It might be better to spatial smoothing after calling applywarp rather than
before. Also, I wouldn't necessarily put --nomask and --nobet in the melodic
command line unless you have already applied a brain mask to your input files.
Otherwise it looks good. Note that (although I've not personally used it) the
Melodic GUI is supposed to do much of this for you automatically.
On Monday, October 17, 2011 08:12:29 you wrote:
> Hi Steve,
>
> sorry for the confusion, I may not have been writing out things properly,
> will do this now:
>
> 1.I first use feat to pre-process the subjects data, ie. Motion correction,
> B0 unwarping, smoothing and high-pass filtering. I also do the
> linear/nonlinear registration to highres and then to standard space.
>
> 2.Then I bring the individuals filtered_func data into standard space:
> applywarp --ref=${FSLDIR}/data/standard/MNI152_T1_2mm --in=$filtered_func
> --warp=$warp --premat=$premat –out=$output
>
> 3.I apply command-line melodic in temporal concatenation mode on standard
> space data. Note I run it on all subjects (patients and controls) without
> specifying any contrasts: melodic -i filtered_func_warp .txt -o melodic -a
> concat --nomask --nobet --mmthresh=0.5 --tr=3 --report -v –Oall
>
> 4.Then I run dual_regression, specifying the groups. Note I included a 3rd
> EV column to account for slightly different acquisition parameters (ie
> there are a several subjects where the acquisition matrix was slightly
> different from the majority of subjects, I attach the simple design)
> dual_regression melodic_ados/melodic_IC 1 design.mat design.con 5000
> melodic_dual_reg `cat filtered_func_warp .txt `
>
> So my questions:
> 1. Does this procedure look OK to you? Particularly the simple design...
> 2. If I wanted to include the motion parameters, I'd need to use fsl_glm
> before? Is this generally recommended to do?
>
> Thank you so much in advance for your patience.
>
> All the best,
>
> Torsten
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