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Abstract #3425

A Randomized Global Signal Regression Method for Resting State Functional Connectivity Studies

Hongjian He1,2, Anna Leigh Rack-Gomer2, Thomas T. Liu2

1Department of Physics, Zhejiang University, Hangzhou, Zhejiang, China; 2Center for Functional MRI, University of California, San Diego, La Jolla, CA, United States

Global signal removal is a widely used and controversial method for resting state functional connectivity analysis. When all voxels are used for the computation of the global signal, removal of the global signal can produce artifactual negative correlations. In this study, we consider the use of an alternative estimate of the global signal that utilizes a random sample of voxels chosen to be outside the regions of interest that are used to compute the correlation. Because this estimate does not include voxels within the regions of interest, its use does not force negative correlations to exist.