A novel approach to understanding Parkinsonian cognitive decline using minimum spanning trees, edge cutting, and magnetoencephalography

Abstract Graph theory-based approaches are efficient tools for detecting clustering and group-wise differences in high-dimensional data across a wide range of fields, such as gene expression analysis and neural connectivity. Here, we examine data from a cross-sectional, resting-state magnetoencephal...

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Autores principales:	Olivier B. Simon, Isabelle Buard, Donald C. Rojas, Samantha K. Holden, Benzi M. Kluger, Debashis Ghosh
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/fed05e3379004ea0af73781e1451d50d
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spelling	oai:doaj.org-article:fed05e3379004ea0af73781e1451d50d2021-12-02T18:37:08ZA novel approach to understanding Parkinsonian cognitive decline using minimum spanning trees, edge cutting, and magnetoencephalography10.1038/s41598-021-99167-22045-2322https://doaj.org/article/fed05e3379004ea0af73781e1451d50d2021-10-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-99167-2https://doaj.org/toc/2045-2322Abstract Graph theory-based approaches are efficient tools for detecting clustering and group-wise differences in high-dimensional data across a wide range of fields, such as gene expression analysis and neural connectivity. Here, we examine data from a cross-sectional, resting-state magnetoencephalography study of 89 Parkinson’s disease patients, and use minimum-spanning tree (MST) methods to relate severity of Parkinsonian cognitive impairment to neural connectivity changes. In particular, we implement the two-sample multivariate-runs test of Friedman and Rafsky (Ann Stat 7(4):697–717, 1979) and find it to be a powerful paradigm for distinguishing highly significant deviations from the null distribution in high-dimensional data. We also generalize this test for use with greater than two classes, and show its ability to localize significance to particular sub-classes. We observe multiple indications of altered connectivity in Parkinsonian dementia that may be of future use in diagnosis and prediction.Olivier B. SimonIsabelle BuardDonald C. RojasSamantha K. HoldenBenzi M. KlugerDebashis GhoshNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-17 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Olivier B. Simon Isabelle Buard Donald C. Rojas Samantha K. Holden Benzi M. Kluger Debashis Ghosh A novel approach to understanding Parkinsonian cognitive decline using minimum spanning trees, edge cutting, and magnetoencephalography
description	Abstract Graph theory-based approaches are efficient tools for detecting clustering and group-wise differences in high-dimensional data across a wide range of fields, such as gene expression analysis and neural connectivity. Here, we examine data from a cross-sectional, resting-state magnetoencephalography study of 89 Parkinson’s disease patients, and use minimum-spanning tree (MST) methods to relate severity of Parkinsonian cognitive impairment to neural connectivity changes. In particular, we implement the two-sample multivariate-runs test of Friedman and Rafsky (Ann Stat 7(4):697–717, 1979) and find it to be a powerful paradigm for distinguishing highly significant deviations from the null distribution in high-dimensional data. We also generalize this test for use with greater than two classes, and show its ability to localize significance to particular sub-classes. We observe multiple indications of altered connectivity in Parkinsonian dementia that may be of future use in diagnosis and prediction.
format	article
author	Olivier B. Simon Isabelle Buard Donald C. Rojas Samantha K. Holden Benzi M. Kluger Debashis Ghosh
author_facet	Olivier B. Simon Isabelle Buard Donald C. Rojas Samantha K. Holden Benzi M. Kluger Debashis Ghosh
author_sort	Olivier B. Simon
title	A novel approach to understanding Parkinsonian cognitive decline using minimum spanning trees, edge cutting, and magnetoencephalography
title_short	A novel approach to understanding Parkinsonian cognitive decline using minimum spanning trees, edge cutting, and magnetoencephalography
title_full	A novel approach to understanding Parkinsonian cognitive decline using minimum spanning trees, edge cutting, and magnetoencephalography
title_fullStr	A novel approach to understanding Parkinsonian cognitive decline using minimum spanning trees, edge cutting, and magnetoencephalography
title_full_unstemmed	A novel approach to understanding Parkinsonian cognitive decline using minimum spanning trees, edge cutting, and magnetoencephalography
title_sort	novel approach to understanding parkinsonian cognitive decline using minimum spanning trees, edge cutting, and magnetoencephalography
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/fed05e3379004ea0af73781e1451d50d
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A novel approach to understanding Parkinsonian cognitive decline using minimum spanning trees, edge cutting, and magnetoencephalography

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