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

RpoE mediates environmental stress tolerance and biofilm formation in foodborne <i>Staphylococcus</i> <i>aureus</i>.

Current research in food science·2026
Same author

Electromagnetic Exposure Assessment of 5G Mobile Phones: SAR and Thermal Distribution in a Multi-Layer Human Head Model.

Sensors (Basel, Switzerland)·2026
Same author

Reliability-Based Recycling of Reclaimed Asphalt Pavement Using a t-Distribution Guarantee Rate Method and a Ternary Composite Rejuvenation System.

Materials (Basel, Switzerland)·2026
Same author

[Electroencephalogram signals decomposition based on improved variational mode decomposition for depression recognition].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi·2026
Same author

From Pre-Swelling to Performance Enhancement: Mechanisms and Effects of an Instant Ultra High-Performance Bituminous Material Modifier.

Materials (Basel, Switzerland)·2026
Same author

Impact of a 24/7 on-site percutaneous coronary intervention team strategy on door-to-wire time.

BMJ open quality·2025
Same journal

Multimodal Contrastive Spatiotemporal Self-Organizing Neural Networks for In-Home Activity Learning of Mild Cognitive Impairment.

IEEE journal of biomedical and health informatics·2026
Same journal

Integrating Multi-View Residue Graph and Protein Language Model for Cell-Penetrating Peptide Prediction via Global-Local Graph Aggregation and Cross-Attentive Fusion.

IEEE journal of biomedical and health informatics·2026
Same journal

An Ultra-Lightweight Cross-scale Attention Mamba Network for Accurate Skin Lesion Segmentation.

IEEE journal of biomedical and health informatics·2026
Same journal

Explanation-Guided Reconstruction of Missing Clinical Features for Survival Prediction in Pancreatic Cancer.

IEEE journal of biomedical and health informatics·2026
Same journal

stDGCN: A dual-augmentation graph convolutional network for identifying spatial domains with attention mechanism.

IEEE journal of biomedical and health informatics·2026
Same journal

Patient-specific Biomechanical Investigation of Percutaneous Pulmonary Valves: Towards the Integration of Routinely Acquired Clinical Data and Fluid-structure Interaction Simulations.

IEEE journal of biomedical and health informatics·2026
查看所有相关文章

相关实验视频

Updated: May 9, 2025

Author Spotlight: Therapeutic Benefit of Closed-Loop Deep Brain Stimulation in Depression Treatment
05:19

Author Spotlight: Therapeutic Benefit of Closed-Loop Deep Brain Stimulation in Depression Treatment

Published on: July 7, 2023

2.1K

双散式基于字典的脑电图频道选择用于抑郁症分析.

Bingtao Zhang, Chonghui Wang, Na Chen

    IEEE journal of biomedical and health informatics
    |May 5, 2025
    PubMed
    概括
    此摘要是机器生成的。

    这项研究引入了一种新的弹性网方法,用于选择关键的脑电图 (EEG) 通道进行抑郁症分析,识别大脑功能网络的变化并减少计算负载.

    更多相关视频

    Cortical Source Analysis of High-Density EEG Recordings in Children
    09:32

    Cortical Source Analysis of High-Density EEG Recordings in Children

    Published on: June 30, 2014

    21.2K
    Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis
    08:22

    Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis

    Published on: April 26, 2024

    1.5K

    相关实验视频

    Last Updated: May 9, 2025

    Author Spotlight: Therapeutic Benefit of Closed-Loop Deep Brain Stimulation in Depression Treatment
    05:19

    Author Spotlight: Therapeutic Benefit of Closed-Loop Deep Brain Stimulation in Depression Treatment

    Published on: July 7, 2023

    2.1K
    Cortical Source Analysis of High-Density EEG Recordings in Children
    09:32

    Cortical Source Analysis of High-Density EEG Recordings in Children

    Published on: June 30, 2014

    21.2K
    Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis
    08:22

    Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis

    Published on: April 26, 2024

    1.5K

    科学领域:

    • 神经科学是一个神经科学.
    • 信号处理 信号处理
    • 计算生物学 计算生物学

    背景情况:

    • 高密度脑电图 (EEG) 分析抑郁症 (DP) 面临的挑战是道冗余和计算复杂性.
    • 在DP患者中识别核心大脑功能网络 (BFNs) 对于理解疾病机制至关重要.

    研究的目的:

    • 提出一种基于弹性网的双稀疏字典通道选择 (EN-DSDCS) 方法,用于抑郁症中高效的EEG分析.
    • 确定关键的EEG通道并分析DP患者BFN的拓变化.
    • 与现有方法相比,以减少信号重建错误和频道稀疏性.

    主要方法:

    • 一种改进的粗粒度方法重建了EEG信号并计算了多尺度顺序 (MSPE).
    • 使用DCT矩阵创建一个双稀疏字典结构,并通过稀疏K-SVD进行优化.
    • 弹性网规则化用于词典和稀疏系数的联合优化,使道选择成为可能.

    主要成果:

    • 通过EN-DSDCS方法,信号重建误差减少了3x10^-4.
    • 与基于Lasso的方法 (L-DSDCS) 相比,通道稀疏度减少了3.93%.
    • 选择的道主要位于额叶和叶,揭示了在DP患者中Hub节点分布的差异连接和左半球偏差.

    结论:

    • 该EN-DSDCS方法有效地识别核心EEG通道,并分析抑郁症中的BFN变化.
    • 这些发现突出了DP患者大脑中特定的拓变化和连接模式.
    • 这种方法为基于EEG的抑郁症研究提供了一种更高效,更准确的计算方法.