An ANOVA approach for statistical comparisons of brain networks

Abstract The study of brain networks has developed extensively over the last couple of decades. By contrast, techniques for the statistical analysis of these networks are less developed. In this paper, we focus on the statistical comparison of brain networks in a nonparametric framework and discuss...

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Autores principales:	Daniel Fraiman, Ricardo Fraiman
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2018
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/f3c348a3b3b04bfcbad5e44986d7685d
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spelling	oai:doaj.org-article:f3c348a3b3b04bfcbad5e44986d7685d2021-12-02T15:08:37ZAn ANOVA approach for statistical comparisons of brain networks10.1038/s41598-018-23152-52045-2322https://doaj.org/article/f3c348a3b3b04bfcbad5e44986d7685d2018-03-01T00:00:00Zhttps://doi.org/10.1038/s41598-018-23152-5https://doaj.org/toc/2045-2322Abstract The study of brain networks has developed extensively over the last couple of decades. By contrast, techniques for the statistical analysis of these networks are less developed. In this paper, we focus on the statistical comparison of brain networks in a nonparametric framework and discuss the associated detection and identification problems. We tested network differences between groups with an analysis of variance (ANOVA) test we developed specifically for networks. We also propose and analyse the behaviour of a new statistical procedure designed to identify different subnetworks. As an example, we show the application of this tool in resting-state fMRI data obtained from the Human Connectome Project. We identify, among other variables, that the amount of sleep the days before the scan is a relevant variable that must be controlled. Finally, we discuss the potential bias in neuroimaging findings that is generated by some behavioural and brain structure variables. Our method can also be applied to other kind of networks such as protein interaction networks, gene networks or social networks.Daniel FraimanRicardo FraimanNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 8, Iss 1, Pp 1-14 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Daniel Fraiman Ricardo Fraiman An ANOVA approach for statistical comparisons of brain networks
description	Abstract The study of brain networks has developed extensively over the last couple of decades. By contrast, techniques for the statistical analysis of these networks are less developed. In this paper, we focus on the statistical comparison of brain networks in a nonparametric framework and discuss the associated detection and identification problems. We tested network differences between groups with an analysis of variance (ANOVA) test we developed specifically for networks. We also propose and analyse the behaviour of a new statistical procedure designed to identify different subnetworks. As an example, we show the application of this tool in resting-state fMRI data obtained from the Human Connectome Project. We identify, among other variables, that the amount of sleep the days before the scan is a relevant variable that must be controlled. Finally, we discuss the potential bias in neuroimaging findings that is generated by some behavioural and brain structure variables. Our method can also be applied to other kind of networks such as protein interaction networks, gene networks or social networks.
format	article
author	Daniel Fraiman Ricardo Fraiman
author_facet	Daniel Fraiman Ricardo Fraiman
author_sort	Daniel Fraiman
title	An ANOVA approach for statistical comparisons of brain networks
title_short	An ANOVA approach for statistical comparisons of brain networks
title_full	An ANOVA approach for statistical comparisons of brain networks
title_fullStr	An ANOVA approach for statistical comparisons of brain networks
title_full_unstemmed	An ANOVA approach for statistical comparisons of brain networks
title_sort	anova approach for statistical comparisons of brain networks
publisher	Nature Portfolio
publishDate	2018
url	https://doaj.org/article/f3c348a3b3b04bfcbad5e44986d7685d
work_keys_str_mv	AT danielfraiman ananovaapproachforstatisticalcomparisonsofbrainnetworks AT ricardofraiman ananovaapproachforstatisticalcomparisonsofbrainnetworks AT danielfraiman anovaapproachforstatisticalcomparisonsofbrainnetworks AT ricardofraiman anovaapproachforstatisticalcomparisonsofbrainnetworks
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An ANOVA approach for statistical comparisons of brain networks

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