Adaptive strategy for the statistical analysis of connectomes.

Détails

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Etat: Public
Version: de l'auteur⸱e
ID Serval
serval:BIB_670C3496024C
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Adaptive strategy for the statistical analysis of connectomes.
Périodique
Plos One
Auteur⸱e⸱s
Meskaldji D.E., Ottet M.C., Cammoun L., Hagmann P., Meuli R., Eliez S., Thiran J.P., Morgenthaler S.
ISSN
1932-6203 (Electronic)
ISSN-L
1932-6203
Statut éditorial
Publié
Date de publication
2011
Volume
6
Numéro
8
Pages
e23009
Langue
anglais
Notes
Publication types: Journal ArticlePublication Status: ppublish
Résumé
We study an adaptive statistical approach to analyze brain networks represented by brain connection matrices of interregional connectivity (connectomes). Our approach is at a middle level between a global analysis and single connections analysis by considering subnetworks of the global brain network. These subnetworks represent either the inter-connectivity between two brain anatomical regions or by the intra-connectivity within the same brain anatomical region. An appropriate summary statistic, that characterizes a meaningful feature of the subnetwork, is evaluated. Based on this summary statistic, a statistical test is performed to derive the corresponding p-value. The reformulation of the problem in this way reduces the number of statistical tests in an orderly fashion based on our understanding of the problem. Considering the global testing problem, the p-values are corrected to control the rate of false discoveries. Finally, the procedure is followed by a local investigation within the significant subnetworks. We contrast this strategy with the one based on the individual measures in terms of power. We show that this strategy has a great potential, in particular in cases where the subnetworks are well defined and the summary statistics are properly chosen. As an application example, we compare structural brain connection matrices of two groups of subjects with a 22q11.2 deletion syndrome, distinguished by their IQ scores.
Pubmed
Web of science
Open Access
Oui
Création de la notice
16/08/2011 8:19
Dernière modification de la notice
20/08/2019 14:22
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