The perils of global signal regression for group comparisons: a case study of Autism Spectrum Disorders

Abstract

We have previously argued from a theoretical basis that the standard practice of regression of the Global Signal from the fMRI time series in functional connectivity studies is ill advised, particularly when comparing groups of participants. Here, we demonstrate in resting-state data from participants with an Autism Spectrum Disorder and matched controls that these concerns are also well founded in real data. Using the prior theoretical work to formulate predictions, we show: (1) rather than simply altering the mean or range of correlation values amongst pairs of brain regions, Global Signal Regression systematically alters the rank ordering of values in addition to introducing negative values, (2) it leads to a reversal in the direction of group correlation differences relative to other preprocessing approaches, with a higher incidence of both long-range and local correlation differences that favor the Autism Spectrum Disorder group, (3) the strongest group differences under other preprocessing approaches are the ones most altered by Global Signal Regression, and (4) locations showing group differences no longer agree with those showing correlations with behavioral symptoms within the Autism Spectrum Disorder group. The correlation matrices of both participant groups under Global Signal Regression were well predicted by our previous mathematical analyses, demonstrating that there is nothing mysterious about these results. Finally, when independent physiological nuisance measures are lacking, we provide a simple alternative approach for assessing and lessening the influence of global correlations on group comparisons that replicates our previous findings. While this alternative performs less well for symptom correlations than our favored preprocessing approach that includes removal of independent physiological measures, it is preferable to the use of Global Signal Regression, which prevents unequivocal conclusions about the direction or location of group differences.

Altered global brain signal in schizophrenia

“…Present effects have important implications for the widespread use of GSR in rs-fcMRI clinical studies, which remains controversial (16,23). If groups differ in GS properties, GSR may affect between-group differences in complex ways (23).…”

“…Present effects have important implications for the widespread use of GSR in rs-fcMRI clinical studies, which remains controversial (16,23). If groups differ in GS properties, GSR may affect between-group differences in complex ways (23). Informed by the neurobiology of SCZ, we tested this possibility in two ways: focusing on prefrontal cortex (PFC) (17) and thalamo-cortical networks (6,18,24).…”

“…A key objective of this study was empirical, namely to establish evidence for greater GS variance in SCZ. However, this finding has methodological implications for many future clinical connectivity studies, as GSR has been hypothesized to impact patterns of between-group differences in such studies (16,23). Here it is important to examine which measures may be sensitive to GSR in between-group clinical comparisons because of greater GS variance in SCZ.…”

Save the Global: Global Signal Connectivity as a Tool for Studying Clinical Populations with Functional Magnetic Resonance Imaging

“…As the authors noted, this finding is specifically relevant to clinical research that compares patients and healthy controls after global signal regression. Indeed, this finding was recently supported experimentally using resting-state data of participants with autism (Gotts et al, 2013). However, given the enormous variance in neural manifestations of different mental pathologies, it is currently unclear whether these findings may be generalized to other clinical populations.…”

Functional connectivity-based subtypes of individuals with and without autism spectrum disorder

“…For instance, Muller et al (2011) found that studies supporting the "general underconnectivity" hypothesis of ASD were more likely to not use lowpass filtering and to utilize ROIs as opposed to whole-brain analyses. It has also been reported that removal of the global signal alters group differences in FC observed between participants with ASD and TD participants (Gotts et al, 2013). Therefore, it is crucial to gain a more thorough understanding of how a variety of preprocessing choices affect observed group differences in FC, and to compare FC-based subtypes of ASD across different preprocessing strategies.…”