What you have described should work. The residuals will be in whatever 
space the analysis was made in (mkanalysis-sess). What ROI are you 
trying to get an average over? What are your mkanalysis-sess and 
mri_segstats commands?


On 05/22/2018 10:26 PM, Mcnorgan, Christopher wrote:
> Hi,
>
> I have some BOLD data from a fast event-related experiment with 3 
> experimental conditions, 1, 2 and 3.  A reviewer wants me to isolate 
> the signal for condition 1. Under the assumptions of the GLM, the 
> signal is a linear combination of A1+B2+C3+Error, so it seems that I 
> need to construct a design matrix that contains only the onsets for B 
> and C, and then run selxavg3-sess with the —svres argument given. The 
> residuals should thus be the best estimate available of condition 1 + 
> error. So in a nutshell, I want the best approximation of the 
> preprocessed BOLD time series, as though conditions 2 and 3 never 
> happened, but without any other transformation of the BOLD data.
>
> I have a student working on this, but he’s running into a problem of 
> the residuals no longer being in anatomical space, or at least the 
> same anatomical space he started in (mri_segstats is reporting a 
> dimension mismatch, which is why I emphasized above I don’t want any 
> other transformations applied to the data). The data were originally 
> processed in fsaverage space. Barring my student accidentally 
> switching to the subject’s native surface space, is there any reason 
> what I’ve described above shouldn’t work?
>
> /**********************************************
> * Chris McNorgan
> * Assistant Professor
> * Department of Psychology
> * University at Buffalo,
> * The State University of New York
> * http://ccnlab.buffalo.edu/
> * Office: 716.645.0236
> * Lab: 716.645.0222
> **********************************************/
>
>
>
>
>
>
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