Hi,

you should co register your structural scans with robust-register or robust-template (if you have more than 2). This can be done into the midspace to make sure both time points are mapped to avoid processing bias.

You can then register the functional scans to their corresponding structurals and concat the transforms to get everything into the same midspace.

Best, Martin


On 02/10/2016 12:48 PM, Ji Won Bang wrote:
Dear. Freesurfer team.

Thanks so much your help and advice.

Based on the comments, I'm trying freesurfer version 5.3.0 instead of 4.5.0 now.

In our experiment, each participant is scanned twice on different days and the functional scan's brain volume are different (some scans have 33 number of slices, some have 32 number of slices).

Since participants moved a bit between scans on the same day, and the head position is different between different days, my advisor advised me to do co-registration between different functional scans and then do co-registration between anatomical and functional scans.

My question is this.

If I do motion-correction such that we align all EPI data to the first EPI of the first functional scan, will it be enough for co-registration between different functional scans and different days? Or should I do coregistration-specific process such as mri_robust_register, mri_robust_template etc?

Or I guess the method I choose should depend on how much the participant moved between scans and how much different the head position was between different days? For example, if the participant was very still between runs and the head position was not that too different, this motion correction is enough for coregistration between functional scans. However, if not, I should do coregistration-specific process such as mri_robust_register, mri_robust_template etc?

I'd appreciate any of your advice.

Please feel free to let me know your thoughts.

Best,
Ji Won

2016-02-08 22:31 GMT-05:00 Douglas Greve <gr...@nmr.mgh.harvard.edu <mailto:gr...@nmr.mgh.harvard.edu>>:

    In 4.5 I don't think there is a way to run it when different runs
    have different number of slices. Version 5+ will handle it
    properly. If you really want to use 4.5, then you'll have to put
    it in a different functional subdir (FSD, eg, bold), and create a
    new analysis for it, then combine them together after analysis. A
    bit of a hassle.


    On 2/8/16 5:58 PM, Ji Won Bang wrote:
    Dear. Freesurfer team.

    As another attempt, I run the motion correction without the
    argument -targrun:

    mc-sess -s $SUBJECT -df sessdirfile -fsd bold_retino

    However, I get the same error message again.

    Why is that?

    Thanks so much for your effort and time.

    I appreciate it a lot.

    Best,
    Ji Won


    2016-02-08 17:16 GMT-05:00 Ji Won Bang <kirsten...@gmail.com
    <mailto:kirsten...@gmail.com>>:

        Dear. Freesurfer team.

        I'd appreciate any advice from you.

        When doing the motion correction, I'd like to align all EPI
        data(bold_retino) to the first EPI of target
        run(bold_decode/003). However, the number of slices for
        target run(33) and the number of slices(32) for input
        run(bold_retino) are different.

        When I type: mc-sess -s $SUBJECT -df sessdirfile -fsd
        bold_retino -targrun $DATA_DIR/$SUBJECT/bold_decode/003

        Freesurfer says that:
        ** FATAL ERROR: perhaps you could make your datasets match?
        ERROR: 3dvolreg
        Invalid null command.

        These two kinds of run (bold_decode, bold_retino) were
        collected in one scan per subject, so the head position
        should not be too different...

        Do you have any suggestions for fixing this error?

        Should I do 3dWarp -deoblique?

        Thank you so much.

        Best,
        Ji Won

        2016-02-08 16:30 GMT-05:00 Ji Won Bang <kirsten...@gmail.com
        <mailto:kirsten...@gmail.com>>:

            Dear. Freesurfer team.

            Hi.

            I'm using freesurfer 4.5 version.

            While doing the motion correction, an error occurred.

            the command I used:
            mc-sess -s $SUBJECT -df sessdirfile -fsd bold_retino
            -targrun $DATA_DIR/$SUBJECT/bold_decode/003

            the error I have:
            /home/jbang/Projects/replay/epi/replay01/bold_retino
            3dvolreg -verbose -dfile 025/fmc.mcdat -base
            025/tmp.mc-afni2.32291/tempvol.nii.gz -prefix
            025/tmp.mc-afni2.32291/outvol.nii.gz
            025/tmp.mc-afni2.32291/invol.nii.gz
            ++ 3dvolreg: AFNI version=AFNI_2008_07_18_1710 (Feb 10
            2009) [64-bit]
            ++ Authored by: RW Cox
            *+ WARNING:   If you are performing spatial
            transformations on an oblique dset,
              such as 025/tmp.mc-afni2.32291/tempvol.nii.gz,
              or viewing/combining it with volumes of differing
            obliquity,
              you should consider running:
                 3dWarp -deoblique
              on this and  other oblique datasets in the same session.
             See 3dWarp -help for details.
            ++ Oblique dataset:025/tmp.mc-afni2.32291/tempvol.nii.gz
            is 3.263868 degrees from plumb.
            ++ Reading in base dataset
            025/tmp.mc-afni2.32291/tempvol.nii.gz
            ++ Oblique dataset:025/tmp.mc-afni2.32291/invol.nii.gz is
            4.564286 degrees from plumb.
            ++ centers of base and input datasets are 9.09 mm apart
            ** Input ./invol.nii.gz+orig.HEAD and base
            ./tempvol.nii.gz+orig.HEAD don't have same dimensions!
               Input: nx=74  ny=74  nz=32
               Base:  nx=74  ny=74  nz=33
            ** FATAL ERROR: perhaps you could make your datasets match?
            ERROR: 3dvolreg
            Invalid null command.

            I think it's because the volume size is different.

            The volume size for bold_retino is: number of slices 32
            The volume size for bold_decode: number of slices 33

            What should I do to correct this error?

            Thank you for taking your time.

            Best,
            Ji Won





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