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We compare two common methods for detecting functional connectivity: thresholding correlations and singular value decomposition (SVD). We find that thresholding correlations are better at detecting focal regions of correlated voxels, whereas SVD is better at detecting extensive regions of correlated voxels. We apply these results to resting state networks in an fMRI dataset to look for connectivity in cortical thickness.

Original publication

DOI

10.1098/rstb.2005.1637

Type

Journal article

Journal

Philos Trans R Soc Lond B Biol Sci

Publication Date

29/05/2005

Volume

360

Pages

913 - 920

Keywords

Brain, Brain Mapping, Humans, Image Processing, Computer-Assisted, Linear Models, Magnetic Resonance Imaging, Models, Neurological