sdm-help-list
sdm-help-list > Surface-based morphometry data
Aug 13, 2019 06:08 PM | Avi G - University of Toronto
Surface-based morphometry data
Hi experts,
I am conducting a meta-analysis with seed-based d Mapping on surface-based morphometry (SBM) data. Specifically, the studies I am including investigated local Gyrification Index (lGI) differences in individuals with ASD compared to controls (on FreeSurfer). Since I am new in using SDM (and doing a meta-analysis) and also using this tool for meta-analyzing SBM data, I have a few questions below that I'd really appreciate advice on:
1. All papers included in my meta-analysis report surface coordinates (of fsaverage). My understanding is that I would have to first convert these reported coordinates to coordinates in MNI space, correct? and after doing so, to save these coordinates in files ending with *.other_mni.txt. for each study, correct?
2. In this help-list you've previously mentioned to use an appropriate cortical gray matter mask (specifically the gray matter analyzed in a SBM software) when working with SBM data on SDM. Would it be possible for me to contact you directly to get more information regarding this? As I couldn't find more information online.
3. Some of my studies reported no significant between-group differences in lGI. Would I make *.no_peaks.txt files for these studies and simply leave these files empty?
4. I don't have t-statistics reported in my studies, however, I do have p-values reported. When I use the "Two-sample p to t converter" on SDM website do I change the sign of the t-value the converter gives me according to the following : negative if ASD < controls [i.e. 40, 21, 30, -1.34]; positive if ASD > controls [i.e. 40, 21, 30, 1.34] ? Because I noticed that the converter always gives a negative t-value (however sometimes the actual finding of the study may be ASD > controls).
5. In pre-processing stage ('pre processing parameters' window): Considering that I am working with SBM data, do I also select "VBM- gray matter" for my modality? and anisotropy of 1, FWHM of 20, voxel size of 2?
I'd really appreciate your help as I am very excited to use SDM for meta-analyzing SBM studies.
Thanks so much,
Avi
I am conducting a meta-analysis with seed-based d Mapping on surface-based morphometry (SBM) data. Specifically, the studies I am including investigated local Gyrification Index (lGI) differences in individuals with ASD compared to controls (on FreeSurfer). Since I am new in using SDM (and doing a meta-analysis) and also using this tool for meta-analyzing SBM data, I have a few questions below that I'd really appreciate advice on:
1. All papers included in my meta-analysis report surface coordinates (of fsaverage). My understanding is that I would have to first convert these reported coordinates to coordinates in MNI space, correct? and after doing so, to save these coordinates in files ending with *.other_mni.txt. for each study, correct?
2. In this help-list you've previously mentioned to use an appropriate cortical gray matter mask (specifically the gray matter analyzed in a SBM software) when working with SBM data on SDM. Would it be possible for me to contact you directly to get more information regarding this? As I couldn't find more information online.
3. Some of my studies reported no significant between-group differences in lGI. Would I make *.no_peaks.txt files for these studies and simply leave these files empty?
4. I don't have t-statistics reported in my studies, however, I do have p-values reported. When I use the "Two-sample p to t converter" on SDM website do I change the sign of the t-value the converter gives me according to the following : negative if ASD < controls [i.e. 40, 21, 30, -1.34]; positive if ASD > controls [i.e. 40, 21, 30, 1.34] ? Because I noticed that the converter always gives a negative t-value (however sometimes the actual finding of the study may be ASD > controls).
5. In pre-processing stage ('pre processing parameters' window): Considering that I am working with SBM data, do I also select "VBM- gray matter" for my modality? and anisotropy of 1, FWHM of 20, voxel size of 2?
I'd really appreciate your help as I am very excited to use SDM for meta-analyzing SBM studies.
Thanks so much,
Avi
Threaded View
Title | Author | Date |
---|---|---|
Avi G | Aug 13, 2019 | |
Anton Albajes-Eizagirre | Aug 14, 2019 | |
Avi G | Aug 20, 2019 | |
Joaquim Radua | Aug 27, 2019 | |
Avi G | Sep 5, 2019 | |
Avi G | Sep 3, 2019 | |
Avi G | Aug 27, 2019 | |
Hui Zheng | Aug 15, 2019 | |