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...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2018-03-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-018-23152-5 |
| _version_ | 1818995694076166144 |
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| author | Daniel Fraiman Ricardo Fraiman |
| author_facet | Daniel Fraiman Ricardo Fraiman |
| author_sort | Daniel Fraiman |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-20T21:17:55Z |
| format | Article |
| id | doaj.art-f3c348a3b3b04bfcbad5e44986d7685d |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-12-20T21:17:55Z |
| publishDate | 2018-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-f3c348a3b3b04bfcbad5e44986d7685d2022-12-21T19:26:23ZengNature PortfolioScientific Reports2045-23222018-03-018111410.1038/s41598-018-23152-5An ANOVA approach for statistical comparisons of brain networksDaniel Fraiman0Ricardo Fraiman1Departamento de Matemática y Ciencias, Universidad de San AndrésCentro de Matemática, Facultad de Ciencias, Universidad de la RepúblicaAbstract 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.https://doi.org/10.1038/s41598-018-23152-5 |
| spellingShingle | Daniel Fraiman Ricardo Fraiman An ANOVA approach for statistical comparisons of brain networks Scientific Reports |
| title | 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_short | An ANOVA approach for statistical comparisons of brain networks |
| title_sort | anova approach for statistical comparisons of brain networks |
| url | https://doi.org/10.1038/s41598-018-23152-5 |
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