Search research articles

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 Journal Methods Collections JoVE Encyclopedia of Experiments 存档

教育

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual 教师资源中心教师网站

使用条款与条件

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

Small Intestinal Bacterial Overgrowth: Microbiome Dysregulation, Gut-Brain Axis Disruption, and Systemic Consequences.

Molecular nutrition & food research·2026

Same author

Vagus nerve stimulation for refractory epilepsy: a 24-year single-center experience.

Journal of neurosurgery·2026

Same author

Characterization and Structural Evaluation of Niobium-Integrated Chitosan-Gelatin Hybrid Hydrogels.

Gels (Basel, Switzerland)·2026

Same author

<i>Salvia coccinea</i> and Apigenin: A Natural Treasure of Lamiaceae in Pharmacological Innovation.

Food science & nutrition·2026

Same author

Structured dissociative PCA methods for high dimensional neuroimaging signal decomposition.

Scientific reports·2026

Same author

Integration of Multi-Cereals Into Wheat Flour: Nutritional Composition, Dough Rheology, and Sensory Profile of Composite Breads.

Food science & nutrition·2025

Search research articles

相关实验视频

Updated: Jul 10, 2025

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

一种使用多个主体fMRI空间和时间组件的新型学科智能字典学习方法.

Muhammad Usman Khalid¹, Malik Muhammad Nauman²

¹College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University, 11564, Riyadh, Saudi Arabia.

Scientific reports

|November 19, 2023

概括

新的词典学习算法 (swsDL和swbDL) 有效地整合了多个主体的fMRI数据,通过整合时空模式来改进分析,以获得更好的群体层面见解.

更多相关视频

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Published on: March 21, 2019

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques

Published on: June 30, 2020

相关实验视频

Last Updated: Jul 10, 2025

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Published on: March 21, 2019

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques

Published on: June 30, 2020

科学领域:

神经成像是一种神经成像.
机器学习机器学习
信号处理信号处理

背景情况:

传统的字典学习 (DL) 适应个人fMRI数据,忽视多主体的时空信息.
根据学科的数据可以分解为多学科的时间课程和空间地图.

研究的目的:

引入新的字典学习算法 (swsDL和swbDL) 以利用多主体fMRI数据.
巩固跨学科的时空多样性,以进行增强的分析.

主要方法:

使用混合模型与预先计算的多主题基数矩阵开发了一个新的框架.
采用稀疏的时空盲源分离用于基矩阵生成.
使用[公式:参见文本]/[公式:参见文本]-规范处罚/约束,并交替最小化以进行优化.

主要成果:

拟议的swsDL和swbDL算法成功地结合了多主体的时空组件.
与现有方法相比,实现了平均相关性[公式:参见文本]的增加.
通过 swsDL 和 swbDL.dll 证明了平均计算时间的 [公式:参见文本] 减少.

结论:

swsDL和swbDL提供了一种独特的方法,通过更新主题智能的原子/分散代码与多主题组件.
这些算法有助于从fMRI数据中提取组级动态.
这些方法在相关性和计算效率方面表现优于最先进的算法.