B
Bertrand Thirion
Researcher at Université Paris-Saclay
Publications - 334
Citations - 91237
Bertrand Thirion is an academic researcher from Université Paris-Saclay. The author has contributed to research in topics: Cluster analysis & Cognition. The author has an hindex of 51, co-authored 311 publications receiving 73839 citations. Previous affiliations of Bertrand Thirion include French Institute for Research in Computer Science and Automation & French Institute of Health and Medical Research.
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Journal ArticleDOI
Significant correlation between a set of genetic polymorphisms and a functional brain network revealed by feature selection and sparse Partial Least Squares.
Edith Le Floch,Vincent Guillemot,Vincent Guillemot,Vincent Frouin,Vincent Frouin,Philippe Pinel,Philippe Pinel,Christophe Lalanne,Laura Trinchera,Arthur Tenenhaus,Antonio Moreno,Antonio Moreno,Monica Zilbovicius,Monica Zilbovicius,Thomas Bourgeron,Stanislas Dehaene,Stanislas Dehaene,Stanislas Dehaene,Bertrand Thirion,Bertrand Thirion,Bertrand Thirion,Jean-Baptiste Poline,Edouard Duchesnay,Edouard Duchesnay,Edouard Duchesnay +24 more
TL;DR: This paper investigates the use of different strategies of regularisation and dimension reduction techniques combined with PLS or CCA to face the very high dimensionality of imaging genetics studies, and estimates the generalisability of the multivariate association with a cross-validation scheme.
Proceedings ArticleDOI
Identifying Predictive Regions from fMRI with TV-L1 Prior
TL;DR: To tackle efficiently this joint prediction-segmentation problem, a fast optimization algorithm based on a primal-dual approach is introduced and it is shown that injecting a spatial segmentation prior leads to unmatched performance in recovering predictive regions.
Journal ArticleDOI
Multi-scale Mining of fMRI data with Hierarchical Structured Sparsity
Rodolphe Jenatton,Alexandre Gramfort,Vincent Michel,Guillaume Obozinski,Evelyn Eger,Francis Bach,Bertrand Thirion +6 more
TL;DR: A sparse hierarchical structured regularization that encodes the spatial structure of the data at different scales into the regularization, which makes the overall prediction procedure more robust to inter-subject variability.
Journal ArticleDOI
Total variation regularization for fMRI-based prediction of behaviour
TL;DR: This article applies for the first time this method to fMRI data, and shows that TV regularization is well suited to the purpose of brain mapping while being a powerful tool for brain decoding.
Journal ArticleDOI
NeuroQuery: comprehensive meta-analysis of human brain mapping
Jérôme Dockès,Russell A. Poldrack,Romain Primet,Hande Gözükan,Tal Yarkoni,Fabian M. Suchanek,Bertrand Thirion,Gaël Varoquaux +7 more
TL;DR: The authors proposed a multivariate model to predict the spatial distribution of neurological observations, given text describing an experiment, cognitive process, or disease, and the resulting meta-analytic tool, neuroquery, can ground hypothesis generation and data-analysis priors on a comprehensive view of published findings on the brain.