Hi Jason, Tim,
yes this a problem I also ran into, solved it accessing the data in python
with memmap specifying C order (instead of Fortran order as used in Nifti1
and nibabel nifti2 implementation)
using:
nii = nb.load(ts_file) # just to get header infos
tss = np.memmap(nii.get_filename(),
nii.get_data_dtype(),
shape=nii.shape,
offset=nii.header.get_data_offset(),
order='C',
mode='r')
Basile
On Mon, Jan 20, 2014 at 11:01 PM, Timothy Coalson <[email protected]> wrote:
>
> You may be running into an unfortunate design problem in CIFTI-1, if
NiBabel expects them to be standard NIfTI-2 - the dimensions are backwards
in the header, so non-square matrices will have their elements rearranged.
You may be able to get matlab to fix them via a reshape with the
dimensions swapped. Alternatively, you can use wb_command -cifti-convert
-to-gifti-ext to get them into a file that should read correctly per the
GIFTI standard (and the matlab gifti toolbox).
>
> CIFTI-2 will fix this problem, but hasn't been finalized yet (it is
currently open for comments, see
http://www.nitrc.org/forum/message.php?msg_id=9303).
>
> Tim
>
>
>
> On Mon, Jan 20, 2014 at 11:13 AM, Jason Bohland <[email protected]> wrote:
>>
>> Hi. I've been working on putting together some ROI-level correlation
matrices from individual HCP data. I'm trying to use the wb_command
-cifti-parcellate to give me region level time series. I have been a bit
surprised by the results of this operation, and I wanted to verify that
what I'm seeing is correct, and ask a few questions. I appreciate any
guidance. I'll use subject 100307 as an example.
>>
>> 1) To get out cortical surface ROI time series, I started with the
following:
>>
>> wb_command -cifti-parcellate
rfMRI_REST1_LR_Atlas_hp2000_clean.dtseries.nii
../../fsaverage_LR32k/100307.aparc.a2009s.32k_fs_LR.dlabel.nii COLUMN
100307.cortical.ptseries.nii
>>
>> 2) To get out subcortical ROI time series, I used:
>>
>> wb_command -cifti-create-label subcortical_label.nii -volume
../../ROIs/Atlas_ROIs.2.nii.gz ../../ROIs/Atlas_ROIs.2.nii.gz
>>
>> wb_command -cifti-parcellate
rfMRI_REST1_LR_Atlas_hp2000_clean.dtseries.nii subcortical_label.nii COLUMN
100307.subcortical.ptseries.nii
>>
>> 3) Then I use Python with NiBabel ('1.4.0dev') to read and examine the
resulting matrices:
>>
>> ipython --pylab
>>
>> import nibabel as nb
>>
>> subcortical =
squeeze(nb.load('100307.subcortical.ptseries.nii').get_data())
>>
>> subcortical.shape
>> Out[7]: (19, 1200)
>>
>> cortical = squeeze(nb.load('100307.cortical.ptseries.nii').get_data())
>>
>> cortical.shape
>> Out[11]: (75, 1200)
>>
>> plot(subcortical.T)
>> hold(True)
>> plot(cortical.T)
>> xlabel('Scans')
>>
>> *** The resulting plot is attached ***
>>
>> Note the step-wise form of the curves, which does not appear correct
(and does not correspond well to the global mean in the dtseries file),
especially since the subcortical and cortical ROI curves are quite
different. In fact, it appears that the "number of steps" may equal the
number of ROIs (19 vs. 75) in each family of curves? This makes me think
that either nibabel is improperly loading the ptseries data, or
cifti-parcellate is not functioning correctly, but I haven't been able to
determine which is true.
>>
>> Is it possible to examine the data from the ptseries files any other
way? I tried -nifti-information -display-matrix but I get a message saying
this is not supported. I don't know of any other way to read in the
ptseries data.
>>
>> >>wb_command -nifti-information 100307.subcortical.ptseries.nii
-print-matrix
>> Printing Matrix/Volume information is only supported for Cifti.
>>
>>
>> As an additional question, assuming I'm going about this in a reasonable
way, and that I can find a way to read or export the resulting data, can I
assume that the ordering of the ROIs in the NIFTI/CIFTI matrix rows follows
the numerical ordering of the ids from FreeSurfer?
>>
>> Many thanks for your help,
>> -Jay
>>
>>
>>
>>
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>
>
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