Hi Rick,

Thanks for the quick reply!

If I'm using afni_proc.py, it failed at the regress step. Sometimes it looks something like

voxel loop: 012
killed

If I'm using 3dDeconvolve, it's the same situation.

The input to this step is usually around 32GB combining all the pb04* files. And the computers I'm running on are all iMac computers with MacOS. I try to run them on 64GB RAM machines, some succeeded and some failed. I don't understand why it took 5 whole days to finish. I checked the activity monitor and it seems there is plenty of RAM free...And if possible, I really want to run them on 32GB machines too.

I'll try the option -regress_compute_fitts with afni_procy.py. If I started with 3dDeconvolve, is there any way to reduce the RAM it used?

BTW, on the related note: every time I try to add some new contrasts to my analysis, I need to ran 3dDeconvolve with all the stim and glt labels. I don't know if it's the single stim labels or the glt contrasts that are taking so much time to fit. Is there any way to just add a new glt contrast quickly?

Thank you so much!

--Lingyan