Sorry.  My mistake. I'm so used to answering VBM questions, and not used to people wanting to get better results from their fMRI.

Yes, you are right.  The way you originally had the batch is correct.

(4). Normalize into MNI space
  DARTEL template: template_6.nii
  Few subjects
    Flow fields = u_rc1xx
    Images = rxxx.nii
  Preserve = Preserve Concentrations ("no modulation")

Now it makes sense that you wanted 2mm voxel sizes and no "modulation".

Best regards,

-John

On 28 July 2016 at 18:16, 陳志剛 <[log in to unmask]> wrote:

Hi John,

Thanks but, my aim is to normalize my realigned EPI data (that's why I use " Images = rxxx.nii").

 Your suggestion (i.e., " Images = cxxx.nii") seems normalizing the gray matter of structural imaging to MNI space, right?

Or, maybe you mean that, using "Flow fields = u_rc1xx;  Images = cxxx.nii," it will produce a xxx_sn.mat file, and then I do the following to normalize my EPI data?

Normalize: Write         

  Parameter files: xxx_sn.mat        

  Images to write: rxxx.nii        

  Voxel size: [2 2 2]         

  Interpolation: 7th degree B-spline

Mike

2016-07-29 0:23 GMT+08:00 John Ashburner <[log in to unmask]>:

I'd suggest:

(4). Normalize into MNI space
  DARTEL template: template_6.nii
  Few subjects
    Flow fields = u_rc1xx
    Images = cxxx.nii
  Preserve = Preserve Amount ("modulation")

It's been a while since I've done anything with SPM8, but I guess you could use a voxel size of 2 mm. I don't know if it makes any difference to the results.

Best regards,
-John

On 28 July 2016 at 16:06, 陳志剛 <[log in to unmask]> wrote:

Hi John,

Thanks. Let me clarify further, please.

This is my original batch:

(1). Segment
  Images = Coregistered T1WI
  Grey matter/white matter/CSF = Native space
  [This process produced a xxx_sn.mat file as well as c1xx, c2xx, c3xx files corresponging to GM, WM, and CSF]

(2). DARTEL tool, Initial import
  Parameter files = xxx_sn.mat
  GM, WM, CSF: Yes
  Voxel size: 1.5
  [This process produced rc1xx, rc2xx, rc3xx file]

(3). DARTEL tool, run DARTEL
  Images: rc1xx, rc2xx, rc3xx
  [This process produced u_rc1xx, u_rc2xx, u_rc3xx file, and a series of template files, with the last one called template_6.nii]

(4). Normalize into MNI space
  DARTEL template: template_6.nii
  Few subjects
    Flow fields = u_rc1xx
    Images = rxxx.nii
  Preserve = Preserve Concentrations ("no modulation")
  [This process produced swrxxx.nii but also Template_6_2mni.mat]

By saying "I'd suggest normalising the native-space images (c*.nii) rather than the imported versions (rc*.nii), as this can reduce aliasing effects", do you mean:

(4). Normalize into MNI space
  DARTEL template: template_6.nii
  Few subjects
    Flow fields = c1xx
    Images = rxxx.nii
  Preserve = Preserve Concentrations ("no modulation")
  [This process produced swrxxx.nii but also Template_6_2mni.mat]

Also, for the voxel size issue, how about:

(2). DARTEL tool, Initial import
  Parameter files = xxx_sn.mat
  GM, WM, CSF: Yes
  Voxel size: 2.0

Thanks in advance.

Mike

2016-07-28 20:59 GMT+08:00 John Ashburner <[log in to unmask]>:

I'd suggest normalising the native-space images (c*.nii) rather than the imported versions (rc*.nii), as this can reduce aliasing effects.

As for whether or not you use modulation when you write out the warped images, this will depend on your actual question.  Do you want to see where there are differences in the registration errors of one group versus the other, or do you want to see the differences in tissue volumes?  I find it hard to put a biological interpretation on unmodulated VBM results, although they seem to lead to greater sensitivity to differences.

There's no easy way to change the voxel sizes of the spatially normalised images.  If you want to do this, you'll need to write MATLAB code.

Smoothing is combined with writing out the warped images.  If you don't want it to smooth, you can set the FWHM to zero.

Best regards,

-John

On 27 July 2016 at 21:18, Mike <[log in to unmask]> wrote:

Hi DARTELers,

Because my subjects are aged patients with possible brain structural changes, I want to perform DARTEL normalization rather than default spatial normalization in SPM8 so as to have a better spatial normalization.

All EPI images were adjusted for timing differences between slices, unwarped using field maps, realigned and re-sliced to correct for motion artifacts (producing rxxx.nii). The resulting mean EPI was co-registered with the subject's T2-weighted image, which in turn was aligned with the T1-weighted image (that is, T1WI has been coregistered to EPI).

Below is my procedure for DARTEL normalization and I hope someone could help to confirm my procedures:

(1). Segment
  Images = Coregistered T1WI
  Grey matter/white matter/CSF = Native space
  [This process produced a xxx_sn.mat file as well as c1xx, c2xx, c3xx files corresponging to GM, WM, and CSF]

(2). DARTEL tool, Initial import
  Parameter files = xxx_sn.mat
  GM, WM, CSF: Yes
  Voxel size: 1.5
  [This process produced rc1xx, rc2xx, rc3xx file]

(3). DARTEL tool, run DARTEL
  Images: rc1xx, rc2xx, rc3xx
  [This process produced u_rc1xx, u_rc2xx, u_rc3xx file, and a series of template files, with the last one called template_6.nii]

(4). Normalize into MNI space
  DARTEL template: template_6.nii
  Few subjects
    Flow fields = u_rc1xx
    Images = rxxx.nii
  Preserve = Preserve Concentrations ("no modulation")
  [This process produced swrxxx.nii but also Template_6_2mni.mat]

Are my procedures correct?
However, the voxel size in swrxxx.nii is 1.5x1.5x1.5. If I want to get a MNI standard space with 2x2x2 voxel size, how should I do?
Also, (4) performed not only normalization but automatically smoothing process...

Thanks in advance. Mike