Independent Component Analysis of Localized Resting State fMRI Reveals Specific Motor Sub-Networks.

Brain Connect. 2012 Jun 28;

Authors: Sohn WS, Yoo K, Jeong Y

Abstract
Recent studies have shown that BOLD low frequency (<0.1 Hz) fluctuations (LFFs) during a "resting state" exhibit a high degree of correlation with other regions which share cognitive function. Initial studies of resting state network mapping have focused primarily on major networks such as the default mode network, primary motor, somatosensory, visual, and auditory networks. However more specific or sub-networks including those associated with specific motor functions have yet to be properly addressed. We performed independent component analysis (ICA) in a specific target region of the brain, a process we name "localized ICA". We demonstrated that ICA with localized data can, resting state LFFS in regions associated with specific motor functions (e.g. finger tapping, foot movement, or bilateral lip pulsing) and other smaller networks can be distinguished from one another. These ICA components generated from localized data can then be used as functional regions of interest (ROIs) to map whole brain connectivity. In addition, this method can be used to visualize interregional connectivity by expanding the localized region and identifying components which show connectivity between the two regions.

PMID: 22738280 [PubMed - as supplied by publisher]