An approach to directly link ICA and seed-based functional connectivity: Application to schizophrenia.

ABSTRACT: Independent component analysis (ICA) and seed-based analyses are widely used techniques for studying intrinsic neuronal activity in task-based or resting scans. In this work, we show there is a direct link between the two, and show that there are some important differences between the two approaches in terms of what information they capture. We developed an enhanced connectivity-matrix independent component analysis (cmICA) for calculating whole brain voxel maps of functional connectivity, which reduces the computational complexity of voxel-based connectivity analysis on performing many temporal correlations. We also show there is a mathematical equivalency between parcellations on voxel-to-voxel functional connectivity and simplified cmICA. Next, we used this cost-efficient data-driven me

SUBMITTER: Wu L 

PROVIDER: S-EPMC6072460 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature