Hybrid ICA-seed-based methods for fMRI functional connectivity assessment: a feasibility study

  • Authors:

  • Robert E. Kelly;Zhishun Wang;George S. Alexopoulos;Faith M. Gunning;Christopher F. Murphy;Sarah ShizukoMorimoto;Dora Kanellopoulos;Zhiru Jia;Kelvin O. Lim;Matthew J. Hoptman

  • Affiliations:

  • Weill Cornell Institute of Geriatric Psychiatry, Weill Cornell Medical College, White Plains, NY;Columbia University, New York State Psychiatric Institute, New York, NY;Weill Cornell Institute of Geriatric Psychiatry, Weill Cornell Medical College, White Plains, NY;Weill Cornell Institute of Geriatric Psychiatry, Weill Cornell Medical College, White Plains, NY;Weill Cornell Institute of Geriatric Psychiatry, Weill Cornell Medical College, White Plains, NY;Weill Cornell Institute of Geriatric Psychiatry, Weill Cornell Medical College, White Plains, NY;Weill Cornell Institute of Geriatric Psychiatry, Weill Cornell Medical College, White Plains, NY;Weill Cornell Institute of Geriatric Psychiatry, Weill Cornell Medical College, White Plains, NY;Department of Psychiatry, University of Minnesota, Minneapolis, MN;Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY and Department of Psychiatry, New York University School of Medicine, New York, NY

  • Venue:
  • Journal of Biomedical Imaging
  • Year:
  • 2010

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Abstract

Brain functional connectivity (FC) is often assessed from fMRI data using seed-based methods, such as those of detecting temporal correlation between a predefined region (seed) and all other regions in the brain; or using multivariate methods, such as independent component analysis (ICA). ICA is a useful data-driven tool, but reproducibility issues complicate group inferences based on FC maps derived with ICA. These reproducibility issues can be circumvented with hybrid methods that use information from ICA-derived spatial maps as seeds to produce seed-based FC maps. We report results from five experiments to demonstrate the potential advantages of hybrid ICA-seed-based FC methods, comparing results from regressing fMRI data against task-related a priori time courses, with "back-reconstruction" from a group ICA, and with five hybrid ICA-seed-based FC methods: ROI-based with (1) single-voxel, (2) few-voxel, and (3) many-voxel seed; and dual-regression-based with (4) single ICA map and (5) multiple ICA map seed.