Hi Doug,
I use the following command for fslmaths
fslmaths fmc.nii -bptf 200 2 fmcfilt.nii

where 200*(TR+2) is 400s, and 2*(TR=2)=4s.

and for mkanalysis-sess
-force
-fsd bold
-funcstem fmcfilt
-analysis name
-notask
-tr 2
-runlistfile name
-native
-nskip 5
-mask brain
-tpef name
-taskreg name

for debugging, I did not include nuisance regressors.
Caspar


2012/5/7 Douglas N Greve <greve@nmr.mgh.harvard.edu>
What frequencies did you chose for the FSL bandpass filter? What is you mkanalysis-sess command?


On 05/07/2012 02:58 PM, Caspar M. Schwiedrzik wrote:
yes

2012/5/7 Douglas N Greve <greve@nmr.mgh.harvard.edu <mailto:greve@nmr.mgh.harvard.edu>>


   Did you regenerate the seeds after filtering?


   On 05/07/2012 02:50 PM, Caspar M. Schwiedrzik wrote:

       I have tried analyses with only one seed time course (either 1
       voxel, mean of a sphere of 1 voxel radius, or mean of a
       functionally defined roi), as well as several seeds within the
       same design matrix, with the same problem.
       All of these analyses did yield higher pcc when done without
       filtering.
       Caspar

       2012/5/7 Douglas N Greve <greve@nmr.mgh.harvard.edu
       <mailto:greve@nmr.mgh.harvard.edu>
       <mailto:greve@nmr.mgh.harvard. edu

       <mailto:greve@nmr.mgh.harvard.edu>>>


          Is this doing all of those seeds simultaneously or one seed
       at a time?

          On 05/07/2012 02:25 PM, Caspar M. Schwiedrzik wrote:
       > Hi,
       > I am trying to use fslmaths to filter my data before I plug it
          into a
       > resting state analysis. However, once I obtain a pcc map, all
       > correlation coefficients are <0.1, even the autocorrelation
       with the
       > seed voxel.
       > The data look fine when I open them in Matlab using MRIread; the
       > correlations between individual voxel time courses obtained in
          Matlab
       > is about 0.6.
       >
       > My analysis stream is as follows:
       > a) I filter the data using "fslmaths input -bptf highpass
       lowpass
       > output"; from this I obtain a filtered nii.gz file
       > b) I extract a seed timecourse from the filtered data in Matlab
       > c) I run mkanalysis-sess with -notask
       > d) I run selxavg3-sess
       > e) I overlay the pcc.nii
       >
       > I have tried this with smoothed and unsmoothed data, with and
          without
       > nuisance regressors, with different seeds, with mri_convert
          after step
       > a. It is not a problem with the overlay since the max values
       in pcc
       > are all <0.1.
       > I noticed that there are some differences in the nifti header
          (as read
       > with MRIread) before and after filtering, but it seemed to
       me that
       > they are gone after I used mri_convert.
       > I do find much higher correlations with unfiltered data.
       > Any advice what could be going wrong here? I am using
       Freesurfer 5.1
       > and FSL 4.1.9 on Linux.
       > Thanks, Caspar
       >
       >
       >
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