Modeling and statistical inference on fMRI data in Python
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Nistats is a Python module for fast and easy modeling and statistical analysis of functional Magnetic Resonance Imaging data.

It leverages the nilearn Python toolbox for neuroimaging data manipulation (data downloading, visualization, masking).

This work is made available by a community of people, amongst which the INRIA Parietal Project Team and D'esposito lab at Berkeley.

It is based on developments initiated in the nipy nipy project.

Important links


The required dependencies to use the software are:

  • Python >= 2.7
  • setuptools
  • Numpy >= 1.11
  • SciPy >= 0.17
  • Nibabel >= 2.0.2
  • Nilearn >= 0.4.0
  • Pandas >= 0.18.0
  • Sklearn >= 0.18.0
  • Patsy >= 0.4.1

If you are using nilearn plotting functionalities or running the examples, matplotlib >= 1.5.1 is required.

If you want to run the tests, you need nose >= 1.2.1 and coverage >= 3.7.

If you want to download openneuro datasets Boto3 >= 1.2 is required


In order to perform the installation, run the following command from the nistats directory:

python install --user




You can check the latest sources with the command:

git clone git://

or if you have write privileges:

git clone