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.
Papers
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SpaceNet: Multivariate brain decoding and segmentation
TL;DR: This work presents SpaceNet, a multivariate method for brain decoding and segmentation that uses priors like TV (Total Variation) and GraphNet / Smooth-Lasso to regularize / penalize classification and regression problems in brain imaging.
Posted Content
HRF estimation improves sensitivity of fMRI encoding and decoding models
TL;DR: In this paper, a model for jointly estimating the hemodynamic response function (HRF) and the activation patterns via a low-rank representation of task effects is proposed, which can be computed using standard gradient-based solvers.
Proceedings Article
Label scarcity in biomedicine: Data-rich latent factor discovery enhances phenotype prediction.
TL;DR: It is demonstrated that low-dimensional embedding spaces can be derived from the UK Biobank population dataset and used to enhance data-scarce prediction of health indicators, lifestyle and demographic characteristics.
New Results - Principal Component Regression predicts functional responses across individuals
TL;DR: A novel analysis framework is introduced, where the amount of variance that is fit by a random effects subspace learned on other images is estimated; it is shown that a principal component regression estimator outperforms other regression models and that it fits a significant proportion (10% to 25%) of the between-subject variability.
Book ChapterDOI
Intra and inter subject analyses of brain functional Magnetic Resonance Images (fMRI)
TL;DR: This chapter proposes a review of the most prominent issues in analysing brain functional Magnetic Resonance data and introduces the domain for readers with no or little knowledge in the field, including some specific advances that are important for application studies in cognitive neurosciences.