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Embedding of Functional Human Brain Networks on a Sphere

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sphericalMDS

Title: Embedding of Functional Human Brain Networks on a Sphere

Authors: Moo K. Chung and Zijian Chen, University of Wisconsin-Madison

Abstract: Human brain activity is often measured using the blood-oxygen-level dependent (BOLD) signals obtained through functional magnetic resonance imaging (fMRI). The strength of connectivity between brain regions is then measured and represented as Pearson correlation matrices. As the number of brain regions increases, the dimension of matrix increases. It becomes extremely cumbersome to even visualize and quantify such weighted complete networks. To remedy the problem, we propose to embedded brain networks onto a hypersphere, which is a Riemannian manifold with constant positive curvature.

The codes performs the spherical- and hyperbolic-MDS explained in https://arxiv.org/abs/2204.03653. The folder contains latex zipped file for arXiv paper as well. Run script.m

(C) 2022 Codes are written by Moo K. Chung and Zijian Chen of University of Wisconsin-Madison.

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