Skip to main content

Modeling and Statistical analysis of fMRI data in Python

Project description


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.


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

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for nistats, version 0.0.1b0
Filename, size File type Python version Upload date Hashes
Filename, size nistats-0.0.1b0-py3-none-any.whl (93.8 kB) File type Wheel Python version py3 Upload date Hashes View hashes
Filename, size nistats-0.0.1b0.tar.gz (75.3 kB) File type Source Python version None Upload date Hashes View hashes

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page