BrainSync: An Orthogonal Transformation for Synchronization of fMRI Data Across Subjects

  • Anand A. JoshiEmail author
  • Minqi Chong
  • Richard M. Leahy
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10433)


We describe a method that allows direct comparison of resting fMRI (rfMRI) time series across subjects. For this purpose, we exploit the geometry of the rfMRI signal space to conjecture the existence of an orthogonal transformation that synchronizes fMRI time series across sessions and subjects. The method is based on the observation that rfMRI data exhibit similar connectivity patterns across subjects, as reflected in the pairwise correlations between different brain regions. The orthogonal transformation that performs the synchronization is unique, invertible, efficient to compute, and preserves the connectivity structure of the original data for all subjects. Similarly to image registration, where we spatially align the anatomical brain images, this synchronization of brain signals across a population or within subject across sessions facilitates longitudinal and cross-sectional studies of rfMRI data. The utility of this transformation is illustrated through applications to quantification of fMRI variability across subjects and sessions, joint cortical clustering of a population and comparison of task-related and resting fMRI.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Anand A. Joshi
    • 1
    Email author
  • Minqi Chong
    • 1
  • Richard M. Leahy
    • 1
  1. 1.Signal and Image Processing InstituteUniversity of Southern CaliforniaLos AngelesUSA

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