Hi there,
I am using conn (20.b). I am processing my data in subject-space and thus the QA plots look all wrong (Because an MNI template is used for the anatomical overlay. My intra-subject anatomical T1 and BOLD files are registered correctly and the QA registration plot looks fine).
Based on what you said in the previous post [quote]"Unfortunately, you are exactly right that this change also made the procedure inappropriate for datasets that are not in MNI-space."[/quote]
I was wondering if this has an effect on the actual denoising or if it is just problematic for the generation of the plots?
If it is a problem for the actual denoising, is what you suggested above an appropriate fix? [quote]In order to fix this I am thinking one potential approach would be having CONN keep the current strategy (selecting voxels randomly within the referenceGM mask) for those projects where the 'analysis mask' field (defined in Setup.Options) is set to the default value (i.e. mask.volume.brainmask.nii), which is indicative of the functional data actually being in MNI-space, while reverting to the previous strategy (selecting voxels randomly within the Gray Matter ROI masks) in all other cases.[/quote]
If so, is it sufficient to simply choose in Setup - Options: "Analysis mask (voxel-level): Implicit mask (subject-specific)" or do I need to do anything else? Could you tell me how exactly I would define this in a script?
Thank you very much in advance!
Cheers,
Julia
I am using conn (20.b). I am processing my data in subject-space and thus the QA plots look all wrong (Because an MNI template is used for the anatomical overlay. My intra-subject anatomical T1 and BOLD files are registered correctly and the QA registration plot looks fine).
Based on what you said in the previous post [quote]"Unfortunately, you are exactly right that this change also made the procedure inappropriate for datasets that are not in MNI-space."[/quote]
I was wondering if this has an effect on the actual denoising or if it is just problematic for the generation of the plots?
If it is a problem for the actual denoising, is what you suggested above an appropriate fix? [quote]In order to fix this I am thinking one potential approach would be having CONN keep the current strategy (selecting voxels randomly within the referenceGM mask) for those projects where the 'analysis mask' field (defined in Setup.Options) is set to the default value (i.e. mask.volume.brainmask.nii), which is indicative of the functional data actually being in MNI-space, while reverting to the previous strategy (selecting voxels randomly within the Gray Matter ROI masks) in all other cases.[/quote]
If so, is it sufficient to simply choose in Setup - Options: "Analysis mask (voxel-level): Implicit mask (subject-specific)" or do I need to do anything else? Could you tell me how exactly I would define this in a script?
Thank you very much in advance!
Cheers,
Julia
