Hi PyMVPA users, I'm trying to perform a surface based analysis using the Haxby dataset and I've been stuck with the preprocessing of the fMRI dataset.
According to the tutorial page ( http://dev.pymvpa.org/datadb/tutorial_data.html#datadb-tutorial-data), the 4D fMRI time-series have been skull-stripped and motion corrected and the preprocessed data is the bold.nii.gz file. I tried doing similar preprocessing steps on all six raw bold data using either A) the following command: $ bet bold_raw bold_brain -F -f 0.5 -g 0 $ mcflirt -in bold_brain -out bold_mc -plots or B) pymvpa2-prep-fmri.py bold_raw I then checked the raw bold data and the output file (bold_mc.nii.gz) using $fslhd and fslview and found out that the qform_code and sform_code were both 0, and the volumes were incorrectly oriented (the axial and coronal views should be swapped and the sagittal view was in wrong orientation). However, for the preprocessed tutorial data bold.nii.gz, the header information qform_code and sform_code are both 1 and the qto_xyz and sto_xyz matrices are different from my preprocessed data. I was wondering whether I'm missing some key preprocessing steps which might lead to my incorrect results here. Any help would be greatly appreciated! Best, Xixi
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