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Cohort-Level Brain Mapping: Learning Cognitive Atoms to Single Out Specialized Regions

  • Gaël Varoquaux
  • Yannick Schwartz
  • Philippe Pinel
  • Bertrand Thirion
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7917)

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.

Keywords

Independent Component Analysis Independent Component Analysis Functional Network Sparse Code Dictionary Learning 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Gaël Varoquaux
    • 1
    • 2
    • 3
  • Yannick Schwartz
    • 1
    • 2
  • Philippe Pinel
    • 2
    • 3
  • Bertrand Thirion
    • 1
    • 2
  1. 1.INRIAParietal TeamSaclayFrance
  2. 2.NeuroSpin, CEA SaclayGif-sur-Yvette, cedexFrance
  3. 3.INSERM U992 Cognitive Neuroimaging UnitFrance

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