EEG Decoding

EEG: Electroencephalography

Follow this topic Ask about this topic

Momentum

21 papers in the last four weeks, up 200% on the four weeks before. 0.2% of all new papers.

Jul 13Week of Sep 28

Latest papers 136

All topics

Towards Robust EEG Decoding Based on Riemannian Self-Attention
Jun 24, 2026Shaocheng Jin, Tao Zhou, Rui Wang +4Brain-Computer Interfaces Self-Attention
School of Artificial Intelligence and Computer Science Jiangnan University Wuxi, China · Department of Information Engineering and Computer Science University of Trento Trento, Italy · Centre for Vision, Speech and Signal Processing (CVSSP) University of Surrey Guildford, UK
Average Rankings Mask Per-Subject Optimality: A Friedman-Nemenyi Benchmark of EEG Motor-Imagery BCI Decoders
Jun 23, 2026Xavier Vasques, Paul Barbaste, Olivier OullierMI Classification Brain-Computer Interfaces
IBM Technology, Bois-Colombes, France · IBM France Lab, Orsay, France · Inclusive Brains, Marseille, France +4
Breaking Shortcut Learning for Cross-Trial EEG-Guided Target Speech Extraction via Two-Stage Training
Jun 23, 2026Wonchul Shin, Inyong Choi, Kyogu LeeTarget Speaker Extraction EEG Decoding
Department of Intelligence and Information, Seoul National University, Republic of Korea · Department of Communication Sciences and Disorders, University of Iowa, United States · Interdisciplinary Program in Artificial Intelligence, Seoul National University, Republic of Korea +1
NeuroSonic: Conditional Flow Matching for EEG-to-Speech Reconstruction
Jun 23, 2026Wenhao Gao, Yifan Wang, Yijia Ma +3Conditional Flow Matching EEG Decoding
Stony Brook University, Stony Brook, NY, USA · University of Texas Health Center at Houston, Houston, TX, USA · Emory University, Atlanta, GA, USA
B[FM] $^2$ : Brain Foundation Model via Flow Matching with SplitUNet
Jun 18, 2026Jaedong Hwang, Kathleen Zhang, Wei Dai +5Flow Matching EEG Decoding
Massachusetts Institute of Technology · KU Leuven
SwitchBraidNet: Quantisation-Aware Lightweight Architecture for Hybrid Brain-Computer Interface
Jun 17, 2026Gourav Siddhad, Yogesh Kumar MeenaEfficient Neural Network Inference Brain-Computer Interfaces
Human-AI Interaction (HAIx) Lab, Indian Institute of Technology Gandhinagar, Gujarat, 382055, India
SUP-MCRL: Subject-aware Unified Pseudo-feature Coded Multimodal Contrastive Representation Learning for EEG Visual Decoding
Jun 15, 2026Shengyu Gong, Weiming Zeng, Yueyang Li +4Cross-Subject EEG Decoding Contrastive Learning
Lab of Digital Image and Intelligent Computation, Shanghai Maritime University, Shanghai 201306, China · Department of Language Science and Technology, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Special Administrative Region, China · Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang 222002, China
Learning aligned EEG representations with subject-specific encoders
Jun 15, 2026Bruna J. Lopes, Gabriel Schwartz, Sylvain Chevallier +2Cross-Subject EEG Decoding MI Classification
University of São Paulo, São Paulo, Brazil · Université Paris-Saclay, Inria TAU team, LISN-CNRS, France · Institut de neuromodulation, GHU Paris, psychiatrie et neurosciences, centre hospitalier Sainte-Anne, pôle hospitalo-universitaire 15, Université Paris Cité, Paris, France +3
FAConformer: Frequency-Aware Convolutional Transformer for Auditory Attention Decoding
Jun 12, 2026Ziwei Wang, Xingyi He, Tianwang Jia +2Hybrid CNN-Transformer Architectures Neural Decoding
Hubei Key Laboratory of Brain-inspired Intelligent Systems, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China
Zero-Shot Neural Priors for Generalizable Cross-Subject and Cross-Task EEG Decoding
Jun 12, 2026Baimam Boukar Jean Jacques, Brandone Fonya, Nchofon Tagha Ghogomu +2Cross-Subject EEG Decoding Zero-Shot Learning
Carnegie Mellon University
Deep Sleep Classification via EEG Signal Criticality: A Passive BCI Approach for Sleep-Improvement Neurofeedback
Jun 11, 2026Stanisław Narębski, Tomasz Komendziński, Tomasz M. RutkowskiSleep Stage Classification Brain-Computer Interfaces
Nicolaus Copernicus University, Toru´n, Poland · Araya Inc., Tokyo, Japan · The University of Tokyo, Tokyo, Japan
The Identity Trap in EEG Foundation Models: A Diagnostic Audit
Jun 4, 2026Jun-You Lin, Ying Choon Wu, Tzyy-Ping JungCross-Subject EEG Decoding EEG Decoding
School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan · Swartz Center for Computational Neuroscience, University of California, San Diego, La Jolla, CA 92037, USA
A Sliced-Wasserstein Framework on Correlation Matrices for EEG Decoding
Jun 4, 2026Chen Hu, Rui Wang, Jiale Zhou +4EEG Decoding Domain Generalization
Westlake University Hangzhou, China · School of Artificial Intelligence and Computer Science Jiangnan University Wuxi, China · Zhejiang University Hangzhou, China +1
Channel-Oriented Design for EEG-to-Music Reconstruction
Jun 2, 2026Jiaxin Qing, Junwei Lu, Lexin LiElectroencephalography Cross-Modal Representation Learning
UC Berkeley · Harvard University
ERP-XTTN: Interpretable Prototype-Guided Cross-Attention for Cross-Subject ERP Classification
Jun 1, 2026Charlotte Genevier Wyman, Leanne HirshfieldCross-Subject EEG Decoding Prototype-Based Classification
University of Colorado Boulder, Boulder, CO, United States of America
EVA-Net: Subject-Independent EEG Motor Decoding with Video-Derived Motor Priors
Jun 1, 2026Ziyuan Li, Yueru Sun, Yimeng ZhangCross-Subject EEG Decoding Brain-Computer Interfaces
South China University of Technology, Guangzhou, China
EvoBrain: Continual Learning of EEG Foundation Models Across Heterogeneous BCI Tasks
Jun 1, 2026Yangxuan Zhou, Sha Zhao, Jiquan Wang +2Brain-Computer Interfaces EEG Decoding
State Key Laboratory of Brain-machine Intelligence and College of Computer Science and Technology, Zhejiang University, Hangzhou, Zhejiang, China · MOE Frontier Science Center for Brain Science and Brain-Machine Integration, Zhejiang University, Hangzhou, Zhejiang, China
Context-aware tokenization for Cross-subject Emotion Decoding from EEG
May 30, 2026Jiaxin Qing, Lexin LiCross-Subject EEG Decoding EEG Decoding
University of California, Berkeley
OmniEEG-Bench: A Standardized Evaluation Benchmark for EEG Foundation Models
May 30, 2026Ziling Lu, Zongsheng Li, Xinke Shen +11Brain-Computer Interfaces Benchmark Design
Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China · School of Computer Science and Engineering, The Chinese University of Hong Kong, Shenzhen, China · Omni-Intelligence, Shenzhen, China +1
MindVoice: Reconstructing Intelligible Speech from Non-invasive Neural Signals with Pretrained Priors
May 29, 2026Guangyin Bao, Taiping Zeng, Jianfeng Feng +1Brain-Computer Interfaces Neural Decoding
Fudan University
Routing on the Stiefel Manifold: When Does Adaptive Subspace Selection Help for Cross-Domain EEG Decoding?
May 29, 2026Isabella Costa Maia, Pedro L. C. Rodrigues, Salem Said +1Cross-Subject EEG Decoding Stiefel Manifold Optimization
GIPSA-lab, University Grenoble Alpes, CNRS, Grenoble-INP · Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP, LJK · Univ. Grenoble Alpes, CNRS, Grenoble INP, LJK
Benchmarking Positional Encoding Strategies for Transformer-Based EEG Foundation Models
May 28, 2026Ayse Betul Yuce, Sebastian StoberMI Classification EEG Decoding
Department of Computer Science, Otto von Guericke University, Magdeburg, Germany
A Multi-dimensional Framework for Evaluating Generalization in EEG Foundation Models
May 27, 2026Aditya Kommineni, Emily Zhou, Kleanthis Avramidis +2Neural Network Generalization EEG Decoding
Signal Analysis and Interpretation Laboratory, University of Southern California, USA
SYNAPSE: Neuro-Symbolic Visual Thought-to-Text Decoding via Topological Semantic Denoising
May 27, 2026Akshaj Murhekar, Abhijit MishraLanguage Model Decoding EEG Decoding
School of Information University of Texas at Austin
A Methodological Framework for Explicit Control of the Speed-Accuracy Trade-off in Brain-Computer Interfaces
May 26, 2026Javier Jiménez, Francisco B RodríguezBrain-Computer Interfaces EEG Decoding
EEG-FM-Audit: A Systematic Evaluation and Analysis Pipeline for EEG Foundation Models
May 26, 2026Xianheng Wang, Yige Yang, Damien CoyleEEG Decoding Explainability Evaluation
Bath Institute for the Augmented Human University of Bath Bath, BA2 7AY · Department of Computer Science University of Bath Bath, BA2 7AY
Aperiodic and Low-Frequency Spectral Bias in Reconstruction based EEG Foundation Models
May 26, 2026Aditya Kommineni, Emily Zhou, Kleanthis Avramidis +7Self-Supervised Time Series Representation Learning EEG Decoding
Ming Hsieh Department of Electrical and Computer Engineering1 University of Southern California · Thomas Lord Department of Computer Science2[cs.LG] University of Southern California · Department of Mathematical Sciences3 Aalborg University
Sleep-stage efficient classification using a lightweight self-supervised model
May 25, 2026Eldiane Borges dos Santos Durães, João Batista FlorindoEfficient Neural Network Inference Sleep Stage Classification
Institute of Mathematics, Statistics and Scientific Computing, University of Campinas, Street Sergio Buarque de Holanda, 651, Campinas, Brazil
Decoding Stimulus Reconstruction-Based Auditory Attention Robustly in Unbalanced EEG Datasets
May 25, 2026Yuanming Zhang, Yayun Liang, Zhibin Lin +1Class-Imbalanced Learning Electroencephalography
Key Lab of Modern Acoustics, Nanjing University, Nanjing 210093, China · NJU-Horizon Intelligent Audio Lab, Horizon Robotics, Beijing 100094, China
BandVQ: Band-Wise Vector-Quantized EEG Foundation Model
May 24, 2026Jamiyan Sukhbaatar, Satoshi Imamura, Toshihisa TanakaCross-Subject EEG Decoding Masked Autoencoders
National University of Mongolia, Ulaanbaatar, Mongolia · Tokyo University of Agriculture and Technology, Tokyo, Japan

Jun 24, 2026, cs.LGJ/K move · Enter open · S save

Towards Robust EEG Decoding Based on Riemannian Self-Attention

Shaocheng Jin, Tao Zhou, Rui Wang, Ziheng Chen+3

School of Artificial Intelligence and Computer Science Jiangnan University Wuxi, China · Department of Information Engineering and Computer Science University of Trento Trento, Italy · Centre for Vision, Speech and Signal Processing (CVSSP) University of Surrey Guildford, UK

Brain-Computer Interfaces Self-Attention EEG Decoding

Open paper AskPDF arXiv

Brain-Computer Interface (BCI) based on electroencephalography (EEG) enables direct interaction between the brain and external environments and has significant applications in assistive technologies, medical rehabilitation, and entertainment. Recently, EEG decoding methods based on Symmetric Positive Definite (SPD) learning have demonstrated superior performance. However, these methods typically employ basic network architectures and do not explicitly capture local relationships between EEG signals. This limitation is problematic for EEG signals due to their inherently low Signal-to-Noise Ratio (SNR). Moreover, most existing Riemannian manifold-based methods are restricted to specific metrics. The most widely used is the Affine-Invariant Metric (AIM). However, it has a quadratic dependency on the SPD matrices and cannot handle ill-conditioned SPD matrices, which hinders the effectiveness of networks. In contrast, the Bures-Wasserstein Metric (BWM) exhibits linear dependence on SPD matrices and demonstrates superior performance for ill conditioning. To overcome these challenges, we propose a Riemannian self-attention network based on the BWM. Additionally, the recently introduced power-deformed generalized Bures-Wasserstein metric reveals a nonlinear relationship between SPD matrices and matrix power deformation. This metric provides a more nuanced representation of the geometric structure of the SPD manifold. Consequently, we extend our model to a learnable version. For simplicity, we refer to it as GBWAtt. Experimental results on three EEG benchmarking datasets validate the robustness and effectiveness of our proposed method. The code is available at https://github.com/jissc/GBWAtt.

Momentum

Related topics

Latest papers 136