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Brain Connect. 2019 Jul;9(6):464-474. doi: 10.1089/brain.2018.0636. Epub 2019 Jun 20.

A New Approach for Functional Connectivity via Alignment of Blood Oxygen Level-Dependent Signals.

Author information

1
Department of Statistics, University of California Davis, Davis, California.

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.

KEYWORDS:

community detection; data visualization; functional connectivity; multidimensional scaling; multivariate time series

PMID:
31219308
DOI:
10.1089/brain.2018.0636

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