Extracting voxels within a mask for GLM in nilearn

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Hi everyone,
I want to fit GLM to a specific set of voxels rather than the whole brain. For this purpose, I created a mask using NiftiMasker class from nilearn. My code is like the following:

mask_img= nib.load(‘mask_img.nii’)
func_data= nib.load(‘func_data.nii’)
masker= NiftiMasker(mask_img, target_affine= func_data.affine, target_shape=
func_data.get_fdata()[:,:,:,1]
masker.fit()
masked_data= masker.inverse_transform(masker.transform_single_imgs(func_data))

This way, I get a nifti image with the exact dimension of my func_data and only the voxels within the mask. Am I doing it right? Is there any other way to extract the voxels within a mask rather than transforming and inverse transforming?

Any input would be highly appreciated! Thanks!

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AFAICT you’re doing it right.
But, why not simply provide your selective mask together with the fMRI data to the GLM model ? It should be able to handle it. Let me know if you encounter an issue when doing so.
HTH,
Bertrand

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Hi Bertrand,
Thanks for your confirmation! Actually, I don’t know how to include a mask with fMRI data in GLM. Could you please share an example in nilearn?
Regards,
Nahid

4

Hi @Nhasan ,

If I understand your question, I’d recommend looking at this example in the docs !

You can substitute your mask of interest for mask_img=data['mask'].

HTH,

Elizabeth

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