用局限问题，开发多模态EEG基础模型，结合多种编码器，通过创新预训练技术创建癫痫相关表征。在多个数据集和评估设置下实验，该模型实现强大癫痫检测与适应新场景能力，支持可解释癫痫定位，性能达当前最优。

EVA-Net: Subject-Independent EEG Motor Decoding with Video-Derived Motor Priors

EVA-Net: 基于视频衍生运动先验的跨被试脑电运动解码

Ziyuan Li, Yueru Sun, Yimeng Zhang

机构 * South China University of Technology（华南理工大学） 纠错

专题命中 EEG解码 ：EEG(title,abstract)；BCI(abstract,abstract_cn)；brain-computer interface(abstract)

AI总结 提出EVA-Net两阶段框架，利用动作视频作为语义先验，通过跨模态对比学习和对齐减少个体差异，实现跨被试脑电运动解码，在EEGMMI上取得8.66%的LOSO准确率提升。

miMamba: EEG-based Emotion Recognition with Multi-scale Inverted Mamba Models

miMamba：基于多尺度倒置曼巴模型的脑电情感识别

Xin Zhou, Dawei Huang, Xiaojing Peng, Lijun Yin

机构 * Department of Computer Science, State University of New York at Binghamton（纽约州立大学布法罗分校计算机科学系） ； College of Big Data and Internet, Shenzhen Technology University（深圳科技大学大数据与互联网学院） 纠错

专题命中 EEG解码 ：EEG(title,abstract)；brain-computer interface(abstract)；分类 eess.SP、cs.LG、cs.HC

AI总结 研究脑电情感识别，提出多尺度倒置曼巴（MS-iMamba）网络，含多尺度时间块和时空融合块，能捕捉不同尺度子序列特征及时空交互，实验表明其仅用四通道脑电信号就优于现有方法。

Comments IEEE Transactions on Affective Computing (2025)

Journal ref IEEE Transactions on Affective Computing ( Volume: 16, Issue: 4, Oct.-Dec. 2025)

Dual-Stream EEG Decoding for 3D Visual Perception

用于3D视觉感知的双流脑电解码

Ninon Lizé Masclef, Taisija Demcenko, Antonella Catanzaro, Nataliya Kosmyna

机构 * Massachusetts Institute of Technology（麻省理工学院） 纠错

专题命中 EEG解码 ：EEG(title,summary_cn)

AI总结 提出一种模仿生物视觉腹侧和背侧通路的双流脑电解码模型，通过圆形回归预测角度和EEG条件多视图扩散实现3D重建，揭示了时间动态的通道参与模式。

Comments 17 pages, 4 figures. Accepted at the Symmetry and Geometry in Neural Representations Workshop (NeurReps), NeurIPS 2025. To appear in Proceedings of Machine Learning Research (PMLR)

LuMamba: Latent Unified Mamba for Electrode Topology-Invariant and Efficient EEG Modeling

LuMamba: 用于电极拓扑不变且高效的EEG建模的潜在统一Mamba

Danaé Broustail, Anna Tegon, Thorir Mar Ingolfsson, Yawei Li, Luca Benini

机构 * ETH Zürich, Institute of Information Systems（苏黎世联邦理工学院信息系统研究所） 纠错

专题命中 EEG解码 ：EEG(title,title_cn)

AI总结 提出LuMamba框架，结合拓扑不变编码和线性复杂度状态空间模型，通过LUNA的查询交叉注意力机制统一通道，FEMBA的双向Mamba块高效时序建模，在5个下游任务上以4.6M参数达到SOTA性能。

Comments EUSIPCO 2026, 5 pages, 2 figures, 4 tables

A Methodological Framework for Explicit Control of the Speed-Accuracy Trade-off in Brain-Computer Interfaces

脑机接口中速度-准确性权衡显式控制的方法论框架

Javier Jiménez, Francisco B Rodríguez

机构 * Grupo de Neurocomputación Biológica, Departamento de Ingeniería Informática, Universidad Autónoma de Madrid（生物神经计算组，信息工程系，马德里自治大学） 纠错

专题命中 EEG解码 ：brain-computer interface(title,abstract)；BCI(abstract,abstract_cn)；分类 eess.SP、cs.LG、cs.HC

AI总结 提出一个独立于分类器、范式和早停策略的评估框架，通过增益和保持度两个指标及可调参数α显式控制速度-准确性权衡，并在P300范式上验证其有效性。

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization

对齐共享专家和路由专家以实现跨被试脑电图泛化

Zhi Zhang, Yan Liu, Zhejing Hu, Gong Chen, Sheng-hua Zhong, Changhong Jing, Shuqiang Wang, Jibin Wu, KC Tan, Jiannong Cao

专题命中 EEG解码 ：EEG(title,summary_cn)

AI总结 提出共享-路由专家对齐（SREA）框架，通过联合嵌入、原型稀疏路由和互导重加权，协同共享专家与路由专家，解决跨被试EEG泛化中个体差异与可迁移结构的平衡问题。

Interpretable Fuzzy Modeling Reveals Population-Level Representation Differences in P300 Brain Computer Interfaces Across Neurodivergent and Neurotypical Cohorts

可解释的模糊建模揭示了P300脑机接口在自闭症、肌萎缩侧索硬化和典型神经群体中的群体层面表征差异

Xiaowei Jiang, Sudong Shang, Adrian Wilkinson, Michael L. Platt, Da Xiao, Bening Cao, Thomas Do

机构 * Department of Management, Griffith Business School（管理学院，格里菲斯商学院） ； Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania（神经科学系，佩尔曼医学学院，宾夕法尼亚大学） ； Marketing Department, Wharton School of Business, University of Pennsylvania（营销系，沃顿商学院，宾夕法尼亚大学） ； Department of Psychology, School of Arts and Sciences, University of Pennsylvania（心理学系，艺术与科学学院，宾夕法尼亚大学） 纠错

专题命中 EEG解码 ：brain computer interface(title)；BCI(abstract,abstract_cn)；brain-computer interface(abstract)；分类 eess.SP、cs.LG、cs.HC

AI总结 本文提出可解释的模糊时空框架用于P300分类，分析不同群体在波形形态和表征几何上的系统性差异，揭示群体异质性对解码性能及模型学习结构的影响。

PAT: Privacy-Preserving Adversarial Transfer for Accurate, Robust and Privacy-Preserving EEG Decoding

PAT: 用于准确、鲁棒且隐私保护的对抗性迁移

Xiaoqing Chen, Tianwang Jia, Yunlu Tu, Dongrui Wu

机构 * Hubei Key Laboratory of Brain-inspired Intelligent Systems, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology（华中科技大学人工智能与自动化学院脑启发智能系统湖北省重点实验室） ； Shenzhen Huazhong University of Science and Technology Research Institute（深圳华中科技大学研究院） ； Zhongguancun Academy（中关村学院） 纠错

专题命中 EEG解码 ：EEG(title,abstract)；BCI(abstract)；brain-computer interface(abstract)；分类 eess.SP、cs.LG、cs.HC

AI总结 本文提出PAT框架，结合数据对齐、对抗训练和隐私保护迁移，提升EEG解码的准确性、鲁棒性和隐私保护，实验表明其在多个数据集上优于现有方法。

Spatial Insight: How Data-Driven Regions of Interest Selection Enhances Single-Trial P300 Classification in EEG-Based BCIs

Eva Guttmann-Flury, Jian Zhao, Mohamad Sawan

专题命中 EEG解码 ：EEG(title,abstract)；BCI(abstract)；brain-computer interface(abstract)；cortical(abstract)

PL-DCP: A Pairwise Learning framework with Domain and Class Prototypes for EEG emotion recognition under unseen target conditions

Guangli Li, Canbiao Wu, Zhehao Zhou, Tuo Sun, Ping Tan, Li Zhang, Zhen Liang

机构 * School of Biological Science and Medical Engineering, Hunan University of Technology（湖南工程技术大学生物科学与医学工程学院） ； Xiangjiang Laboratory（湘江实验室） ； School of Intelligent Engineering and Intelligent Manufacturing, Hunan University of Technology and Business（湖南工程技术大学与商学院智能工程与智能制造学院） ； School of Biomedical Engineering, Health Science Center, Shenzhen University（深圳大学生物医学工程学院、健康科学中心） ； Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging（广东省生物医学测量与超声成像重点实验室） 纠错

专题命中 EEG解码 ：EEG(title,abstract)；BCI(abstract)；brain-computer interface(abstract)；分类 eess.SP、cs.LG、cs.HC

Siamese Network with Dual Attention for EEG-Driven Social Learning: Bridging the Human-Robot Gap in Long-Tail Autonomous Driving

Xiaoshan Zhou, Carol C. Menassa, Vineet R. Kamat

专题命中 EEG解码 ：EEG(title,abstract)；BCI(abstract)；brain-computer interface(abstract)；分类 cs.LG、cs.HC、cs.RO

Comments 50 pages, 18 figures

NeuroLM: A Universal Multi-task Foundation Model for Bridging the Gap between Language and EEG Signals

Wei-Bang Jiang, Yansen Wang, Bao-Liang Lu, Dongsheng Li

专题命中 EEG解码 ：EEG(title,abstract)；brain-computer interface(abstract)；neural signal(abstract)；分类 eess.SP、cs.LG、cs.HC

Comments The Thirteenth International Conference on Learning Representations

Journal ref The Thirteenth International Conference on Learning Representations, 2025

Large Cognition Model: Towards Pretrained EEG Foundation Model

Chi-Sheng Chen, Ying-Jung Chen, Aidan Hung-Wen Tsai

专题命中 EEG解码 ：EEG(title,abstract)；BCI(abstract)；brain-computer interface(abstract)；分类 q-bio.NC、eess.SP、cs.LG

Dataset Refinement for Improving the Generalization Ability of the EEG Decoding Model

Sung-Jin Kim, Dae-Hyeok Lee, Hyeon-Taek Han

专题命中 EEG解码 ：EEG(title,abstract)；brain-computer interface(abstract)；motor imagery(abstract)；分类 eess.SP、cs.LG、cs.HC

Comments 4 pages, 1 figure, conference

LGGNet: Learning from Local-Global-Graph Representations for Brain-Computer Interface

Yi Ding, Neethu Robinson, Chengxuan Tong, Qiuhao Zeng, Cuntai Guan

专题命中 EEG解码 ：brain-computer interface(title,abstract)；BCI(abstract)；EEG(abstract)；分类 q-bio.NC、eess.SP、cs.LG

Comments This work has been submitted to the IEEE for possible publication

Recording Brain Activity While Listening to Music Using Wearable EEG Devices Combined with Bidirectional Long Short-Term Memory Networks

Jingyi Wang, Zhiqun Wang, Guiran Liu

专题命中 EEG解码 ：EEG(title,abstract)；BCI(abstract)；brain-computer interface(abstract)；分类 eess.SP、cs.LG、cs.HC

Comments 15 pages

Riemannian Geometry-Based EEG Approaches: A Literature Review

Imad Eddine Tibermacine, Samuele Russo, Ahmed Tibermacine, Abdelaziz Rabehi, Bachir Nail, Kamel Kadri, Christian Napoli

专题命中 EEG解码 ：EEG(title,abstract)；BCI(abstract)；brain-computer interface(abstract)；分类 eess.SP、cs.LG、cs.HC

EEG2TEXT: Open Vocabulary EEG-to-Text Decoding with EEG Pre-Training and Multi-View Transformer

Hanwen Liu, Daniel Hajialigol, Benny Antony, Aiguo Han, Xuan Wang

专题命中 EEG解码 ：EEG(title,abstract)；BCI(abstract)；brain-computer interface(abstract)；motor imagery(abstract)

Decoding Natural Images from EEG for Object Recognition

Yonghao Song, Bingchuan Liu, Xiang Li, Nanlin Shi, Yijun Wang, Xiaorong Gao

专题命中 EEG解码 ：EEG(title,abstract)；brain-computer interface(abstract)；neural decoding(abstract)；分类 q-bio.NC、eess.SP、cs.HC

Comments ICLR, 2024

Sequential Best-Arm Identification with Application to Brain-Computer Interface

Xin Zhou, Botao Hao, Jian Kang, Tor Lattimore, Lexin Li

专题命中 EEG解码 ：brain-computer interface(title,abstract)；BCI(abstract)；EEG(abstract)；分类 q-bio.NC、cs.LG、cs.HC

Two Heads are Better than One: A Bio-inspired Method for Improving Classification on EEG-ET Data

Eric Modesitt, Ruiqi Yang, Qi Liu

专题命中 EEG解码 ：EEG(title,abstract)；BCI(abstract)；brain computer interface(abstract)；分类 eess.SP、cs.LG、cs.HC

Comments 6 pages, 3 figures, HCI International 2023 Poster

Human Emotion Classification based on EEG Signals Using Recurrent Neural Network And KNN

Shashank Joshi, Falak Joshi

专题命中 EEG解码 ：EEG(title,abstract)；BCI(abstract)；brain-computer interface(abstract)；分类 eess.SP、cs.LG、cs.HC

EEG Synthetic Data Generation Using Probabilistic Diffusion Models

Giulio Tosato, Cesare M. Dalbagno, Francesco Fumagalli

专题命中 EEG解码 ：EEG(title,abstract)；BCI(abstract)；brain computer interface(abstract)；分类 q-bio.NC、eess.SP、cs.LG

Comments Our paper has been accepted for presentation at the Synapsium2023 conference

Mental arithmetic task classification with convolutional neural network based on spectral-temporal features from EEG

Zaineb Ajra, Binbin Xu, Gérard Dray, Jacky Montmain, Stephane Perrey

专题命中 EEG解码 ：EEG(title,abstract)；BCI(abstract)；brain-computer interface(abstract)；分类 q-bio.NC、eess.SP、cs.LG

Comments Updated Figure

Journal ref 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)