Perelman School of Medicine at the University of Pennsylvania

Section for Biomedical Image Analysis (SBIA)

participating with CBICA

Functional connectivity analysis: Identification of subject-specific brain functional networks

Delineation of large-scale intrinsic connectivity networks (ICNs) from resting state functional MRI (rsfMRI) data has become a standard tool to explore the functional brain organization in neuroscience. However, existing methods sacrifice subject specific variation in order to maintain the across-subject correspondence necessary for group-level analyses. In order to obtain subject specific ICNs that are comparable across subjects, we have developed functional brain decomposition techniques for detecting subject specific ICNs while establishing group level correspondence, including group information guided ICA and collaborative sparse nonnegative matrix decomposition. Our methods could obtain subject specific ICNs with improved functional coherence, providing enhanced ability for characterizing the functional brain of individual subjects.


  1. Du, Y. and Fan, Y., Group information guided ICA for fMRI data analysis, Neuroimage, 2013. 69:157–197
  2.  Li, H., et al., Identification of subject-specific brain functional networks using a collaborative sparse nonnegative matrix decomposition method, ISBI 2016: 984-987