Hi all,
I have analyzed a task based fmri dataset using fsl feat. Now, that I have some interesting finding between two groups in the FEAT 2nd level analysis, I want to take it to the next level : do machine learning(ML) - classification/prediction using PRONTO, or tools similar to that.
My question is, what image(s) per subject from FEAT should I use as my feature/input image for my ML algorithm? Would it be the cope image? z-stat image? or a combination of images on which FEAT performs the ttest during group-level analysis.
For instance, if I wanted to do ML on DTI data, I could use normalized FA images as my feature/input image.
I hope it's not a convoluted problem.
Thanks in advance for the reply.
Binod
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