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Hi Uri,
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<div class="">You will have to tell Cifti what is along this new axis you created. One way to do this is to use the cifti2 axes (<a href="https://nipy.org/nibabel/reference/nibabel.cifti2.html#module-nibabel.cifti2.cifti2_axes" class="">https://nipy.org/nibabel/reference/nibabel.cifti2.html#module-nibabel.cifti2.cifti2_axes</a>).
After creating newdata this would look like:</div>
<div class="">>>> from nibabel import cifti2</div>
<div class="">>>> new_axis = cifti2.ScalarAxis([f"parcel {idx + 1}" for idx in range(N)]) # these are the names for all the parcels; you might want to replace them with something more meaningfull</div>
<div class="">>>> grayordinate_axis = dsobj.header.get_axis(1) # get a description of the greyordinate space from the loaded CIFTI file</div>
<div class="">>>> newobj = nb.Cifti2Image(newdata, (new_axis, grayordinate_axis)) # creates a new Cifti2 header based on these axes</div>
<div class="">This newobj will have the shape of (N, 64984) for N parcels.</div>
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<div class="">However, based on your description I'm not completely sure if this is what you want to be doing. The output will still be a 2D CIFTI file rather than a 4D NIFTI file. If you want the latter, just reshape the newdata to be 4D using something like
`newdata.T.reshape(64984, 1, 1, N)` and create a new nb.Nifti1Image object from that data.</div>
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<div class="">Good luck,</div>
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<div class="">Michiel</div>
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<div class="">On 24 Oct 2020, at 19:05, Uri Elias <<a href="mailto:uri.urie@gmail.com" class="">uri.urie@gmail.com</a>> wrote:</div>
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Hi All,<br class="">
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Top level - I'd like to apply dual regression on rest fMRI based on parcellation where my rs-fMRI data in in CIFTI format.<br class="">
<br class="">
For a dual-regression SW I've chosen FSL, also because it works on Cifti (according to manual).<br class="">
For parcellation I've chosen the Schaefer parcellation, as it is Cifti-available and also partially based on rest-fMRI.<br class="">
<br class="">
Now, the Cifti parcellation file is a dscalar file (that is - a single volume/surface), with each greyordinate belongs to one of N parcels. FSL (AFAIU) requires a 4D file as a reference<br class="">
Working with nibabel, reformatting the matrix is easy - reading it with nibabel and do something like: for k in range(N):
<div class=""> newdata[k,:] = (orgdata==k+1).astype(float) <br class="">
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Updating the Nifti header is also easy - <br class="">
newobj = nb.Cifti2Image(newdata, dscobj.header, dscobj.nifti_header)<br class="">
newobj.update_headers()<br class="">
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The problem with this way is the the Cifti header is not being updated - </div>
<div class=""> newobj.header.matrix.get_data_shape()<br class="">
yeilds </div>
<div class=""> (1, 64984)<br class="">
<br class="">
What's a good way of doing this? - either by sticking to the nibabel->FSL line right or by any alternative<br class="">
<br class="">
Thanks all so much,<br class="">
Uri<br clear="all" class="">
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<h3 style="margin: 0px;" class=""><span style="font-size:16px" class="">Uri Elias</span></h3>
<div style="margin: 0px; line-height: 20px;" class="">Computational Neuropsychiatry Lab </div>
<div style="margin: 0px; line-height: 20px;" class="">Hadassah Hebrew University Medical School</div>
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