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Communication Dans Un Congrès Année : 2022

Aligning individual brains with Fused Unbalanced Gromov-Wasserstein

Résumé

Individual brains vary in both anatomy and functional organization, even within a given species. Inter-individual variability is a major impediment when trying to draw generalizable conclusions from neuroimaging data collected on groups of subjects. Current co-registration procedures rely on limited data, and thus lead to very coarse inter-subject alignments. In this work, we present a novel method for inter-subject alignment based on Optimal Transport, denoted as Fused Unbalanced Gromov Wasserstein (FUGW). The method aligns cortical surfaces based on the similarity of their functional signatures in response to a variety of stimulation settings, while penalizing large deformations of individual topographic organization. We demonstrate that FUGW is well-suited for whole-brain landmark-free alignment. The unbalanced feature allows to deal with the fact that functional areas vary in size across subjects. Our results show that FUGW alignment significantly increases between-subject correlation of activity for independent functional data, and leads to more precise mapping at the group level.

Dates et versions

hal-03858930 , version 1 (18-11-2022)

Identifiants

Citer

Alexis Thual, Huy Tran, Tatiana Zemskova, Nicolas Courty, Rémi Flamary, et al.. Aligning individual brains with Fused Unbalanced Gromov-Wasserstein. NeurIPS 2022 - Conference on Neural Information Processing Systems, Nov 2022, New-Orlean, France. ⟨hal-03858930⟩
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