Cohort-level brain mapping: learning cognitive atoms to single out specialized regions

Gaël Varoquaux 1, 2, 3 Yannick Schwartz 1, 2 Philippe Pinel 2, 3, 4 Bertrand Thirion 1, 2
1 PARIETAL - Modelling brain structure, function and variability based on high-field MRI data
Inria Saclay - Ile de France, NEUROSPIN - Service NEUROSPIN
2 NEUROSPIN - Service NEUROSPIN
3 UNICOG-U992 - Neuroimagerie cognitive
4 CDF - Collège de France
Abstract : Functional Magnetic Resonance Imaging (fMRI) studies map the human brain by testing the response of groups of individuals to carefully-crafted and contrasted tasks in order to delineate specialized brain regions and networks. The number of functional networks extracted is limited by the number of subject-level contrasts and does not grow with the cohort. Here, we introduce a new group-level brain mapping strategy to differentiate many regions reflecting the variety of brain network configurations observed in the population. Based on the principle of functional segregation, our approach singles out functionally-specialized brain regions by learning group-level functional profiles on which the response of brain regions can be represented sparsely. We use a dictionary-learning formulation that can be solved efficiently with on-line algorithms, scaling to arbitrary large datasets. Importantly, we model inter-subject correspondence as structure imposed in the estimated functional profiles, integrating a structure-inducing regularization with no additional computational cost. On a large multi-subject study, our approach extracts a large number of brain networks with meaningful functional profiles.
Mots-clés : fMRI brain parcellations cognitive domains
Type de document :
Communication dans un congrès
William M. Wells and Sarang Joshi and Kilian M. Pohl. IPMI - Information Processing in Medical Imaging - 2013, Jun 2013, Asilomar, United States. Springer, 7917, pp.438-449, 2013, LNCS. 〈http://link.springer.com/chapter/10.1007/978-3-642-38868-2_37〉. 〈10.1007/978-3-642-38868-2_37〉
Liste complète des métadonnées

Littérature citée [19 références]  Voir  Masquer  Télécharger
https://hal.inria.fr/hal-00841502
Contributeur : Gaël Varoquaux <>
Soumis le : samedi 6 juillet 2013 - 06:59:12
Dernière modification le : lundi 4 juin 2018 - 15:42:02
Document(s) archivé(s) le : mercredi 5 avril 2017 - 07:18:41

Fichier

paper.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Collections

INRIA | CEA | PSL | JOLIOT | CEA-DRF | NEUROSPIN

Citation

Gaël Varoquaux, Yannick Schwartz, Philippe Pinel, Bertrand Thirion. Cohort-level brain mapping: learning cognitive atoms to single out specialized regions. William M. Wells and Sarang Joshi and Kilian M. Pohl. IPMI - Information Processing in Medical Imaging - 2013, Jun 2013, Asilomar, United States. Springer, 7917, pp.438-449, 2013, LNCS. 〈http://link.springer.com/chapter/10.1007/978-3-642-38868-2_37〉. 〈10.1007/978-3-642-38868-2_37〉. 〈hal-00841502〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

1039

Téléchargements de fichiers

393

Contact


archive-ouverte@inria.fr