Title
Effects Of Tissue-Specific Functional Magnetic Resonance Imaging Signal Regression On Resting-State Functional Connectivity
Abstract
Neuroimaging studies typically consider white matter as unchanging in different neural and metabolic states. However, a recent study demonstrated that white matter signal regression (WMSR) produced a similar loss of neurometabolic information to global (whole-brain) signal regression (GSR) in resting-state functional magnetic resonance imaging (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 R-fMRI data from the 1000 Functional Connectomes Project. We describe several regional and motion-related differences between different types of regressions. However, the overall effects of concern, particularly network-specific alteration of correlation coefficients, are present for all regressions. This suggests that tissue-specific regression is not an adequate strategy to counter pitfalls of GSR. Conversely, if GSR is desired, but the studied disease state excludes either gray matter or white matter from analysis (e.g., due to tissue atrophy), our results indicate that WMSR or GMSR may reproduce the gross effects of GSR.
Year
DOI
Venue
2017
10.1089/brain.2016.0465
BRAIN CONNECTIVITY
Keywords
Field
DocType
default mode, global signal, gray matter, motion, regression, white matter
Default mode network,Neuroscience,White matter,Functional magnetic resonance imaging,Regression,Connectome,Resting state fMRI,Psychology,Correlation,Neuroimaging
Journal
Volume
Issue
ISSN
7
8
2158-0014
Citations 
PageRank 
References 
0
0.34
13
Authors
3
Name
Order
Citations
PageRank
Reinder Vos de Wael182.50
Fahmeed Hyder2429.53
Garth John Thompson31558.55