help
help > RE: Question about "Demeaning & Detrending" strategy as identified in Ciric et al., 2017, Satterthwaite et al., 2019
Apr 1, 2020 10:04 PM | Alfonso Nieto-Castanon - Boston University
RE: Question about "Demeaning & Detrending" strategy as identified in Ciric et al., 2017, Satterthwaite et al., 2019
Hi Billy,
If I am not mistaken demeaning simply refers to subtracting the average BOLD signal value (averaged across all timepoints within each run/session) separately for each voxel, which is a standard practice both for activation- (e.g. in SPM these are often referred to as "main session effects", and they are always present in the design matrix of all SPM first-level analyses) and connectivity- based analyses (e.g. in CONN the average BOLD signal is always removed as part of the Denoising step). In my experience demeaning/centering is often not explicitly mentioned since it is redundant with other common denoising steps such as high-pass filtering (any high-pass filter will also subtract/remove the average BOLD signal / 0Hz component).
Best
Alfonso
Originally posted by An Chuen Cho:
If I am not mistaken demeaning simply refers to subtracting the average BOLD signal value (averaged across all timepoints within each run/session) separately for each voxel, which is a standard practice both for activation- (e.g. in SPM these are often referred to as "main session effects", and they are always present in the design matrix of all SPM first-level analyses) and connectivity- based analyses (e.g. in CONN the average BOLD signal is always removed as part of the Denoising step). In my experience demeaning/centering is often not explicitly mentioned since it is redundant with other common denoising steps such as high-pass filtering (any high-pass filter will also subtract/remove the average BOLD signal / 0Hz component).
Best
Alfonso
Originally posted by An Chuen Cho:
Hello all,
As I'm working on the preprocessing/denoising methods of my paper, I came across a term that I'm unfamiliar with and very little leads as to what it means. In two recent denoising strategies papers (references below), one of the denoising strategies is "demeaning & detrending". I've come to understand that detrending is an option that can be done in CONN's denoising tab, but I am unfamiliar with what "demeaning" means. Initial guesses were that it is the same as global signal regression, but that is classified as its own strategy in the two papers. Would anyone happen to know what this "demeaning" is referring to, what it tries to do, and how it is done?
I'm very much looking forward to your response, thank you!
Sincerely,
Billy
Ciric, R., Wolf, D. H., Power, J. D., Roalf, D. R., Baum, G. L., Ruparel, K., ... & Gur, R. C. (2017). Benchmarking of participant-level confound regression strategies for the control of motion artifact in studies of functional connectivity. Neuroimage, 154, 174-187.
Satterthwaite, T. D., Ciric, R., Roalf, D. R., Davatzikos, C., Bassett, D. S., & Wolf, D. H. (2019). Motion artifact in studies of functional connectivity: Characteristics and mitigation strategies. Human brain mapping, 40(7), 2033-2051.
As I'm working on the preprocessing/denoising methods of my paper, I came across a term that I'm unfamiliar with and very little leads as to what it means. In two recent denoising strategies papers (references below), one of the denoising strategies is "demeaning & detrending". I've come to understand that detrending is an option that can be done in CONN's denoising tab, but I am unfamiliar with what "demeaning" means. Initial guesses were that it is the same as global signal regression, but that is classified as its own strategy in the two papers. Would anyone happen to know what this "demeaning" is referring to, what it tries to do, and how it is done?
I'm very much looking forward to your response, thank you!
Sincerely,
Billy
Ciric, R., Wolf, D. H., Power, J. D., Roalf, D. R., Baum, G. L., Ruparel, K., ... & Gur, R. C. (2017). Benchmarking of participant-level confound regression strategies for the control of motion artifact in studies of functional connectivity. Neuroimage, 154, 174-187.
Satterthwaite, T. D., Ciric, R., Roalf, D. R., Davatzikos, C., Bassett, D. S., & Wolf, D. H. (2019). Motion artifact in studies of functional connectivity: Characteristics and mitigation strategies. Human brain mapping, 40(7), 2033-2051.
Threaded View
| Title | Author | Date |
|---|---|---|
| An Chuen Cho | Apr 1, 2020 | |
| Alfonso Nieto-Castanon | Apr 1, 2020 | |
| An Chuen Cho | Apr 1, 2020 | |