Hi,
I would like to run an ICA analysis using the FSL-MELODIC tool on fMRI scans
which I have spatially normalized using SPM2. First, the MPRAGE scan was
normalized to a customized group template (of scans normlized to the SPM
template). Second, I applied the resulting sn.mat to the fMRI scan,
converted it to the NIFTI format (fslchfiletype function) and started
Melodic. However, I received the error message "Two many components
selected" (see below).
The voxel size of the normalized sMRI scan was 1 x 1 x 1 mm, that of the
original fMRI scan (3.75 x 3.75 x 5 mm) and the voxel size of the
normalized fMRI scan was 2 x 2 x 2 mm.
I noted that there was an earlier message on a similar error message posted,
However the explanation of wrong indication of file path does not seem to
apply here.
http://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=ind0709&L=FSL&P=R16776&I=-3
Any suggestions would be greatly appreciated.
Regards,
Michael
/usr/local/fsl/bin/fslroi prefiltered_func_data example_func 0 1
/usr/local/fsl/bin/bet prefiltered_func_data prefiltered_func_data_bet -F
/usr/local/fsl/bin/fslmaths prefiltered_func_data_bet -thrp 10 -Tmin -bin
mask -odt char
/usr/local/fsl/bin/fslmaths prefiltered_func_data_bet -mas mask
prefiltered_func_data_bet
/usr/local/fsl/bin/fslmaths mask -kernel gauss 2.12314225053 -fmean
mask_weight -odt float
/usr/local/fsl/bin/fslmaths prefiltered_func_data_bet -kernel gauss
2.12314225053 -fmean -div mask_weight -mas mask filtered_func_data -odt float
/usr/local/fsl/bin/fslmaths filtered_func_data -ing 10000 filtered_func_data
-odt float
/usr/local/fsl/bin/fslmaths filtered_func_data -bptf 16.6666666667 -1
filtered_func_data -odt float
/usr/local/fsl/bin/fslhd -x filtered_func_data | sed 's/ dt = .*/ dt =
'3.0'/g' | /usr/local/fsl/bin/fslcreatehd - filtered_func_data
/usr/local/fsl/bin/fslmaths filtered_func_data -Tmean mean_func
/bin/rm -rf prefiltered_func_data*
ERROR:: too many components selected
Melodic Version 3.05
Melodic results will be in filtered_func_data.ica
Create mask ... done
Reading data file filtered_func_data ... done
Estimating data smoothness ... done
Removing mean image ... done
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