help
help > RE: Correction for global signal
Nov 20, 2020 06:11 PM | Nobody
RE: Correction for global signal
Originally posted by Alfonso
Nieto-Castanon:
Dear
Natalia,
By default the conn toolbox uses CompCor, instead of global signal regression, to address potential subject-movement and physiological confounding effects without the risk of artificially introducing anticorrelations into your functional connectivity estimates, so generally I would not recommend using global signal regression instead. See this thread (https://www.nitrc.org/forum/forum.php?th...), or this reference (Chai X.J., Nieto-Castanon A., Ongur D., Whitfield-Gabrieli S. (2012) Anticorrelations in resting state networks without global signal regression. NeuroImage 59(2):1420-1428) for more details about this issue.
That said, if you still want to regress out the global signal you may do so (approximately) by entering the 'grey-matter' ROI into the 'confounds' list in the 'Preprocessing' tab (and probably removing the White-matter and CSF ROIs if you do not want to use the CompCor strategy), or (perhaps more precisely) by adding a new ROI in the 'Setup->ROIs' tab that encompass the entire brain (e.g. brainmask.nii if you are working on normalized volumes) and entering this ROI instead into the 'confounds' list in the 'Preprocessing' tab.
Hope this helps
Alfonso
By default the conn toolbox uses CompCor, instead of global signal regression, to address potential subject-movement and physiological confounding effects without the risk of artificially introducing anticorrelations into your functional connectivity estimates, so generally I would not recommend using global signal regression instead. See this thread (https://www.nitrc.org/forum/forum.php?th...), or this reference (Chai X.J., Nieto-Castanon A., Ongur D., Whitfield-Gabrieli S. (2012) Anticorrelations in resting state networks without global signal regression. NeuroImage 59(2):1420-1428) for more details about this issue.
That said, if you still want to regress out the global signal you may do so (approximately) by entering the 'grey-matter' ROI into the 'confounds' list in the 'Preprocessing' tab (and probably removing the White-matter and CSF ROIs if you do not want to use the CompCor strategy), or (perhaps more precisely) by adding a new ROI in the 'Setup->ROIs' tab that encompass the entire brain (e.g. brainmask.nii if you are working on normalized volumes) and entering this ROI instead into the 'confounds' list in the 'Preprocessing' tab.
Hope this helps
Alfonso
Hello all,
I am writing a conn batch script which does global signal regression along with other confounds. I share a list of confound names:
batch.Denoising.confounds.names={'White
Matter','CSF','head_movement'}
But I am not able to understand how should I add the name of a whole brain mask in the list. Will it be "art_mask_aurest.nii" file? If someone knows the name of the whole brain mask file generated by CONN's default prepocessing pipeline, please let me know. I am assuming that the following with appropriate filename should work:-
batch.Denoising.confounds.names={'White
Matter','CSF','head_movement', '.nii'}
Thank you and regards,
Rudradeep
Threaded View
| Title | Author | Date |
|---|---|---|
| Natalia Yakunina | Jul 15, 2013 | |
| Alfonso Nieto-Castanon | Jul 18, 2013 | |
| Sascha Froelich | Sep 9, 2016 | |
| Nobody | Nov 20, 2020 | |
| Alfonso Nieto-Castanon | Sep 9, 2016 | |
| Ben R | Apr 8, 2020 | |
| Scott Burwell | Sep 9, 2016 | |
| Natalia Yakunina | Jul 23, 2013 | |
| Jeff Browndyke | Aug 29, 2015 | |
| Alfonso Nieto-Castanon | Aug 31, 2015 | |
| Jeff Browndyke | Aug 31, 2015 | |
| Jeff Browndyke | Aug 28, 2015 | |
| Alfonso Nieto-Castanon | Aug 28, 2015 | |
| Jeff Browndyke | Aug 29, 2015 | |