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Abstract #3866

Global signal measures are significantly related to functional connectivity variations across scans both before and after global signal regression

Alican Nalci1, Wenjing Luo1, and Thomas T Liu1

1University of California, San Diego, La Jolla, CA, United States

Global signal regression (GSR) is widely employed to reduce the influence of nuisance factors in functional connectivity (FC) estimates. Here, we investigate the GS contributions to the variability of FC estimates across different scans. We show that correlation-based FC estimates are significantly related to the GS norms across scans. We further show that even after GSR there is still a significant relation between the GS norms and FC estimates, indicating that inter-scan FC variations can largely reflect GS effects both before and after GSR.

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