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Connectome preprocessing by Consensus Clustering increases separability in group neuroimaging studies

View ORCID ProfileJavier Rasero, Jesus M Cortes, View ORCID ProfileDaniele Marinazzo, View ORCID ProfileSebastiano Stramaglia
doi: https://doi.org/10.1101/348110
Javier Rasero
Biocruces Health Research Institute. Hospital Universitario de Cruces., E-48903, Barakaldo, Spain.Dipartimento di Fisica, Universitá degli Studi”Aldo Moro” Bari, Italy
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Jesus M Cortes
Biocruces Health Research Institute. Hospital Universitario de Cruces., E-48903, Barakaldo, Spain.Ikerbasque, The Basque Foundation for Science, E-48011, Bilbao, Spain.
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Daniele Marinazzo
Faculty of Psychology and Educational Sciences, Department of Data Analysis, Ghent University, Henri Dunantlaan 2, B-9000 Ghent, Belgium
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Sebastiano Stramaglia
Dipartimento di Fisica, Universitá degli Studi”Aldo Moro” Bari, ItalyIstituto Nazionale di Fisica Nucleare, Sezione di Bari, ItalyTIRES-Center of Innovative Technologies for Signal Detection and Processing, Universitá degli Studi,”Aldo Moro” Bari, Italy
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Abstract

One of the biggest challenges in preprocessing pipelines for neuroimaging data is to increase the signal-to-noise ratio of the data which will be used for subsequent analyses. In the same line, we suggest in the present work that the application of consensus clustering for brain connectivity matrices to find subgroups of subjects can be a valid additional”connectome processing” step helpful to reduce intra-group variability and therefore increase the separability of distinct classes. In addition, by partitioning the data before any group comparison, we demonstrate that unique regions within each cluster arise and bring new information that could be relevant from a clinical point of view.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted June 16, 2018.
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Connectome preprocessing by Consensus Clustering increases separability in group neuroimaging studies
Javier Rasero, Jesus M Cortes, Daniele Marinazzo, Sebastiano Stramaglia
bioRxiv 348110; doi: https://doi.org/10.1101/348110
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Connectome preprocessing by Consensus Clustering increases separability in group neuroimaging studies
Javier Rasero, Jesus M Cortes, Daniele Marinazzo, Sebastiano Stramaglia
bioRxiv 348110; doi: https://doi.org/10.1101/348110

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