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help > RE: Reviewer not familiar with CONN?
Oct 21, 2015 04:10 PM | Fran
RE: Reviewer not familiar with CONN?
Originally posted by Alfonso Nieto-Castanon:
Hi Jeff and
Fran,
Regarding the global signal regression question, I am typically in the exact opposite side of this where I would ask authors for a justification if they DID use GSR instead of one of the many current and arguably better/less-problematic alternatives (CompCor, FIX, AROMA, retroicor, etc.) In addition to your response I would probably just point the reviewer towards a number of publications discussing the issues with GSR (e.g. Murphy et al. 2009, Schölvinck et al. 2010, Chai et al. 2012, Saad et al. 2012, Gotts et al. 2013). Most reviewers should be satisfied if you simply justify your choice even if they do not share your perspective (and if you feel that an additional analyses might help I would suggest to simply enter the gray-matter ROI signal in CONN as an additional confouding effect during denoising and see whether your main results still replicate; even though I personally do not love this approach because of the many confounding effects that this may incurr in)
Regarding the subject-motion response, CONN uses aCompCor (not tCompCor), mainly because tCompCor can just as easily pick-up neural signals from gray matter voxels which one does not want to include as denoising regressors (for the same reasons as in GSR). If you have used ART as part of preprocessing (e.g. in the default CONN preprocessing pipeline) I would mention that as well in the response, since that is one of the main protections agains motion outliers. All considered, it is not a bad idea to perform some additional post-hoc analyses to make sure that potential differences in subject-motion across groups are not influencing your results (and to that end I would probably use some proxy measure of subject-motion degree as an additional second-level covariate and then: a) test whether there are group differences in this measure of subject motion -e.g. in Tools.Calculator-; and b) add this covariate as an additional subject-effect in your main second-level analyses to see whether your results replicate when controlling for the degree of subject-motion)
Hope this helps
Alfonso
Hi Alfonso,
Regarding the global signal regression question, I am typically in the exact opposite side of this where I would ask authors for a justification if they DID use GSR instead of one of the many current and arguably better/less-problematic alternatives (CompCor, FIX, AROMA, retroicor, etc.) In addition to your response I would probably just point the reviewer towards a number of publications discussing the issues with GSR (e.g. Murphy et al. 2009, Schölvinck et al. 2010, Chai et al. 2012, Saad et al. 2012, Gotts et al. 2013). Most reviewers should be satisfied if you simply justify your choice even if they do not share your perspective (and if you feel that an additional analyses might help I would suggest to simply enter the gray-matter ROI signal in CONN as an additional confouding effect during denoising and see whether your main results still replicate; even though I personally do not love this approach because of the many confounding effects that this may incurr in)
Regarding the subject-motion response, CONN uses aCompCor (not tCompCor), mainly because tCompCor can just as easily pick-up neural signals from gray matter voxels which one does not want to include as denoising regressors (for the same reasons as in GSR). If you have used ART as part of preprocessing (e.g. in the default CONN preprocessing pipeline) I would mention that as well in the response, since that is one of the main protections agains motion outliers. All considered, it is not a bad idea to perform some additional post-hoc analyses to make sure that potential differences in subject-motion across groups are not influencing your results (and to that end I would probably use some proxy measure of subject-motion degree as an additional second-level covariate and then: a) test whether there are group differences in this measure of subject motion -e.g. in Tools.Calculator-; and b) add this covariate as an additional subject-effect in your main second-level analyses to see whether your results replicate when controlling for the degree of subject-motion)
Hope this helps
Alfonso
Hi Alfonso,
Thank you for your extremely valuable/helpful
reply. I checked the references you suggested in regard to GSR and
added them in my reply to the reviewer.
In regard to the motion effects/new analysis, I actually run all preprocessing on spm not on CONN. Further, the motion data were entered as covariates in the analysis (CONN) so I wonder if that would save me from running a new analysis.
Thank you in advance for your attention
Francesco
In regard to the motion effects/new analysis, I actually run all preprocessing on spm not on CONN. Further, the motion data were entered as covariates in the analysis (CONN) so I wonder if that would save me from running a new analysis.
Thank you in advance for your attention
Francesco
Threaded View
| Title | Author | Date |
|---|---|---|
| Fran | Oct 8, 2015 | |
| Jeff Browndyke | Oct 8, 2015 | |
| Alfonso Nieto-Castanon | Oct 9, 2015 | |
| Fran | Oct 21, 2015 | |
| Fran | Oct 9, 2015 | |