Comparing the means of 2 images

The goal of this example is to illustrate the use of the function nilearn.image.math_img with a list of images as input. We compare the means of 2 resting state 4D images. The mean of the images could have been computed with nilearn nilearn.image.mean_img function.

Fetching 2 subject movie watching brain development fmri datasets.

from nilearn import datasets
dataset = datasets.fetch_development_fmri(n_subjects=2)

Print basic information on the adhd subjects resting state datasets.

print('Subject 1 resting state dataset at: %s' % dataset.func[0])
print('Subject 2 resting state dataset at: %s' % dataset.func[1])

Subject 1 resting state dataset at: /home/alexis/nilearn_data/development_fmri/development_fmri/sub-pixar123_task-pixar_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz
Subject 2 resting state dataset at: /home/alexis/nilearn_data/development_fmri/development_fmri/sub-pixar001_task-pixar_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz

Comparing the means of the 2 movie watching datasets.

from nilearn import plotting, image

result_img = image.math_img("np.mean(img1, axis=-1) - np.mean(img2, axis=-1)",
                            img1=dataset.func[0],
                            img2=dataset.func[1])

plotting.plot_stat_map(result_img,
                       title="Comparing means of 2 resting state 4D images.")
plotting.show()

Estimated memory usage: 816 MB