Quantifying and Visualizing Intraregional Connectivity in Resting-State Functional Magnetic Resonance Imaging with Correlation Densities
Quantifying and Visualizing Intraregional Connectivity in Resting-State Functional Magnetic Resonance Imaging with Correlation Densities
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DOI：
10.1089/brain.2018.0591
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发表时间：
2019-02
影响因子：
3.4
通讯作者：
Alexander Petersen;Chun-Jui Chen;H. Müller
中科院分区：
文献类型：
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作者：
Alexander Petersen;Chun-Jui Chen;H. Müller
相关密度的使用被引入量化和提供视觉解释在大脑区域内的功能连接。对于每个大脑区域，计算种子体素和该区域内其他灰质体素之间的两两相关性，并将这些相关值的集合分布表示为概率密度，即相关密度。通过核平滑可以估计相关密度。它为每个地区的本地级别上特定于主题的功能连接强度提供了直观和全面的表示。为了解决在考虑多个区域时解释和利用这些丰富的连通性信息的挑战，实现了功能数据分析的方法，包括最近开发的专门用于概率分布分析的降维方法。为了说明这些方法在神经成像中的效用，进行了实验来确定局部功能连接和一系列神经认知评分之间的关联。这些实验表明，相关密度有助于发现和解释特定的区域-分数关联。
The use of correlation densities is introduced to quantify and provide visual interpretation for intraregional functional connectivity in the brain. For each brain region, pairwise correlations are computed between a seed voxel and other gray matter voxels within the region, and the distribution of the ensemble of these correlation values is represented as a probability density, the correlation density. The correlation density can be estimated by kernel smoothing. It provides an intuitive and comprehensive representation of subject-specific functional connectivity strength at the local level for each region. To address the challenge of interpreting and utilizing this rich connectivity information when multiple regions are considered, methods from functional data analysis are implemented, including a recently developed method of dimensionality reduction specifically tailored to the analysis of probability distributions. To illustrate the utility of these methods in neuroimaging, experiments were carried out to identify the associations between local functional connectivity and a battery of neurocognitive scores. These experiments demonstrate that correlation densities facilitate the discovery and interpretation of specific region-score associations.