title: Deformation-Invariant Sparse Coding for Modeling Spatial Variability of Functional Patterns in the Brain.
abstract: For a given cognitive task such as language processing, the location of corresponding functional regions in the brain may vary across subjects relative to anatomy. We present a probabilistic generative model that accounts for such variability as observed in fMRI data. We relate our approach to sparse coding that estimates a basis consisting of functional regions in the brain. Individual fMRI data is represented as a weighted sum of these functional regions that undergo deformations. We demonstrate the proposed method on a language fMRI study. Our method identified activation regions that agree with known literature on language processing and established correspondences among activation regions across subjects, producing more robust group-level effects than anatomical alignment alone.
authors.forename: George H
authors.initials: GH
authors.lastname: Chen
authors.forename: Evelina G
authors.initials: EG
authors.lastname: Fedorenko
authors.forename: Nancy G
authors.initials: NG
authors.lastname: Kanwisher
authors.forename: Polina
authors.initials: P
authors.lastname: Golland