Thanks, I think I'm getting there! Okay, so for the full analysis after motion correction, do I plug in the output of the preprocessing feat (ie, reg/filtered_func_data), or do I got back to my original bold file?
Can I run the full feat on images in standard space (with input image reg_standard/filtered_func_data from featregapply)? Do I need to make any corrections to do that? Or just make sure all my inputs are in standard space? I've seen a few people suggesting that, so I wanted to clarify.
You had also mentioned using for the T1 in standard space from feat. Where is this image found? I haven't found any images in the feat directories that look like the T1 in standard space if I run flirt directly on the T1.
Finally, for the exchangeability blocks, I just wanted to check the glm I've devised:
Group Subject EV PT EV CTRL
1 Pt1_run1 1 0
1 Pt1_run2 1 0
1 Pt1_run3 1 0
1 Pt1_run4 1 0
2 Pt2_run1 1 0
3 Pt3_run1 1 0
3 Pt3_run2 1 0
3 Pt3_run3 1 0
3 Pt3_run4 1 0
4 Pt4_run1 1 0
4 Pt4_run2 1 0
5 Ctrl1_run1 0 1
5 Ctrl1_run2 0 1
5 Ctrl1_run3 0 1
6 Ctrl2_run1 0 1
7 Ctrl3_run1 0 1
7 Ctrl3_run2 0 1
8 Ctrl4_run1 0 1
9 Ctrl5_run1 0 1
9 Ctrl5_run2 0 1
Do I need to use PALM or can I still do dual_regression and randomise? All the runs are equivalent and obtained on the same day, so there are no paired repeated measures.
Thanks again so much! Happy Friday!
|