Hi Alan,

Try to redo the coregistration step for each subject by using the meanaf.img as your "Reference" image and the 3D-T1 image as you "Source" image....
Anyway, it is better to use the unified normalization-segmentation procedure (as you did in the past!)...
I hope this helps,

Mohamed


Alan Fermin wrote:

Dear SPM Users,

 

I am facing a trouble related to motion correction, and possibly, the processing stage.

 

In the past I used the procedures suggested in the SPM5 manual with the use of the parameter file, generated during the segmentation step, for normalizing the functional images. It worked fairly well.

 

But now I am reanalyzing the same data using slightly different preprocessing procedures. The new preprocessing steps are as follows:

 

1. SLICE TIMING - 2 sessions; # of slices: 30; TR:2; TA: 1.933; ascending interleaved; reference: 15.

2. REALIGNMENT ESTIMATE AND RESLICE - 2 sessions; register to first.

3. COREGISTER - meanaf.img + subject's own T1 3D structural image.

4. NORMALIZE ESTIMATE AND RESLICE - 1 subject; source: original T1 3D img; images to write: all realigned img + T1 3D img; voxel size: resampled from

3x3x5 to 3x3x3; template: MNI T1.

5. SMOOTH - all normalized images.

 

HERE IS THE PROBLEM

This partly new preprocessing procedure seems to work well through all the steps. However, after performing the first-level analysis and estimation and generation of contrast images, when I check the results, there seems to be some activation displacement, I mean, some activations apparently are located off the brain tissue.

 

I have tried other normalization methods as well, such as the one proposed on Christoff's lab website. But the same result awfully appears.

 

My guess is that the problem arises from the coregistration or normalization.

I don't know whether slice/voxel size resampling would cause such problem.

 

I have attached a PDF file with some images from the preprocessing stages and the results.

 

Would any fellow comment on the things I have done so far?

 

I would like to know how good are these steps above and which should be the best way?

 

I would very much appreciate your comments.

 

 

Alan Fermin, PhD student

Okinawa Institute of Science and Technology

Neural Computation Unit

http://www.nc.irp.oist.jp/

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Okinawa, Japan