脑机接口 / BCI

Disentangled and Side-aware Unsupervised Domain Adaptation for Cross-dataset Subjective Tinnitus Diagnosis

Yun Li, Zhe Liu, Lina Yao, Jessica J. M. Monaghan, David McAlpine

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

Self-supervised Learning for Label-Efficient Sleep Stage Classification: A Comprehensive Evaluation

Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, Xiaoli Li

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

Comments Under Review. This document contains 9 pages as a main text, and 2 pages for supplementary materials

Force-Aware Interface via Electromyography for Natural VR/AR Interaction

Yunxiang Zhang, Benjamin Liang, Boyuan Chen, Paul Torrens, S. Farokh Atashzar, Dahua Lin, Qi Sun

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

Comments ACM Transactions on Graphics (SIGGRAPH Asia 2022)

Too Fine or Too Coarse? The Goldilocks Composition of Data Complexity for Robust Left-Right Eye-Tracking Classifiers

Brian Xiang, Abdelrahman Abdelmonsef

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

Comments arXiv admin note: text overlap with arXiv:2208.00465

Transfer learning to decode brain states reflecting the relationship between cognitive tasks

Youzhi Qu, Xinyao Jian, Wenxin Che, Penghui Du, Kai Fu, Quanying Liu

专题命中 BCI数据与评测 ：neural decoding(abstract)；分类 q-bio.NC、cs.LG

Classifier Transfer with Data Selection Strategies for Online Support Vector Machine Classification with Class Imbalance

Mario Michael Krell, Nils Wilshusen, Anett Seeland, Su Kyoung Kim

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

Journal ref Journal of Neural Engineering 14 2 (2017) 025003

Wavelet-Based Multi-Class Seizure Type Classification System

Hezam Albaqami, Ghulam Mubashar Hassan, Amitava Datta

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

IFTT-PIN: A PIN-Entry Method Leveraging the Self-Calibration Paradigm

Jonathan Grizou

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

Side-aware Meta-Learning for Cross-Dataset Listener Diagnosis with Subjective Tinnitus

Yun Li, Zhe Liu, Lina Yao, Molly Lucas, Jessica J. M. Monaghan, Yu Zhang

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

Low Latency Real-Time Seizure Detection Using Transfer Deep Learning

Vahid Khalkhali, Nabila Shawki, Vinit Shah, Meysam Golmohammadi, Iyad Obeid, Joseph Picone

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

Robust alignment of cross-session recordings of neural population activity by behaviour via unsupervised domain adaptation

Justin Jude, Matthew G Perich, Lee E Miller, Matthias H Hennig

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

ICLabel: An automated electroencephalographic independent component classifier, dataset, and website

Luca Pion-Tonachini, Ken Kreutz-Delgado, Scott Makeig

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

Comments Intended for NeuroImage. Updated from version one with minor editorial and figure changes

EEGEyeNet: a Simultaneous Electroencephalography and Eye-tracking Dataset and Benchmark for Eye Movement Prediction

Ard Kastrati, Martyna Beata Płomecka, Damián Pascual, Lukas Wolf, Victor Gillioz, Roger Wattenhofer, Nicolas Langer

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

Comments Published at NeurIPS 2021 Datasets and Benchmarks Track

Adaptive Gaussian Fuzzy Classifier for Real-Time Emotion Recognition in Computer Games

Daniel Leite, Volnei Frigeri, Rodrigo Medeiros

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

Comments 7 pages, 6 figures, Fuzz-IEEE 2021, Luxembourg

Evaluation of Non-Collocated Force Feedback Driven by Signal-Independent Noise

Zonghe Chua, Allison M. Okamura, Darrel R. Deo

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

Comments Accepted to ICRA 2020

Tangent space spatial filters for interpretable and efficient Riemannian classification

Jiachen Xu, Moritz Grosse-Wentrup, Vinay Jayaram

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

Attention Monitoring and Hazard Assessment with Bio-Sensing and Vision: Empirical Analysis Utilizing CNNs on the KITTI Dataset

Siddharth, Mohan M. Trivedi

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

Comments Accepted for publication at IEEE Intelligent Vehicles Symposium 2019

Automatic Emotion Recognition (AER) System based on Two-Level Ensemble of Lightweight Deep CNN Models

Emad-ul-Haq Qazi, Muhammad Hussain, Hatim AboAlsamh, Ihsan Ullah

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

1D Convolutional Neural Network Models for Sleep Arousal Detection

Morteza Zabihi, Ali Bahrami Rad, Serkan Kiranyaz, Simo Särkkä, Moncef Gabbouj

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

Comments 10 pages, 6 figures

Adversarial Domain Adaptation for Stable Brain-Machine Interfaces

Ali Farshchian, Juan A. Gallego, Joseph P. Cohen, Yoshua Bengio, Lee E. Miller, Sara A. Solla

专题命中 BCI数据与评测 ：neural signal(abstract)；分类 q-bio.NC、cs.LG

Comments 14 pages, 6 figures

Decoding Generic Visual Representations From Human Brain Activity using Machine Learning

Angeliki Papadimitriou, Nikolaos Passalis, Anastasios Tefas

专题命中 BCI数据与评测 ：neural decoding(abstract)；分类 q-bio.NC、cs.LG

Comments Accepted at 1st Workshop on Brain-Driven Computer Vision - ECCV 2018

AMIGOS: A Dataset for Affect, Personality and Mood Research on Individuals and Groups

Juan Abdon Miranda-Correa, Mojtaba Khomami Abadi, Nicu Sebe, Ioannis Patras

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

Comments 14 pages, Transaction on Affective Computing

The Neural Representation Benchmark and its Evaluation on Brain and Machine

Charles F. Cadieu, Ha Hong, Dan Yamins, Nicolas Pinto, Najib J. Majaj, James J. DiCarlo

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

Comments The v1 version contained incorrectly computed kernel analysis curves and KA-AUC values for V4, IT, and the HT-L3 models. They have been corrected in this version

Subject Selection on a Riemannian Manifold for Unsupervised Cross-subject Seizure Detection

Samaneh Nasiri Ghosheh Bolagh, Gari. D. Clifford

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

Comments Cross-Subject Learning, Inter-Subject Variability, Unsupervised Subject-Selection, Riemannian Manifold, Seizure Detection, EEG, NIPS ML4H 2017

Predicted Cortex Is Not a Domain-General Prior: A Matched-Control Audit of Brain-Encoding Features for Video Memorability

这取决于数据集：当大脑编码模型的预测响应在视频记忆性方面超过其视觉主干时

Carson Rodrigues

机构 * Celabe（赛拉贝） 纠错

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

AI总结 研究大脑编码模型预测响应能否用于预测短视频记忆性，通过将视频片段投影到特定皮质空间并用岭回归预测，发现结果取决于数据集，大脑投影在VideoMem数据集表现更佳，且携带特定记忆信号，不是通用先验知识。

Comments 11 pages, 3 figures. v4: retitled; adds a dataset-by-representation interaction test (+0.097, 95% CI [+0.032,+0.160], p=0.001) and seed stability for both datasets, replacing the earlier claim that both within-dataset intervals excluded zero (the Memento10k bound was -0.0003); discloses that the pre-specified hypothesis returned NO-GO; adds a regularization-grid check

Cross-Subject Semantic Decoding with Shared-Space Alignment for Generalized Neural Representation Learning

基于共享空间对齐的跨主体语义解码用于广义神经表征学习

Ji-Hoon Heo, Aleksandra Joanna Wisniewska, Seo-Hyun Lee, Seong-Whan Lee

机构 * Korea University（韩国大学） 纠错

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

AI总结 研究针对侵入性神经记录跨主体泛化难题，提出跨主体语义解码框架，通过将多主体神经反应对齐到共享潜在空间并学习映射，经实验验证该框架优于基线方法，能有效提升跨主体泛化能力。

CG-MambaNet: A spatiotemporal framework for cross-patient epileptic seizure prediction using CNN-GCN-Mamba-BiLSTM with event-level clinical evaluation

CG-MambaNet: 基于CNN-GCN-Mamba-BiLSTM的跨患者癫痫发作预测时空框架及事件级临床评估

Mufeng Chen, Qi Wu, Bingchao Huang, Xiwen Lai, Zekai Chen, Xinge Ouyang, Tingyao Zhang, Xufang Yang, Quansheng Ren

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

AI总结 提出CG-MambaNet框架，通过CNN提取多尺度频谱特征、GCN建模通道间功能同步、Mamba与BiLSTM捕获长短期时序，在严格留一患者交叉验证下实现跨患者癫痫发作预测，优于现有方法，并引入事件级评估降低误报率。

Cross-Session Decoding of Neural Spiking Data via Task-Conditioned Latent Alignment

通过任务条件潜在对齐实现跨会话神经脉冲数据解码

Canyang Zhao, Bolin Peng, J. Patrick Mayo, Ce Ju, Bing Liu

机构 * Institute of Automation, Chinese Academy of Sciences（自动化研究所，中国科学院） ； Departments of Ophthalmology and Bioengineering, University of Pittsburgh（眼科学与生物工程系，匹兹堡大学） ； Inria, CEA, Université Paris-Saclay（法国国家科学研究中心（Inria）、法国国家科学研究中心（CEA）、巴黎萨克雷大学） 纠错

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

AI总结 本文提出TCLA框架，通过任务条件潜在对齐在有限目标会话数据下提升神经解码性能，实验显示在运动和眼动皮层数据集上解码效果显著提升。

Comments This work has been accepted by the Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2026);Copyright will be transferred without notice, after which this version may no longer be accessible

Modeling Higher-Order Brain Interactions via a Multi-View Information Bottleneck Framework for fMRI-based Psychiatric Diagnosis

通过多视图信息瓶颈框架建模高阶脑相互作用用于基于fMRI的精神疾病诊断

Kunyu Zhang, Qiang Li, Vince D. Calhoun, Shujian Yu

机构 * Department of Computer Science, Vrije Universiteit Amsterdam（范德比大学计算机科学系） ； Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS)（神经影像与数据科学转化研究中心） ； Georgia State University（佐治亚州立大学） ； Georgia Institute of Technology（佐治亚理工学院） ； Emory University（埃默里大学） ； Department of Physics and Technology, UiT - The Arctic University of Norway（北挪威大学物理与技术系） 纠错

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

AI总结 本文提出O信息度量，用于建模高阶脑相互作用，结合三阶和四阶O信息，通过多视图信息瓶颈框架提升fMRI精神疾病诊断性能，实验表明优于11种基线方法，揭示可解释的区域协同-冗余模式。

Seeing the imagined: a latent functional alignment in visual imagery decoding from fMRI data

看见想象：从fMRI数据中通过潜在功能对齐解码视觉意象

Fabrizio Spera, Tommaso Boccato, Michal Olak, Sara Cammarota, Matteo Ciferri, Michelangelo Tronti, Nicola Toschi, Matteo Ferrante

机构 * Department of Biomedicine and Prevention, University of Rome Tor Vergata（罗马特拉维拉大学生物医学与预防系） ； Tether Evo ； A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital（马萨诸塞总医院生物医学成像中心） 纠错

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

AI总结 本文研究如何将最先进的感知解码器适应于从Imagery-NSD基准中重建想象内容，提出潜在功能对齐方法以提升高阶语义重构指标。