.. -*- mode: rst -*-

People
------

This work is made available by a community of people, which
originated from
the `INRIA Parietal Project Team <https://team.inria.fr/parietal/>`_
and the `scikit-learn <http://scikit-learn.org/>`_ but grew much further.

An up-to-date list of contributors can be seen in on `GitHub
<https://github.com/nilearn/nilearn/graphs/contributors>`_

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

.. _core_devs:

Core developers
...............

The nilearn core developers are:

* Alexandre Gramfort
* Bertrand Thirion
* Elizabeth DuPre
* Gael Varoquaux
* Jerome Dockes
* Julia Huntenburg
* KamalakerDadi
* Kshitij Chawla
* Nicolas Gensollen
* Binh Nguyen
* Thomas Bazeille
* Taylor Salo

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.
  
Funding
.......

Alexandre Abraham, Gael Varoquaux, Kamalakar Reddy Daddy, Loïc Estève,
Mehdi Rahim, Philippe Gervais were paid by the `NiConnect
<https://team.inria.fr/parietal/18-2/spatial_patterns/niconnect>`_
project, funded by the French `Investissement d'Avenir
<http://www.gouvernement.fr/investissements-d-avenir-cgi>`_.

NiLearn is also supported by `DigiCosme <https://digicosme.lri.fr>`_
|digicosme logo| and `DataIA <https://dataia.eu/en>`_ |dataia_logo|.

.. _citing:

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
<http://journal.frontiersin.org/article/10.3389/fninf.2014.00014/abstract>`_.

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
<http://scikit-learn.org/stable/about.html#citing-scikit-learn>`_.


.. |digicosme logo| image:: logos/digi-saclay-logo-small.png
    :height: 25
    :alt: DigiComse Logo

.. |dataia_logo| image:: logos/dataia.png
    :height: 25
    :alt: DataIA Logo