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help > RE: parcellation based on voxel-to-voxel analysis
May 8, 2014 04:05 AM | Alfonso Nieto-Castanon - Boston University
RE: parcellation based on voxel-to-voxel analysis
Dear Hong,
Some thoughts on your questions below
Best
Alfonso
Originally posted by Jui Yang Hong:
You can apply small volume correction to your second-level statistics using SPM. Simply load click on SPM's 'results' and load the SPM.mat file in your second-level results folder (or if using CONN14c or above simply click on the 'display SPM' button on the seed-to-voxel or voxel-to-voxel results explorers), and then click on 'Small Volume' to apply this form of multiple comparison correction (that allows you to restrict multiple comparison corrections to a portion of the brain instead of using the entire brain).
2. For the RSC, I will have three contrasts in the second-level results, which contrast should I use for the parcellation or any way to summerise them all together?
You can simply select all three RSC measures and leave the default between-measures contrast (eye(3) or [1 0 0;0 1 0;0 0 1]) in order to look at the presence of an effect across any of the three measures.
3. Since I have only one group, I will assume the beta_0001.img and con_0001.img are the same?
Yes, exactly, for a one-sample t-test the files beta_0001.img and con_0001.img will be exactly the same.
Hope this helps!
Alfonso
Some thoughts on your questions below
Best
Alfonso
Originally posted by Jui Yang Hong:
1. For the small volume correction, I didn't see
the place I can apply the thalamus mask on the CONN toolbox, could
you tell me in which step and function or should I go matlab coding
it?
You can apply small volume correction to your second-level statistics using SPM. Simply load click on SPM's 'results' and load the SPM.mat file in your second-level results folder (or if using CONN14c or above simply click on the 'display SPM' button on the seed-to-voxel or voxel-to-voxel results explorers), and then click on 'Small Volume' to apply this form of multiple comparison correction (that allows you to restrict multiple comparison corrections to a portion of the brain instead of using the entire brain).
2. For the RSC, I will have three contrasts in the second-level results, which contrast should I use for the parcellation or any way to summerise them all together?
You can simply select all three RSC measures and leave the default between-measures contrast (eye(3) or [1 0 0;0 1 0;0 0 1]) in order to look at the presence of an effect across any of the three measures.
3. Since I have only one group, I will assume the beta_0001.img and con_0001.img are the same?
Yes, exactly, for a one-sample t-test the files beta_0001.img and con_0001.img will be exactly the same.
Hope this helps!
Alfonso
Threaded View
| Title | Author | Date |
|---|---|---|
| Jui Yang Hong | Apr 29, 2014 | |
| Alfonso Nieto-Castanon | May 1, 2014 | |
| Jui Yang Hong | May 2, 2014 | |
| Alfonso Nieto-Castanon | May 8, 2014 | |