A New Approach for Functional Connectivity via Alignment of Blood Oxygen Level-Dependent Signals
A New Approach for Functional Connectivity via Alignment of Blood Oxygen Level-Dependent Signals
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DOI：
10.1089/brain.2018.0636
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发表时间：
2019-07-01
影响因子：
3.4
通讯作者：
Wang, Jane-Ling
中科院分区：
文献类型：
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作者：
Chen, Chun-Jui;Wang, Jane-Ling
由于技术的进步，空间索引对象，如血氧水平相关的时间序列或脑电图数据，通常在不同的科学学科中观察到。这样的对象数据通常是高维的，因此难以处理。我们提出了一种新的方法，空间索引对象数据映射到一个有针对性的一维间隔，使对象是相似的放置在新的目标空间彼此靠近。所提出的对齐不仅为这种复杂的对象数据提供了可视化工具，而且还为研究大脑功能连接提供了一种新的方法。具体来说，我们引入了一个新的路径长度的概念来量化的功能连接和一个新的社区检测方法。所提出的方法的优点是通过模拟和阿尔茨海默病的功能连接的研究。
Due to technological advances, spatially indexed objects, such as blood oxygen level-dependent time series or electroencephalography data, are commonly observed across different scientific disciplines. Such object data are typically high dimensional and therefore challenging to handle. We propose a new approach for spatially indexed object data by mapping their spatial locations to a targeted one-dimensional interval so objects that are similar are placed near each other on the new target space. The proposed alignment not only provides a visualization tool for such complex object data but also facilitates a new way to study brain functional connectivity. Specifically, we introduce a new concept of path length to quantify the functional connectivity and a new community detection method. The advantages of the proposed methods are illustrated by simulations and in a study of functional connectivity for Alzheimer's disease.