Hi --pt,
first of all, thanks for your answer!
I was able to replicate your exampe for the AFNI_data6 func slim file, but it still is different for my dataset.
Regarding the difference between bisided and 2sided: Your're right, I should use bisided, as there's a chance that positive and negative voxels might happen to be next to each other. But there's no -bisided option in 3dClust, is there?
I've just had a look with
3dinfo -verb ...file+tlrc and I'm thinking maybe my issue has something to with internal vs scaled?
-- At sub-brick #5 'Int-Ctlr_over_Time' datum type is short: -18946 to 32767 [internal]
[* 1.02413e-05] -0.194032 to 0.335577 [scaled]
So maybe 3dclust and AFNI GUI are using "scaled" and 3dClusterize is using "internal"? Can I get 3dClusterize to use "scaled", as well?
Thanks for the hint with -noabs, that does indeed make the mean negative :)
> Do you have a particular use case in mind for applying individual ROIs?
After looking at the rs-fmri data (analyzing a few different ICs), my next step is going to be to correlate scores from a neurophysiological test.
I don't really know how I'm going to do that yet (I was busy figuring 3dlmer out :D) , but my supervisor pointed me towards
either 1. inserting the score as a covariate into 3dlmer or
2. getting mean beta values from one of my intermediate steps at each cluster that is observed to be different between Control and Intervention and correlating those with the outcome scores in R.
I figured option 2 sounds easier and can eventually be done in homeoffice, as well. Instead of setting up multiple 3dlmer models and adding each neurophysological outcome parameter as a covariate separately (I don't want to control the model for all those outcome measures, I just want see if there's a correlation between one of them and the imaging data/ the changes observed).
As I said, I haven't really looked into this yet. But if I'm totally off track, please do correct me.
-- Agent 007 ;)
Edited 1 time(s). Last edit at 04/29/2021 01:21PM by AFNIuser007.