Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Long-term care plan recommendation for older adults with disabilities: a bipartite graph transformer and self-supervised approach.

Journal of the American Medical Informatics Association : JAMIA·2025
Same author

A Protocol for Digitalized Collection of Traditional Chinese Medicine (TCM) Pulse Information Using Bionic Pulse Diagnosis Equipment.

Phenomics (Cham, Switzerland)·2023
Same author

Technical and Clinical Progress on Robot-Assisted Endovascular Interventions: A Review.

Micromachines·2023
Same author

An iPPG-Based Device for Pervasive Monitoring of Multi-Dimensional Cardiovascular Hemodynamics.

Sensors (Basel, Switzerland)·2021
Same author

Expression of tissue factor pathway inhibitor-2 in gastric stromal tumor and its clinical significance.

Experimental and therapeutic medicine·2014
Same author

Facile access to cytocompatible multicompartment micelles with adjustable Janus-cores from A-block-B-graft-C terpolymers prepared by combination of ROP and ATRP.

Colloids and surfaces. B, Biointerfaces·2014
Same journal

Cortex-anchored sensor-space harmonics for event-related EEG.

Journal of neural engineering·2026
Same journal

Neural mechanisms of mixed speech and grasp representation in sensorimotor cortices.

Journal of neural engineering·2026
Same journal

Developing a binary communication protocol between biological neural networks using virtual white matter.

Journal of neural engineering·2026
Same journal

Spatiotemporally distinctive astrocytic and neuronal responses to repetitive intracortical microstimulation.

Journal of neural engineering·2026
Same journal

A neural mass modelling framework for evaluating EEG source localisation of seizure activity.

Journal of neural engineering·2026
Same journal

Functional and effective connectivity methods from SEEG for characterizing epileptogenic networks in refractory epilepsy: a comprehensive review and future directions.

Journal of neural engineering·2026
查看所有相关文章

相关实验视频

Updated: Jan 14, 2026

Recording Human Electrocorticographic ECoG Signals for Neuroscientific Research and Real-time Functional Cortical Mapping
13:32

Recording Human Electrocorticographic ECoG Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

Published on: June 26, 2012

26.7K

基础模型用于EEG解码:目前的进展和未来的研究成果.

Yuxuan Yao1,2, Hongbo Wang1,2,3, Li Chen1,3

  • 1Institute of AI and Robotics, Academy for Engineering and Technology, Fudan University, Shanghai 200433, People's Republic of China.

Journal of neural engineering
|October 27, 2025
PubMed
概括
此摘要是机器生成的。

EEG基础模型 (EEG FMs) 提供了一种统一的方法来解码大脑活动,超越监督学习的限制. 本综述分析了目前的EEG FM趋势,并建议未来的研究方向,以提高性能.

关键词:
深度学习是一种深度学习.电脑电图 (EEG) 是一种电脑电图.基础模型的基础模型.预先培训的培训前培训自主监督学习学习

更多相关视频

Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
11:25

Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

Published on: July 26, 2013

44.0K
A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants
11:14

A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants

Published on: October 4, 2015

11.4K

相关实验视频

Last Updated: Jan 14, 2026

Recording Human Electrocorticographic ECoG Signals for Neuroscientific Research and Real-time Functional Cortical Mapping
13:32

Recording Human Electrocorticographic ECoG Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

Published on: June 26, 2012

26.7K
Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
11:25

Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

Published on: July 26, 2013

44.0K
A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants
11:14

A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants

Published on: October 4, 2015

11.4K

科学领域:

  • 神经科学和人工智能 人工智能
  • 大脑与计算机的接口.
  • 机器学习用于神经成像.

背景情况:

  • 传统的脑电图 (EEG) 解码方法在任务特异性和数据集依赖性方面存在局限性.
  • 深度学习越来越多地应用于EEG解码,但监督方法限制了模型的泛化.
  • 灵感来自大型语言模型的EEG基础模型 (EEG FMs),为EEG解码提供了一个统一的范式.

研究的目的:

  • 审查对EEG基础模型 (EEG FMs) 的代表性研究.
  • 提取EEG FM开发和应用中的趋势.
  • 为未来的EEG FM研究提供建议.

主要方法:

  • 对EEG FMs近期进展的全面分析.
  • 专注于下游任务,基准数据集,模型架构和预培训技术.
  • 核心FM组件,性能和通用性的系统比较.

主要成果:

  • EEG FM在大型数据集 (最多14987名受试者,27062小时) 上进行了预训练.
  • 基于面具的重建和基于变压器的架构是常见的预训练策略.
  • EEG FM显示在发作检测方面有潜力,但在复杂的任务 (如运动图像解码) 中性能有限.

结论:

  • EEG FM代表了EEG解码的重大进步,提供了更好的泛化.
  • 目前存在的局限性,特别是在复杂的认知任务.
  • 需要进一步的研究来增强EEG FM的能力,并应对当前的挑战.