Effects of tissue-specific fMRI signal regression on resting-state functional connectivity.

Brain Connect. 2017 Aug 21;:

Authors: Vos de Wael R, Hyder F, Thompson GJ

Abstract
Neuroimaging studies typically consider white matter as unchanging in different neural and metabolic states. However, a recent study (Brain Connect. 6(6):435-447) demonstrated that white matter signal regression (WMSR) produced a similar loss of neurometabolic information to "global" (whole-brain) signal regression (GSR) in resting state fMRI (R-fMRI) data. This was unexpected, as the loss of information would normally be attributed to neural activity within gray matter correlating with the global R-fMRI signal. Indeed, WMSR has been suggested as an alternative to avoid such pitfalls in GSR. To address these concerns about tissue-specific regression in R-fMRI data analysis, we performed GSR, WMSR and gray matter signal regression (GMSR) on resting state fMRI (R-fMRI) data from the 1000 Functional Connectomes project. While minor differences between GSR and tissue-specific regressions existed with respect to subject motion and intra-network correlation, overall effects were very similar between all regressions. Our results suggest that tissue-specific regression is not an adequate strategy to counter pitfalls of GSR. Conversely, if GSR is desired but the studied disease excludes either gray matter or white matter from analysis, our results indicate that WMSR or GMSR respectively could be used in GSR's stead.

PMID: 28825320 [PubMed - as supplied by publisher]