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

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

Additional credit goes to M. Hanke and Y. Halchenko for data and packaging.

Other contributors

Some other past or present contributors are:

  • Abadie, A.

  • Abraham, A.

  • Bellec, P.

  • Bougacha, S.

  • Bzdok, D.

  • Chevalier, J.A.

  • Cipollini., B.

  • Dohmatob, E.

  • Eickenberg, M.

  • Esteve, L.

  • Fritsch, V.

  • Gervais, P.

  • Hoyos Idrobo, A.

  • Gorgolewski, C.F.

  • Kossaifi, J.

  • Michel, V.

  • Pedregosa, F.

  • Perez, M.


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

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

Citing nilearn

There is no paper published yet about nilearn. We are waiting for the package to mature a bit. However, the patterns underlying the package have been described in: Machine learning for neuroimaging with scikit-learn.

We suggest that you read and cite the paper. Thank you.

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 Parietal 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.