On 09/26/2013 02:54 PM, Connor Lane wrote:
> Great, thanks so much for the advice. Can you say a little about why
> pre-whitening needs to be turned off? I thought the process operated on
> each voxel's timeseries independently, so it wouldn't matter that the
> spatial relations are jumbled in the surface format. This isn't the case?
The FEAT prewhitening spatially smooths the autocorrelation function, 
and that will assume volumetric geometry.
>
> As far as writing a converter, my plan was to just modify the freesurfer
> tool to reshape with a remainder. E.g. The modified tool would convert
> between N x 1 x 1 x t surfaces and ceil(N/10) x 10 x 1 x t nifti files
> (with a 10 - remainder vector of 0s in each volume). Would this work? (It
> is a little beside the point, since I'm perfectly fine going straight to
> fsaverage.)
Yes, that should work, but you'll have to do the bookkeeping
doug
>
> Connor
>
> On 9/26/13 2:14 PM, "Douglas N Greve" <gr...@nmr.mgh.harvard.edu> wrote:
>
>>   I would actually put the data straight onto fsaverage, smooth there,
>> and do the FSL analysis there. You will need to put it on fsaverage
>> eventually for group analysis, and you're better off doing that before
>> doing the FEAT analysis. Remember to turn off temporal pre-whitening
>> when running FEAT.
>>
>> For nifti1, there is no solution to the prime number of vertices
>> problem. The problem is fixed in nifti2, so, assuming that FSL is
>> reading nifti2, you could write a mgh to nifti2 converter. But I would
>> do it on fsaverage anyway
>>
>> doug
>>
>>
>> On 09/26/2013 01:53 PM, Connor Lane wrote:
>>> Hmm, that's unfortunate.
>>>
>>> The reason I'm interested in this surface to nifti conversion is that
>>> I'm trying to incorporate surface based pre-stats smoothing into my FSL
>>> fMRI analysis stream. My strategy has been: preprocess with FSL --> map
>>> to surface space and smooth --> convert mgh surface to nifti surface and
>>> continue with FSL analysis.
>>>
>>> Do you think the surface smoothing benefits of this kind of stream
>>> justify the trouble associated with either a) modifying the data as you
>>> suggest every time this factoring issue shows up, or b) writing an mgh
>>> <-> nifti utility that avoids the issue?
>>>
>>> Some other possible answers I've thought of are:
>>>     -After surface smoothing, map the functional data to fsaverage and
>>> then convert back to nifti (since we know there's no factoring problem
>>> with fsaverage). The drawback here is we never get to see statistics in
>>> subject-specific space.
>>>     -Switch from FSL to FsFast, where surface smoothing is built in.
>>>
>>> Or maybe I should forget about surface based smoothing altogether, and
>>> actually volumetric smoothing works just fine?
>>>
>>> I would really appreciate hearing your overall recommendation on this.
>>>
>>> Connor
>>>
>>>
>>>
>>>
>> -- 
>> Douglas N. Greve, Ph.D.
>> MGH-NMR Center
>> gr...@nmr.mgh.harvard.edu
>> Phone Number: 617-724-2358
>> Fax: 617-726-7422
>>
>> Bugs: surfer.nmr.mgh.harvard.edu/fswiki/BugReporting
>> FileDrop: https://gate.nmr.mgh.harvard.edu/filedrop2
>> www.nmr.mgh.harvard.edu/facility/filedrop/index.html
>> Outgoing: ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/
>>
>>
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>

-- 
Douglas N. Greve, Ph.D.
MGH-NMR Center
gr...@nmr.mgh.harvard.edu
Phone Number: 617-724-2358
Fax: 617-726-7422

Bugs: surfer.nmr.mgh.harvard.edu/fswiki/BugReporting
FileDrop: https://gate.nmr.mgh.harvard.edu/filedrop2
www.nmr.mgh.harvard.edu/facility/filedrop/index.html
Outgoing: ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/

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