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

Protein Networks02:26

Protein Networks

3.9K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
3.9K
Kendall's Coefficient of Concordance01:20

Kendall's Coefficient of Concordance

214
Kendall's Coefficient of Concordance (W), also known as Kendall's W, is a non-parametric statistical measure used to assess the agreement or concordance between multiple raters or judges when they rank a set of items. It is often used when you have ordinal data (ranks) and you want to see if there is consistency or consensus among the raters. It is widely applied in research areas such as psychology, medicine, and social sciences, where multiple judges are asked to rank or rate subjects...
214
Cluster Sampling Method01:20

Cluster Sampling Method

11.6K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
11.6K
Functional Classification of Joints01:09

Functional Classification of Joints

3.7K
Functional Classification of Joints
The functional classification of joints is determined by the amount of mobility between the adjacent bones. Joints are functionally classified as a synarthrosis or immobile joint, an amphiarthrosis or slightly moveable joint, or as a diarthrosis, a freely moveable joint. Fibrous and cartilaginous joints can be functionally classified as either synarthroses  or amphiarthroses, whereas all synovial joints are classified as diarthroses.
Synarthrosis
An...
3.7K
Distribution Reliability and Automation01:25

Distribution Reliability and Automation

103
Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
103

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

Lag-adjusted functional network connectivity reveals sensorimotor and higher cognitive network alterations in depression.

Research square·2026
Same author

Structural co-modulation: An individualized measure of inter-component interactions in source-based morphometry.

NeuroImage·2026
Same author

Measuring the Impacts of Urbanicity and Different Exposome Factors on Human Brain through Exposure Network Mapping.

Neuroscience bulletin·2026
Same author

Large-scale brain dynamics are organized by a directional coordination hierarchy.

bioRxiv : the preprint server for biology·2026
Same author

Brain regions with gestational age differences mediate cognition in adolescents born very premature.

Communications biology·2026
Same author

NeuroFLAME: A Scalable, Privacy-Preserving Federated Framework for Secure, Reproducible, and Multi-Site Neuroimaging Analysis.

bioRxiv : the preprint server for biology·2026

相关实验视频

Updated: May 24, 2025

Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

971

动态功能网络连接性聚类和协调评估指标

Biozid Bostami, Noah Lewis, Victor Vergara

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |March 5, 2025
    PubMed
    概括
    此摘要是机器生成的。

    站点效应显著影响多站点研究中的大脑动态功能网络连接 (dFNC) 聚类. 使用ComBat和一个数据协调器进行数据协调.

    更多相关视频

    Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks
    09:49

    Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks

    Published on: September 25, 2021

    4.3K
    Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
    10:44

    Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

    Published on: December 7, 2021

    2.1K

    相关实验视频

    Last Updated: May 24, 2025

    Modeling the Functional Network for Spatial Navigation in the Human Brain
    05:55

    Modeling the Functional Network for Spatial Navigation in the Human Brain

    Published on: October 13, 2023

    971
    Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks
    09:49

    Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks

    Published on: September 25, 2021

    4.3K
    Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
    10:44

    Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

    Published on: December 7, 2021

    2.1K

    科学领域:

    • 神经科学是一个神经科学.
    • 脑部成像 脑部成像
    • 数据科学数据科学数据科学

    背景情况:

    • 多站点神经科学数据集增强了研究,但引入了站点效应.
    • 动态功能网络连接 (dFNC) 分析依赖于时间功能连接模式的集群.
    • 站点效应可以在组合数据集中混dFNC状态识别.

    研究的目的:

    • 调查ComBat协调对dFNC状态在轻度创伤性脑损伤 (mTBI) 数据从两个站点的影响.
    • 引入和使用一个"包容性"模型来评估dFNC集群的场地效应影响.

    主要方法:

    • 应用了ComBat协调对来自两个mTBI研究的dFNC数据.
    • 集群dFNC状态以识别反复出现的连接模式.
    • 开发并使用"包容性"模型来量化关于场所效应的样本分布跨集群.

    主要成果:

    • 发现现场效应显著影响dFNC状态的形成和特征.
    • 通过ComBat协调,dFNC数据中的特定站点偏差减少了.
    • "包容性"模型有效地衡量了网站效应对dFNC协调前后集群的影响.

    结论:

    • 数据协调对于减轻多站点dFNC研究中的站点影响至关重要.
    • "包容性"模型提供了一个新的指标来评估对网站变化的集群稳定性.
    • 这些发现支持使用协调技术在各种数据集中进行可靠的dFNC分析.