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- W2951356526 abstract "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." @default.
- W2951356526 created "2019-06-27" @default.
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- W2951356526 date "2019-07-01" @default.
- W2951356526 modified "2023-09-24" @default.
- W2951356526 title "A New Approach for Functional Connectivity via Alignment of Blood Oxygen Level-Dependent Signals" @default.
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- W2951356526 doi "https://doi.org/10.1089/brain.2018.0636" @default.
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