This work is made available by a community of people, which originated from the INRIA MIND Project Team and scikit-learn but grew much further.

An up-to-date list of contributors can be seen in on GitHub.

Additional credit goes to Michael Hanke and Yaroslav Halchenko for data and packaging.

Core developers#

The nilearn core developers are:

Other contributors#

Some other past or present contributors are:


Himanshu Aggarwal is paid by INRIA.

Rémi Gau is paid by a grant from the Chan Zuckerberg Initiative

Alexandre Abraham, Gael Varoquaux, Kamalakar Reddy Daddy, Loic Estève, Mehdi Rahim, Philippe Gervais were paid by the NiConnect. project, funded by the French Investissement d’Avenir.

Kshitij Chawla was paid by INRIA.

Yasmin Mzayek and Nicolas Gensollen were paid by the Human Brain Project HBP Logo.

NiLearn is also supported by DigiCosme DigiComse Logo and DataIA DataIA Logo.

Citing nilearn#

If you want to cite Nilearn, we suggest you do it using our Zenodo DOI:

    author = {Nilearn contributors},
    license = {BSD-4-Clause},
    title = {{nilearn}},
    url = {},
    doi = {}

Nilearn’s Research Resource Identifier (RRID) is: RRID:SCR_001362

There is no paper published about nilearn. However, the patterns underlying the package have been described in: Machine learning for neuroimaging with scikit-learn.

Citing scikit-learn#

A huge amount of work goes into scikit-learn, upon which nilearn relies heavily. Researchers who invest their time in developing and maintaining the package deserve recognition with citations. In addition, the INRIA MIND Project Team needs citations to the paper in order to justify paying a software engineer on the project. To guarantee the future of the toolkit, if you use it, please cite it.

See the scikit-learn documentation on how to cite.