Hi Robin,

1) Anaticor does not have anything in particular to do with AM analysis. It is just one method to try to remove some scanner, respiration or other artifacts. It was not a necessary part of the NARPS analysis.


2) Resp actually has 2 amplitude modulators, while NoResp has none. However, we were still getting event durations from the timing files for the NoResp class, even though the durations were constant. So there was no actual duration modulation for NoResp. But it was coded with AM1 and dmBLOCK just to fit the style of the model and to get consistency in the meanings of the betas (e.g. BLOCK(4,1) would have yielded the same stats (ind and group) on NoResp, but would have altered the scaling of those betas).

Yes, the events look like that. With 2 amplitude modulators plus a duration, the first event for one subject was 4.071*14*6:2.388 (so 14 and 6 were modulators, and the duration (until button press) was 2.388s).

The NoResp events all had duration 4.

For any runs without a NoResp response, we used -1:1, but -10:0.0001 is great.


3) Resp[1] and Resp[2] refer to the betas of the 2 modulators. Resp[0] refers to the beta of the mean response. So Resp[1] -Resp[2] is the difference of modulation effects.


Indeed, feedback#0_coef is the unmodulated feedback beta and #1 is the modulated one. A contrast between the two would be encoded 'SYM: feedback[0] -feedback[1]'. HOWEVER, that would suggest you have taken great care to make sure the magnitudes of the modulation parameters give it a sort of unit height. Otherwise the contrast would not be appropriate.

For example, if the modulators ranged between 0 and 100 (which would be demeaned in 3dDeconvolve), the betas might be 1/100th of the typical magnitude of the #0 coefs. I see a value near -1 for your modulator, which is encouraging.


4) You say the stimuli are short, but are they consistent? Do they range from 0.1 to 0.8, or are they all near 0.6, for example? If they are consistent, there is no need to use dmBLOCK, you could use BLOCK(0.6,1), say, and still use AM2 (but not AM1).


For the FS output, the mask.aseg.wm.e1.nii.gz dataset was eroded by 1 voxel outside of afni_proc.py, as you show in the global process link. So yes, you could do that if you chose. Though again, ANATICOR is not so necessary.

- rick