Hey guys,

Trying to properly understand beginning steps of Context Dependent Connectivity Analysis (ie. /gangc/CD-CorrAna.html and Cisler 2013 paper) before I tackle it actively. In both the above sources it says to use as an input file, the subject data "which you have already run regression analysis on with 3dDeconvolve". Next you create your interaction regressor by multiplying your masked ROI signal from this deconvolved dataset by your expected HDR function and your -1/0/1's contrast coded, TR synced, stim onset file (ie. what Gang seems to create via steps 2-5).

So I am confused/curious on a few things:

1a. Which subbrick or output file from 3ddeconvolve should I using as the input data? ( ie. The full MSE model, Fstat, All_Betas, fitts, stats?)

1b. Why does this input need to already be deconvolved if we are putting pretty much all the same motion and stim onset regressors into 3ddeconvolve in step 6? Seems like we are removing effects of no interest twice...

2. Why do you need to detrend ROI data if you are masking it from 3dDecon output. Im pretty sure most preprocessing pipelines leading up to activation analysis with 3dDeconvolve already incorporate detrending.

3a. Can you use -cbucket components of an original activation analysis for any of this, to skip complex use of waver and 3dtfitter (ie. Gang's steps 3 and 4.... or..... "the part that really flummoxed me")? For instance the "ideal_cond.1D" files multiplied by TR contrast -1/0/1 onsets be sufficient? Or is it still necessary to create the Impulse response GAM function with waver and other steps etc...

Thanks as always. You guys are life savers for us students.

~`Dane



Edited 1 time(s). Last edit at 09/04/2014 11:16PM by d6anders.