脑机接口 / BCI

A Novel Method for Epileptic Seizure Detection Using Coupled Hidden Markov Models

Jeff Craley, Emily Johnson, Archana Venkataraman

专题命中 EEG解码 ：EEG(abstract)；分类 q-bio.NC、eess.SP

Comments To appear in MICCAI 2018 Proceedings

Cerebral Signal Instantaneous Parameters Estimation MATLAB Toolbox - User Guide Version 2.3

Esmaeil Seraj

专题命中 EEG解码 ：EEG(abstract)；分类 q-bio.NC、cs.HC

Deep Classification of Epileptic Signals

David Ahmedt-Aristizabal, Clinton Fookes, Kien Nguyen, Sridha Sridharan

专题命中 EEG解码 ：EEG(abstract)；分类 q-bio.NC、cs.LG

Comments 4 pages, 3 figures

Journal ref In Proceedings of the IEEE International Conference of Engineering in Medicine and Biology Society. 2018

A new approach for a safe car assistance system

Mejdi Ben Dkhil, Mohamed Neji, Ali Wali, Adel M. Alimi

专题命中 EEG解码 ：EEG(abstract)；分类 eess.SP、cs.HC

The Temple University Hospital Seizure Detection Corpus

Vinit Shah, Eva von Weltin, Silvia Lopez, James Riley McHugh, Lily Veloso, Meysam Golmohammadi, Iyad Obeid, Joseph Picone

专题命中 EEG解码 ：EEG(abstract)；分类 q-bio.NC、eess.SP

Comments Under review in Frontiers in Neuroscience

An Analysis of Two Common Reference Points for EEGs

Silvia Lopez, Aaron Gross, Scott Yang, Meysam Golmohammadi, Iyad Obeid, Joseph Picone

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

Comments Published In IEEE Signal Processing in Medicine and Biology Symposium. Philadelphia, Pennsylvania, USA

Journal ref S. Lopez, A. Gross, S. Yang, M. Golmohammadi, I. Obeid and J. Picone, "An analysis of two common reference points for EEGS," 2016 IEEE Signal Processing in Medicine and Biology Symposium (SPMB), Philadelphia, PA, 2016, pp. 1-5

Optimizing Channel Selection for Seizure Detection

Vinit Shah, Meysam Golmohammadi, Saeedeh Ziyabari, Eva Von Weltin, Iyad Obeid, Joseph Picone

专题命中 EEG解码 ：EEG(abstract)；分类 q-bio.NC、eess.SP

Comments Published in Dec 2017 publication IEEE Signal Processing in Medicine and Biology Symposium. Philadelphia, Pennsylvania, USA

Mixed Neural Network Approach for Temporal Sleep Stage Classification

Hao Dong, Akara Supratak, Wei Pan, Chao Wu, Paul M. Matthews, Yike Guo

专题命中 EEG解码 ：EEG(abstract)；分类 q-bio.NC、cs.LG

Comments THIS ARTICLE HAS BEEN PUBLISHED IN IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING

Loss impresses human beings more than gain in the decision-making game

Jia Quan Shen, Luo-Luo Jiang

专题命中 EEG解码 ：EEG(abstract)；分类 q-bio.NC、cs.HC

Comments 11pages, 5 figure

The intrinsic value of HFO features as a biomarker of epileptic activity

Stephen V. Gliske, Kevin R. Moon, William C. Stacey, Alfred O. Hero

专题命中 EEG解码 ：EEG(abstract)；分类 q-bio.NC、cs.LG

Comments 5 pages, 5 figures

Journal ref IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 6290-6294, Mar. 2016

Alternative Modes of Interaction in Proximal Human-in-the-Loop Operation of Robots

Tathagata Chakraborti, Sarath Sreedharan, Anagha Kulkarni, Subbarao Kambhampati

专题命中 EEG解码 ：EEG(abstract)；分类 cs.HC、cs.RO

Toward improving the visual stimulus meaning for increasing the P300 detection

Hubert Cecotti, Bertrand Rivet

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

Comments 11 pages

Natural brain-information interfaces: Recommending information by relevance inferred from human brain signals

Manuel J. A. Eugster, Tuukka Ruotsalo, Michiel M. Spapé, Oswald Barral, Niklas Ravaja, Giulio Jacucci, Samuel Kaski

专题命中 EEG解码 ：EEG(abstract)；分类 q-bio.NC、cs.HC

Journal ref Scientific Reports 6, Article number: 38580 (2016)

Separating Components of Attention and Surprise

Per Bækgaard, Michael Kai Petersen, Jakob Eg Larsen

专题命中 EEG解码 ：EEG(abstract)；分类 q-bio.NC、cs.HC

Comments 13 pages, 10 figures

Multimodal Emotion Recognition Using Multimodal Deep Learning

Wei Liu, Wei-Long Zheng, Bao-Liang Lu

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

Causal interpretation rules for encoding and decoding models in neuroimaging

Sebastian Weichwald, Timm Meyer, Ozan Özdenizci, Bernhard Schölkopf, Tonio Ball, Moritz Grosse-Wentrup

专题命中 EEG解码 ：EEG(abstract)；分类 q-bio.NC、cs.LG

Comments accepted manuscript

Journal ref NeuroImage, 110:48-59, 2015

Quantifying the Dynamics of Consciousness using Hierarchical Integration, Organised Complexity and Metastability

利用分层整合、有序复杂性和 metastability 量化意识的动力学

Hassan Ugail, Newton Howard

专题命中 EEG解码 ：EEG(abstract,comments)；分类 q-bio.NC

AI总结 本文提出一种理论中立的框架，通过分层整合、有序复杂性和 metastability 量化意识相关的神经动态，验证了其在不同脑状态下的有效性。

Comments This paper presents a computational neuroscience framework for quantifying neural integrative dynamics using a composite index. We validate the method on synthetic data and Sleep-EDF EEG across Wake, N2, and REM, using DFA, LZC, PAC, MI, and synchrony measures. Intended for q-bio.NC

The 1st International Workshop on Disentangled Representation Learning for Controllable Generation (DRL4Real): Methods and Results

Qiuyu Chen, Xin Jin, Yue Song, Xihui Liu, Shuai Yang, Tao Yang, Ziqiang Li, Jianguo Huang, Yuntao Wei, Ba'ao Xie, Nicu Sebe, Wenjun, Zeng, Jooyeol Yun, Davide Abati, Mohamed Omran, Jaegul Choo, Amir Habibian, Auke Wiggers, Masato Kobayashi, Ning Ding, Toru Tamaki, Marzieh Gheisari, Auguste Genovesio, Yuheng Chen, Dingkun Liu, Xinyao Yang, Xinping Xu, Baicheng Chen, Dongrui Wu, Junhao Geng, Lexiang Lv, Jianxin Lin, Hanzhe Liang, Jie Zhou, Xuanxin Chen, Jinbao Wang, Can Gao, Zhangyi Wang, Zongze Li, Bihan Wen, Yixin Gao, Xiaohan Pan, Xin Li, Zhibo Chen, Baorui Peng, Zhongming Chen, Haoran Jin

专题命中 EEG解码 ：EEG(abstract,comments)；分类 cs.LG

Comments Workshop summary paper for ICCV 2025, 9 accepted papers, 9 figures, IEEE conference format, covers topics including diffusion models, controllable generation, 3D-aware disentanglement, autonomous driving applications, and EEG analysis

Cognitive Load-Driven VR Memory Palaces: Personalizing Focus and Recall Enhancement

Zhengyang Li, Hailin Deng

专题命中 EEG解码 ：EEG(abstract,comments)；分类 cs.HC

Comments 10 pages, 5 figures, submitted to HCII 2025. Includes EEG-based VR adaptation experiments, dynamic spatial modeling, and empirical evaluation of memory performance

Real-time noise cancellation with Deep Learning

Bernd Porr, Sama Daryanavard, Lucía Muñoz Bohollo, Henry Cowan, Bernd Porr, Ravinder Dahiya

专题命中 EEG解码 ：EEG(abstract,comments)；分类 eess.SP

Comments 21 pages, 4 figures, code available under https://doi.org/10.5281/zenodo.7100537 and EEG data available here: https://researchdata.gla.ac.uk/1258/

How does artificial intelligence contribute to iEEG research?

Julia Berezutskaya, Anne-Lise Saive, Karim Jerbi, Marcel van Gerven

专题命中 EEG解码 ：brain-computer interface(abstract)；分类 q-bio.NC；EEG(comments)

Comments This chapter is forthcoming in Intracranial EEG for Cognitive Neuroscience (book)

Differentiating resting brain states using ordinal symbolic analysis

C. Quintero-Quiroz, Luis Montesano, A. J. Pons, M. C. Torrent, J. García-Ojalvo, C. Masoller

专题命中 EEG解码 ：EEG(abstract,comments)；分类 q-bio.NC

Comments time series analysis, ordinal analysis, EEG, brain dynamics

Electroencephalographic field influence on calcium momentum waves

Lester Ingber, Marco Pappalepore, Ronald R. Stesiak

专题命中 EEG解码 ：EEG(abstract,comments)；分类 q-bio.NC

Comments Final draft. http://ingber.com/smni14_eeg_ca.pdf may be updated more frequently

Phase-based spatial ordinal patterns for characterizing oscillatory dynamics

用于表征振荡动力学的基于相位的空间序贯模式

Robison J. Santos-Silva, Bruno R. R. Boaretto, Thiago L. Prado, Roberto C. Budzinski

专题命中 EEG解码 ：EEG(abstract)；分类 q-bio.NC

AI总结 本研究提出基于相位的空间序贯模式框架，定义空间置换熵，可表征振荡系统时空动力学，区分锁相状态与部分同步状态，在合成网络和人脑电数据上验证了方法有效性。

AMICA-Python: Adaptive Mixture Independent Component Analysis with Anderson Acceleration

AMICA-Python：具有安德森加速的自适应混合独立成分分析

Scott Huberty, Christian O'Reilly

机构 * University of Southern California（南加州大学） ； University of South Carolina（南卡罗来纳大学） 纠错

专题命中 EEG解码 ：EEG(abstract)；分类 cs.LG

AI总结 研究针对AMICA算法依赖单一Fortran实现、限制其在非MATLAB生态系统中应用的问题，提出AMICA-Python这一Python实现，通过符合scikit-learn的API集成，引入安德森加速方案，经测试其数值精度高、运行时具竞争力。

EEGPrep: a validated Python implementation of the EEGLAB preprocessing pipeline

EEGPrep：EEGLAB预处理管道的经过验证的Python实现

Arnaud Delorme, Suraj Ranganath, Christian Kothe, Aman Jaiswal, Scott Makeig, Bruno Aristimunha

专题命中 EEG解码 ：EEG(abstract)；分类 eess.SP

AI总结 研究旨在解决EEGLAB管道MATLAB实现不利于Python和云工作流部署的问题，开发EEGPrep在Python中重现该管道，经测试其能高精度重现EEGLAB管道，可从PyPI安装或在Docker中运行。

Brain-Aligned Multi-Stream Video Transformers with Sparse Self-Selection

具有稀疏自选择的脑对齐多流视频变换器

Amir Hosein Fadaei, Mahyar Maleki, Mohammad-Reza A. Dehaqani

机构 * University of Tehran（德黑兰大学） 纠错

专题命中 EEG解码 ：EEG(abstract)；分类 cs.LG

AI总结 研究针对现代视频变换器忽视灵长类视觉原理及缺乏神经数据评估的问题，提出含稀疏胜者全得令牌选择模块的脑对齐多流视频变换器，经实验其在精度与推理时间上表现优且鲁棒性强，脑模型相关性高，优于基线。

Comments 23 pages, 11 figures

TVGL-CFM:Generating and Forecasting Time-Varying Trajectories of Dynamic Networks with Conditional Flow Matching

TVGL-CFM：通过条件流匹配生成和预测动态网络的时变轨迹

Om Roy, Yashar Moshfeghi, Keith Malcolm Smith

机构 * University of Strathclyde（斯特拉斯克莱德大学） 纠错

专题命中 EEG解码 ：EEG(abstract)；分类 cs.LG

AI总结 研究针对脑网络等随时间变化的复杂系统，提出TVGL-CFM模型，通过对数欧几里得图和条件流匹配，可生成和预测时变网络轨迹，在多数据集上表现优于原始信号基线，直接生成结构化精度轨迹更可靠。

PhasorFlow: A Python Library for Unit Circle Based Computing

PhasorFlow：基于单位圆的计算Python库

Dibakar Sigdel, Namuna Panday

机构 * Mindverse Computing LLC 纠错

专题命中 EEG解码 ：EEG(abstract)；分类 cs.LG

AI总结 PhasorFlow基于单位圆提出新的计算范式，通过复数相位编码和单位波干涉门实现连续几何梯度预测学习，提供Phasor Circuit模型、变分相位电路和相位变换器三大贡献，验证了其在非线性分类、时间序列预测等任务中的有效性。

Linear Independent Component Analysis via Optimal Transport

通过最优传输进行线性独立成分分析

Ashutosh Jha, Michel Besserve, Simon Buchholz

机构 * University of Tübingen（图宾根大学） ； Max Planck Institute for Intelligent Systems, Tübingen（图宾根马克斯·普朗克智能系统研究所） ； Institute of Artificial Intelligence TU Braunschweig（布伦瑞克工业大学人工智能研究所） 纠错

专题命中 EEG解码 ：EEG(abstract)；分类 cs.LG

AI总结 研究如何从线性混合信号中恢复独立源信号，提出用平方瓦瑟斯坦距离衡量非高斯性，基于此构建OT - ICA算法，实验表明该算法在不同分布上优于传统方法，且可用于无分布假设的应用ICA任务。