Extrapolated nonnegative decompositions for the analysis of functional connectivity

Nicolas Honnorat, Christos Davatzikos

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Functional MRI (fMRI) captures brain function by recording the oxygen consumption of a large number of brain voxels simultaneously along time. The set of time series obtained is typically decomposed using Principal Component Analysis (PCA) or Independent Component Analysis (ICA) to reveal the regions and networks organizing the brain. In this work, we introduce a novel decomposition approach. We separate brain activations and de-activation, and we separately decompose co-activations, captured by the correlation between the activations, co-deactivations measured by the correlation between the de-activations, and the correlations between activations and de-activations. The decomposition is performed by a nonnegative factorization method known to generate sparse decompositions, which we accelerate by extrapolation. As a result, our approach produces in reasonable time compact fMRI scans decompositions offering a rich interpretation of the interactions between brain regions. The experiments presented here, performed on a dataset of forty scans provided by the Human Connectome Project, demonstrate the quality of our decompositions and indicate that a speedup of an order of magnitude is offered by the extrapolation.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2018
Subtitle of host publicationImage Processing
EditorsElsa D. Angelini, Elsa D. Angelini, Bennett A. Landman
ISBN (Electronic)9781510616370
StatePublished - 2018
Externally publishedYes
EventMedical Imaging 2018: Image Processing - Houston, United States
Duration: Feb 11 2018Feb 13 2018

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
ISSN (Print)1605-7422


ConferenceMedical Imaging 2018: Image Processing
Country/TerritoryUnited States


  • NMF
  • functional MRI

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Biomaterials
  • Radiology Nuclear Medicine and imaging


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