Cross-Subject EEG Decoding

EEG: Electroencephalography

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Overview

Cross-subject EEG decoding asks whether models trained on some people can recognize brain states in new people, a key challenge for brain-computer interfaces and clinical tools. Approaches include domain adaptation and alignment, Riemannian covariance methods, contrastive and self-supervised representation learning, and EEG foundation models; some use limited target-subject calibration, while others aim for zero-shot transfer. Studies commonly use leave-one-subject-out tests on motor imagery, emotion, and clinical EEG, but results vary by task and population. A central tension is balancing shared patterns with individual differences while ensuring gains are not caused by leakage or subject-identity shortcuts.

Latest papers

CardsList

78 papers14 papers in the last four weeks, up 17% on the four weeks before. 0.1% of all new papers.

  1. PA-TCNet: Pathology-Aware Temporal Calibration with Physiology-Guided Target Refinement for Cross-Subject Motor Imagery EEG Decoding in Stroke Patients

    Apr 17, 2026Xiangkai Wang, Yun Zhao, Dongyi He +5Cross-Subject EEG DecodingBrain-Computer Interfaces

    School of Artificial Intelligence, Chongqing University of Technology, Chongqing 401135, China; Chongqing Key Laboratory of Embodied Intelligence Perception and Autonomous Learning for Humanoid Robots; Key Laboratory of Advanced Equipment Intelligence of the Chongqing Education Commission, Chongqing 401135, China · School of Smart Health, Chongqing Polytechnic University of Electronic Technology, Chongqing 401131, China · Department of Language Science and Technology, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR, China +2

  2. CA-TCN: A Causal-Anticausal Temporal Convolutional Network for Direct Auditory Attention Decoding

    Mar 27, 2026Iñigo García-Ugarte, Rubén Eguinoa, Ricardo San Martín +2Neural DecodingTemporal Convolutional Networks

    Department of Science, Universidad Pública de Navarra (UPNA), 31006 Pamplona, Spain · BCBL, Basque Center on Cognition Brain and Language, 20009 San Sebastián, Spain · Department of Statistics, Computer Sciences and Mathematics, Universidad Pública de Navarra (UPNA), 31006 Pamplona, Spain +2

  3. CIPHER: Conformer-based Inference of Phonemes from High-density EEG

    Mar 22, 2026Varshith MadishettyEEG-to-Text DecodingConformer

  4. SATTC: Structure-Aware Label-Free Test-Time Calibration for Cross-Subject EEG-to-Image Retrieval

    Mar 21, 2026Qunjie Huang, Weina ZhuCross-Subject EEG DecodingEEG-Based Visual Decoding

    Yunnan University, China

  5. SpecMoE: Spectral Mixture-of-Experts Foundation Model for Cross-Species EEG Decoding

    Mar 17, 2026Davy Darankoum, Chloé Habermacher, Julien Volle +1EEG DecodingEEG Foundation Models

    Univ. Grenoble Alpes, CNRS, Grenoble INP, LJK 38000 Grenoble, France · SynapCell SAS, ZAC ISIPARC, 38330 Saint-Ismier, France

  6. The Deep-Match Framework for Event-Related Potential Detection in EEG

    Mar 11, 2026Marek Zylinski, Bartosz Tomasz Smigielski, Gerard CybulskiElectroencephalographyEEG Decoding

    Institute of Metrology and Biomedical Engineering, Faculty of Mechatronics, Warsaw University of Technology, Warsaw, Poland

  7. LAtte: Hyperbolic Lorentz Attention for Cross-Subject EEG Classification

    Mar 11, 2026Ahmad Bdeir, Johannes Burchert, Tom Hanika +2Cross-Subject EEG DecodingElectroencephalography

    Data Science Group, Universität Hildesheim · ISMLL, Universität Hildesheim

  8. Group Resonance Network: Learnable Prototypes and Multi-Subject Resonance for EEG Emotion Recognition

    Mar 11, 2026Renwei MengCross-Subject EEG DecodingElectroencephalography

    Anhui University, Hefei, China

  9. Scattering Transform for Auditory Attention Decoding

    Feb 26, 2026René Pallenberg, Fabrice Katzberg, Alfred Mertins +1Wavelet Scattering TransformsEEG Decoding

    Institute for Signal Processing, University of Luebeck, 23562 Luebeck, Germany · Department for Vision and Machine Learning, FPI Food Processing Innovation GmbH & Co. KG, 23556 Luebeck, Germany · German Research Center for Artificial Intelligence (DFKI), AI for Assistive Health Technologies, 23562 Luebeck, Germany

  10. CRCC: Contrast-Based Robust Cross-Subject and Cross-Site Representation Learning for EEG

    Feb 22, 2026Xiaobin Wong, Zhonghua Zhao, Haoran Guo +5Cross-Dataset GeneralizationCross-Domain Generalization

    Tsinghua Laboratory of Brain and Intelligence · Institute of Automation, Chinese Academy of Sciences · University of Chinese Academy of Sciences +6

  11. ASPEN: Spectral-Temporal Fusion for Cross-Subject Brain Decoding

    Feb 18, 2026Megan Lee, Seung Ha Hwang, Inhyeok Choi +3Cross-Subject EEG DecodingBrain-Computer Interfaces

    Carnegie Mellon University, Pittsburgh, PA, USA · Kyung Hee University, Yongin, South Korea · Korea Advanced Institute of Science and Technology, Deajeon, South Korea +1

  12. Geometry-Aware Deep Congruence Networks for Manifold Learning in Cross-Subject Motor Imagery

    Nov 24, 2025Sanjeev Manivannan, Chandra Shekar LakshminarayanCross-Subject EEG DecodingMI Classification

    Department of Biotechnology · Department of Data Science and Artificial Intelligence

  13. Interpretable Multimodal EEG-ECG Framework for Neonatal Seizure Prediction and Patient-Adaptive Transfer Learning

    Nov 18, 2025Sithmini Ranasingha, Agasthi Haputhanthri, Hansa Marasinghe +5EEG Seizure DetectionCross-Subject EEG Decoding

    Department of Electronic and Telecommunication Engineering, University of Moratuwa, Sri Lanka · Department of Electrical and Computer Engineering, University of British Columbia, Canada · Department of Biomedical Engineering, University of Melbourne, Australia +1

  14. NeuroBridge: Bio-Inspired Self-Supervised EEG-to-Image Decoding via Cognitive Priors and Bidirectional Semantic Alignment

    Nov 10, 2025Wenjiang Zhang, Sifeng Wang, Yuwei Su +3EEG-Based Visual DecodingCross-Subject EEG Decoding

    School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China · Queen Mary School Hainan, Beijing University of Posts and Telecommunications, Hainan 570100, China

  15. Learning Domain- and Class-Disentangled Prototypes for Domain-Generalized EEG Emotion Recognition

    Sep 1, 2025Guangli Li, Canbiao Wu, Zhehao Zhou +3Cross-Subject EEG DecodingPrototype-Based Classification

    School of Biological Science and Medical Engineering, Hunan University of Technology, Zhuzhou 412008, China · School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen 518060, China · Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen 518060, China +1

  16. Cross-Subject and Cross-Montage EEG Transfer Learning via Individual Tangent Space Alignment and Spatial-Riemannian Feature Fusion

    Aug 11, 2025Nicole Lai-Tan, Xiao Gu, Marios G. Philiastides +1Cross-Subject EEG DecodingBrain-Computer Interfaces

  17. Brain foundation model-guided source-selective domain adaptation for cross-subject EEG decoding

    Jul 28, 2025Jinzhou Wu, Baoping Tang, Qikang Li +3Cross-Subject EEG DecodingMulti-Source Domain Adaptation

    State Key Laboratory of Mechanical Transmission, College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044, China · Department of Computer Science, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands · Machine Learning Group, UiT–The Arctic University of Norway, 9019 Tromsø, Norway

  18. Are EEG Sequences Time Series? EEG Classification with Time Series Models and Joint Subject Training

    Apr 10, 2024Johannes Burchert, Thorben Werner, Vijaya Krishna Yalavarthi +3Time Series ClassificationCross-Subject EEG Decoding

    Institute for Computer Science, University of Hildesheim, Hildesheim, German