脑机接口 / BCI

Leveraging Foundation Models for Calibration-Free c-VEP BCIs

利用基础模型实现无需校准的c-VEP脑机接口

Mohammadreza Behboodi, Eli Kinney-Lang, Ali Etemad, Adam Kirton, Hatem Abou-Zeid

机构 * Department of Biomedical Engineering, University of Calgary（生物医学工程系，卡尔加里大学） ； Department of Electrical and Computer Engineering, Queen’s University（电气与计算机工程系，皇后大学） ； Department of Pediatric and Clinical Neuroscience, University of Calgary（儿科与临床神经科学系，卡尔加里大学） ； Department of Electrical and Software Engineering, University of Calgary（电气与软件工程系，卡尔加里大学） 纠错

专题命中 BCI数据与评测 ：BCI(abstract)；brain-computer interface(abstract)；分类 cs.LG、cs.HC

AI总结 本文提出基于基础模型的无需校准c-VEP脑机接口方法，通过训练分类头实现即插即用，无需受试者特定数据，实验显示在两个数据集上均取得较高准确率。

Comments 8 Pages, 2 figures, Accepted and Presented at the IEEE SMC Conference 2025

Journal ref 2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Vienna, Austria, 2025, pp. 4564-4571

Are Large Brainwave Foundation Models Capable Yet? Insights from Fine-tuning

大规模脑电基础模型是否已具备能力？来自微调的洞察

Na Lee, Konstantinos Barmpas, Yannis Panagakis, Dimitrios Adamos, Nikolaos Laskaris, Stefanos Zafeiriou

机构 * Imperial College London（伦敦帝国学院） ； Archimedes / Athena Research Unit（阿基米德/雅典娜研究单位） ； Aristotle University of Thessaloniki（雅典娜大学） ； Kapodistrian University of Athens（雅典kapodistrian大学） 纠错

专题命中 BCI数据与评测 ：BCI(abstract)；brain-computer interface(abstract)；分类 cs.LG、cs.HC

AI总结 本文通过微调实验评估了大规模脑电基础模型的能力，发现其在BCI任务中效率有限，提出LoRA技术可提升性能，强调需重新设计架构以提升脑电分析效果。

Journal ref International Conference on Machine Learning (ICML) 2025

MoRE-Brain: Routed Mixture of Experts for Interpretable and Generalizable Cross-Subject fMRI Visual Decoding

Yuxiang Wei, Yanteng Zhang, Xi Xiao, Tianyang Wang, Xiao Wang, Vince D. Calhoun

机构 * University of Alabama at Birmingham（阿拉巴马大学伯明翰分校） ； Oak Ridge National Laboratory（橡树岭国家实验室） 纠错

专题命中 BCI数据与评测 ：brain-computer interface(abstract)；neural decoding(abstract)；分类 cs.LG、cs.HC

Comments Accepted to NeurIPS 2025

Calibration of Deep Learning Classification Models in fNIRS

Zhihao Cao, Zizhou Luo

专题命中 BCI数据与评测 ：BCI(abstract)；brain-computer interface(abstract)；分类 eess.SP、cs.LG

Multi-modal Mood Reader: Pre-trained Model Empowers Cross-Subject Emotion Recognition

Yihang Dong, Xuhang Chen, Yanyan Shen, Michael Kwok-Po Ng, Tao Qian, Shuqiang Wang

专题命中 BCI数据与评测 ：EEG(abstract)；neural signal(abstract)；分类 eess.SP、cs.LG

Comments Accepted by International Conference on Neural Computing for Advanced Applications, 2024

Domain Generalization for Zero-calibration BCIs with Knowledge Distillation-based Phase Invariant Feature Extraction

Zilin Liang, Zheng Zheng, Weihai Chen, Xinzhi Ma, Zhongcai Pei, Xiantao Sun

专题命中 BCI数据与评测 ：BCI(abstract)；EEG(abstract)；分类 eess.SP、cs.HC

Towards Interactive Reinforcement Learning with Intrinsic Feedback

Benjamin Poole, Minwoo Lee

专题命中 BCI数据与评测 ：BCI(abstract)；brain-computer interface(abstract)；分类 cs.LG、cs.HC

Comments Name change and vast rewrites of the paper

Towards Subject Agnostic Affective Emotion Recognition

Amit Kumar Jaiswal, Haiming Liu, Prayag Tiwari

专题命中 BCI数据与评测 ：brain-computer interface(abstract)；EEG(abstract)；分类 cs.LG、cs.HC

Comments To Appear in MUWS workshop at the 32nd ACM International Conference on Information and Knowledge Management (CIKM) 2023

Brain informed transfer learning for categorizing construction hazards

Xiaoshan Zhou, Pin-Chao Liao

专题命中 BCI数据与评测 ：brain-computer interface(abstract)；EEG(abstract)；分类 q-bio.NC、cs.LG

Interaction-Grounded Learning with Action-inclusive Feedback

Tengyang Xie, Akanksha Saran, Dylan J. Foster, Lekan Molu, Ida Momennejad, Nan Jiang, Paul Mineiro, John Langford

专题命中 BCI数据与评测 ：BCI(abstract)；brain-computer interface(abstract)；分类 cs.LG、cs.HC

Comments Published in NeurIPS 2022

Active recursive Bayesian inference using Rényi information measures

Yeganeh M. Marghi, Aziz Kocanaogullari, Murat Akcakaya, Deniz Erdogmus

专题命中 BCI数据与评测 ：BCI(abstract)；brain-computer interface(abstract)；分类 eess.SP、cs.LG

Comments 13 pages, 10 figures, 1 table

Subject-Independent Imagined Speech Detection via Cross-Subject Generalization and Calibration

Byung-Kwan Ko, Soowon Kim, Seo-Hyun Lee

机构 * Dept. of Artificial Intelligence Korea University Seoul, Republic of Korea（人工智能系韩国大学首尔共和国） 纠错

专题命中 BCI数据与评测 ：brain computer interface(abstract)；neural decoding(abstract)；分类 q-bio.NC；brain-computer interface(comments)

Comments 4 pages, 2 figures, Name of Conference: International Conference on Brain-Computer Interface

Approximate UMAP allows for high-rate online visualization of high-dimensional data streams

Peter Wassenaar, Pierre Guetschel, Michael Tangermann

专题命中 BCI数据与评测 ：BCI(abstract,comments)；分类 eess.SP、cs.LG、cs.HC；brain-computer interface(journal_ref)

Comments 6 pages, 3 figures, submitted to the Graz BCI conference 2024

Journal ref 9th Graz Brain-Computer Interface Conference (2024) 349-354

Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures

Vladimir Belov, Tracy Erwin-Grabner, Ali Saffet Gonul, Alyssa R. Amod, Amar Ojha, Andre Aleman, Annemiek Dols, Anouk Scharntee, Aslihan Uyar-Demir, Ben J Harrison, Benson M. Irungu, Bianca Besteher, Bonnie Klimes-Dougan, Brenda W. J. H. Penninx, Bryon A. Mueller, Carlos Zarate, Christopher G. Davey, Christopher R. K. Ching, Colm G. Connolly, Cynthia H. Y. Fu, Dan J. Stein, Danai Dima, David E. J. Linden, David M. A. Mehler, Edith Pomarol-Clotet, Elena Pozzi, Elisa Melloni, Francesco Benedetti, Frank P. MacMaster, Hans J. Grabe, Henry Völzke, Ian H. Gotlib, Jair C. Soares, Jennifer W. Evans, Kang Sim, Katharina Wittfeld, Kathryn Cullen, Liesbeth Reneman, Mardien L. Oudega, Margaret J. Wright, Maria J. Portella, Matthew D. Sacchet, Meng Li, Moji Aghajani, Mon-Ju Wu, Natalia Jaworska, Neda Jahanshad, Nic J. A. van der Wee, Nynke Groenewold, Paul J. Hamilton, Philipp Saemann, Robin Bülow, Sara Poletti, Sarah Whittle, Sophia I. Thomopoulos, Steven J. A. van, der Werff, Sheri-Michelle Koopowitz, Thomas Lancaster, Tiffany C. Ho, Tony T. Yang, Zeynep Basgoze, Dick J. Veltman, Lianne Schmaal, Paul M. Thompson, Roberto Goya-Maldonado

专题命中 BCI数据与评测 ：cortical(title)

Comments main document 37 pages; supplementary material 24 pages

Evaluation of selected recurrence measures in discriminating pre-ictal and inter-ictal periods from epileptic EEG data

Eulalie Joelle Ngamga, Stephan Bialonski, Norbert Marwan, Jürgen Kurths, Christian Geier, Klaus Lehnertz

专题命中 BCI数据与评测 ：EEG(title)

Comments 7 pages, 4 figures

Clear Mind: Meditation and the Brain's Signal-to-Noise Ratio

清晰心智：冥想与大脑的信噪比

Ruben Laukkonen

专题命中 BCI数据与评测 ：BCI(abstract_cn)；brain-computer interface(abstract)；分类 q-bio.NC

AI总结 提出冥想通过增强目标相关神经信号（信号）并减少无关波动（噪声）来提高大脑功能信噪比（f-SNR），从而解释冥想对多种心理病理的疗效并促进脑机接口发展。

EduGage: Methods and Dataset for Sensor-Based Momentary Assessment of Engagement in Self-Guided Video Learning

EduGage：基于传感器的自我引导视频学习中即时参与度评估的方法与数据集

Zikang Leng, Edan Eyal, Yingtian Shi, Jiaman He, Yaqi Liu, Thomas Plötz

机构 * School of Interactive Computing, Georgia Institute of Technology（佐治亚理工学院交互计算学院） ； College of Computing, Georgia Institute of Technology（佐治亚理工学院计算机学院） ； School of Computing Technologies, RMIT University（皇家墨尔本理工大学计算技术学院） 纠错

专题命中 BCI数据与评测 ：EEG(abstract,abstract_cn)；分类 cs.HC

AI总结 本文提出EduGage方法与数据集，通过可穿戴和摄像头设备收集生理和运动信号，评估学习者参与度，实验显示多模态建模在参与度评估中有效，且轻量级的生理与行为信号组合优于全多模态设备。

Immediate Derivatives Suffice for Online Recurrent Adaptation

即时导数足以支持在线递归适应

Aur Shalev Merin

机构 * Independent Researcher（独立研究者） 纠错

专题命中 BCI数据与评测 ：BCI(abstract,abstract_cn)；分类 cs.LG

AI总结 本文证明在线递归学习无需传播雅可比张量，通过即时导数实现与全RTRL相似的性能，展示了在不同优化器和网络结构下的有效性。

Comments 25 pages, 4 figures, 19 tables. Submitted to NeurIPS 2026

Forecasting Epileptic Seizures from Contactless Camera via Cross-Species Transfer Learning

通过无接触摄像头进行癫痫发作的跨物种迁移学习预测

Mingkai Zhai, Wei Wang, Zongsheng Li, Quanying Liu

专题命中 BCI数据与评测 ：EEG(abstract)；neural signal(abstract)；分类 cs.LG

AI总结 本文提出基于视频的癫痫发作预测任务，利用短预发作视频片段预测后续5秒内是否会发作，通过跨物种迁移学习利用大量啮齿类动物视频数据提升预测准确性，实验结果显示在纯视频设置下预测准确率超过70%。

Brain4FMs: A Benchmark of Foundation Models for Electrical Brain Signal

Brain4FMs: 一种用于电气脑信号基础模型的基准测试

Fanqi Shen, Enhong Yang, Jiahe Li, Junru Hong, Xiaoran Pan, Zhizhang Yuan, Meng Li, Yang Yang

机构 * Zhejiang University（浙江大学） ； Shanghai Institute of Microsystem and Information Technology, CAS（上海微系统与信息工程研究所，中国科学院） 纠错

专题命中 BCI数据与评测 ：EEG(abstract)；neural signal(abstract)；分类 cs.LG

AI总结 Brain4FMs提出了一种开放评估平台，用于评估和比较脑基础模型在电气脑信号处理中的性能和泛化能力。

Rethinking Self-Training Based Cross-Subject Domain Adaptation for SSVEP Classification

重新思考基于自训练的跨受体域适应用于SSVEP分类

Weiguang Wang, Yong Liu, Yingjie Gao, Guangyuan Xu

机构 * School of Artificial Intelligence, Beijing University of Posts and Telecommunications（人工智能学院，北京邮电大学） ； School of Computer Science and Technology, Beihang University（计算机科学与技术学院，北航） 纠错

专题命中 BCI数据与评测 ：BCI(abstract)；brain-computer interface(abstract)；分类 cs.LG

AI总结 本文提出了一种基于自训练的跨受体域适应方法，通过FBEA策略和CSST框架提升SSVEP分类性能。

Comments Accepted to ICASSP 2026

RISE-iEEG: Robust to Inter-Subject Electrodes Implantation Variability iEEG Classifier

RISE-iEEG: 适用于跨受试者电极植入变异的iEEG分类器

Maryam Ostadsharif Memar, Navid Ziaei, Behzad Nazari, Ali Yousefi

机构 * Department of Electrical and Computer Engineering, Isfahan University of Technology（电子与计算机工程系，伊斯法罕理工大学） ； Department of Biomedical Engineering, University of Houston（生物医学工程系，休斯顿大学） 纠错

专题命中 BCI数据与评测 ：brain-computer interface(abstract)；分类 q-bio.NC、eess.SP、cs.LG

AI总结 RISE-iEEG是一种针对跨受试者电极植入变异鲁棒的iEEG分类器，通过投影网络实现多受试者数据的通用解码，F1得分优于HTNet和EEGNet。

Journal ref 2025 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

ManifoldFormer: Geometric Deep Learning for Neural Dynamics on Riemannian Manifolds

ManifoldFormer: 用于黎曼流形上神经动态的几何深度学习

Yihang Fu, Lifang He, Qingyu Chen

机构 * Yale University（耶鲁大学） ； Lehigh University（莱斯利大学） 纠错

专题命中 BCI数据与评测 ：EEG(abstract)；neural signal(abstract)；分类 cs.LG

AI总结 ManifoldFormer通过几何深度学习框架，利用黎曼流形结构提升EEG信号的表示质量与跨受试者泛化能力。

Comments 5 pages, under review by ICASSP

Minimizing False-Positive Attributions in Explanations of Non-Linear Models

Anders Gjølbye, Stefan Haufe, Lars Kai Hansen

机构 * Technical University of Denmark（丹麦技术大学） ； Technische Universität Berlin（柏林技术大学） ； Physikalisch-Technische Bundesanstalt, Berlin（柏林物理技术部） ； Charité – Universitätsmedizin Berlin（柏林查理医院大学医学中心） 纠错

专题命中 BCI数据与评测 ：EEG(abstract)；motor imagery(abstract)；分类 cs.LG

Comments Accepted at NeurIPS 2025. Code: https://github.com/gjoelbye/PatternLocal

Navigate in Demanding Missions: Integrating Human Intelligence and Brain-Inspired Intelligence

Xu He, Xiaolin Meng, Youdong Zhang, Lingfei Mo, Wenxuan Yin

专题命中 BCI数据与评测 ：BCI(abstract)；brain-computer interface(abstract)；分类 cs.HC

RATE: An LLM-Powered Retrieval Augmented Generation Technology-Extraction Pipeline

Karan Mirhosseini, Arya Aftab, Alireza Sheikh

机构 * Dept. of Management, Science and Technology（管理、科学与技术系） ； Amirkabir University of Technology（阿姆尔卡比尔科技大学） ； Dept. of Electrical Engineering（电气工程系） ； Sharif University of Technology（沙里夫科技大学） 纠错

专题命中 BCI数据与评测 ：BCI(abstract)；brain-computer interface(abstract)；分类 cs.LG

Comments 9 pages, 4 figures, 1 table

The 2025 PNPL Competition: Speech Detection and Phoneme Classification in the LibriBrain Dataset

Gilad Landau, Miran Özdogan, Gereon Elvers, Francesco Mantegna, Pratik Somaiya, Dulhan Jayalath, Luisa Kurth, Teyun Kwon, Brendan Shillingford, Greg Farquhar, Minqi Jiang, Karim Jerbi, Hamza Abdelhedi, Yorguin Mantilla Ramos, Caglar Gulcehre, Mark Woolrich, Natalie Voets, Oiwi Parker Jones

机构 * PNPL ； Google DeepMind（谷歌DeepMind） ； MetaAI ； Mila ； Université de Montréal（蒙特利尔大学） ； EPFL（苏黎世联邦理工学院） ； OHBA ； WIN N University of Oxford（WIN N 奥xford大学） 纠错

专题命中 BCI数据与评测 ：brain-computer interface(abstract)；neural decoding(abstract)；分类 cs.LG

Journal ref NeurIPS 2025 Competition Track

Teaching Wav2Vec2 the Language of the Brain

Tobias Fiedler, Leon Hermann, Florian Müller, Sarel Cohen, Peter Chin, Tobias Friedrich, Eilon Vaadia

专题命中 BCI数据与评测 ：BCI(abstract)；brain computer interface(abstract)；分类 cs.LG

Comments Paper was submitted to ICASSP 2025 but marginally rejected

Effective and Efficient Intracortical Brain Signal Decoding with Spiking Neural Networks

Haotian Fu, Peng Zhang, Song Yang, Herui Zhang, Ziwei Wang, Dongrui Wu

专题命中 BCI数据与评测 ：BCI(abstract)；brain-computer interface(abstract)；分类 cs.HC

A Simple Channel Compression Method for Brain Signal Decoding on Classification Task

Changqing Ji, Keisuke Kawasaki, Isao Hasegawa, Takayuki Okatani

专题命中 BCI数据与评测 ：BCI(abstract)；brain-computer interface(abstract)；分类 q-bio.NC

Comments Method in this work is not enough, we need to merge our previous work together, create a whole scale of our work