Recent Publications

Thirion, B., Pinel, P., Tucholka, A., Roche, A., Ciuciu, P., Mangin, J. and Poline, J. (2007). Structural analysis of fMRI data revisited: improving the sensitivity and reliability of fMRI group studies.. {IEEE Transactions on Medical Imaging} 26: (1256-69). [www] [BibTeX]

@article{thirion:cea-00333747,
 author = {Thirion, B., Pinel, P., Tucholka, A., Roche, A., Ciuciu, P., Mangin, J. and Poline, J.},
 doi = {10.1109/TMI.2007.903226},
 hal_id = {cea-00333747},
 hal_version = {v1},
 journal = {{IEEE Transactions on Medical Imaging}},
 month = {September},
 number = {9},
 pages = {1256-69},
 pdf = {https://cea.hal.science/cea-00333747/file/TMI-2007-0195-R1.pdf},
 publisher = {{Institute of Electrical and Electronics Engineers}},
 title = {{Structural analysis of fMRI data revisited: improving the sensitivity and reliability of fMRI group studies.}},
 url = {https://cea.hal.science/cea-00333747},
 volume = {26},
 year = {2007}
}

Lebenberg, J., Mangin, J., Thirion, B., Poupon, C., Hertz-Pannier, L., Leroy, F., Adibpour, P., Dehaene-Lambertz, G. and Dubois, J. (2019). Mapping the asynchrony of cortical maturation in the infant brain: a MRI multi-parametric clustering approach. {NeuroImage} 185: (641-653). [www] [BibTeX]

@article{lebenberg:hal-01966812,
 author = {Lebenberg, J., Mangin, J., Thirion, B., Poupon, C., Hertz-Pannier, L., Leroy, F., Adibpour, P., Dehaene-Lambertz, G. and Dubois, J.},
 doi = {10.1016/j.neuroimage.2018.07.022},
 hal_id = {hal-01966812},
 hal_version = {v1},
 journal = {{NeuroImage}},
 keywords = {diffusion  tensor  imaging DTI ; clustering ; Magnetic  resonance  imaging  MRI ; infancy ; Human Brain Project (HBP) ; quantitative  T1  and  T2  mapping ; cortical maturation},
 month = {January},
 pages = {641-653},
 pdf = {https://hal.science/hal-01966812/file/LebenbergDubois_neuroimage19_vf.pdf},
 publisher = {{Elsevier}},
 title = {{Mapping the asynchrony of cortical maturation in the infant brain: a MRI multi-parametric clustering approach}},
 url = {https://hal.science/hal-01966812},
 volume = {185},
 year = {2019}
}

Genuer, R., Michel, V., Eger, E. and Thirion, B. (2010). Random Forests based feature selection for decoding fMRI data. {COMPSTAT 2010 - 19th International Conference on Computational Statistics} [www] [BibTeX]

@inproceedings{genuer:hal-00944114,
 address = {Paris, France},
 author = {Genuer, R., Michel, V., Eger, E. and Thirion, B.},
 booktitle = {{COMPSTAT 2010 - 19th International Conference on Computational Statistics}},
 hal_id = {hal-00944114},
 hal_version = {v1},
 month = {August},
 pages = {1071-1078},
 title = {{Random Forests based feature selection for decoding fMRI data}},
 url = {https://inria.hal.science/hal-00944114},
 year = {2010}
}

Thirion, B., Varoquaux, G., Grisel, O., Poupon, C. and Pinel, P. (2014). Principal Component Regression predicts functional responses across individuals. {MICCAI} [www] [BibTeX]

@inproceedings{thirion:hal-01015173,
 address = {Boston, United States},
 author = {Thirion, B., Varoquaux, G., Grisel, O., Poupon, C. and Pinel, P.},
 booktitle = {{MICCAI}},
 hal_id = {hal-01015173},
 hal_version = {v1},
 keywords = {fMRI ; principal components regression ; random effects},
 month = {September},
 pdf = {https://inria.hal.science/hal-01015173/file/paper_869.pdf},
 publisher = {{Springer}},
 title = {{Principal Component Regression predicts functional responses across individuals}},
 url = {https://inria.hal.science/hal-01015173},
 year = {2014}
}

Thirion, B., Pinel, P., M{\'e}riaux, S., Roche, A., Dehaene, S. and Poline, J. (2007). Analysis of a large fMRI cohort: Statistical and methodological issues for group analyses.. {NeuroImage} 35: (105-20). [www] [BibTeX]

@article{thirion:cea-00371089,
 author = {Thirion, B., Pinel, P., M{\'e}riaux, S., Roche, A., Dehaene, S. and Poline, J.},
 doi = {10.1016/j.neuroimage.2006.11.054},
 hal_id = {cea-00371089},
 hal_version = {v1},
 journal = {{NeuroImage}},
 month = {March},
 number = {1},
 pages = {105-20},
 pdf = {https://cea.hal.science/cea-00371089/file/Localizer.pdf},
 publisher = {{Elsevier}},
 title = {{Analysis of a large fMRI cohort: Statistical and methodological issues for group analyses.}},
 url = {https://cea.hal.science/cea-00371089},
 volume = {35},
 year = {2007}
}

Eickhoff, S., Thirion, B., Varoquaux, G. and Bzdok, D. (2016). Connectivity-Based Parcellation: Critique and Implications. {Human Brain Mapping} . [www] [BibTeX]

@article{eickhoff:hal-01184563,
 author = {Eickhoff, S., Thirion, B., Varoquaux, G. and Bzdok, D.},
 doi = {10.1002/hbm.22933},
 hal_id = {hal-01184563},
 hal_version = {v1},
 journal = {{Human Brain Mapping}},
 keywords = {statistical learning ; data-driven ; diffusion MRI ; brain parcellation ; clustering ; resting-state correlations ; statistical inference ; double dipping},
 month = {January},
 pages = {22},
 pdf = {https://hal.science/hal-01184563/file/cbp_critique_subm.pdf},
 publisher = {{Wiley}},
 title = {{Connectivity-Based Parcellation: Critique and Implications}},
 url = {https://hal.science/hal-01184563},
 year = {2016}
}

Hoyos-Idrobo, A., Varoquaux, G., Kahn, J. and Thirion, B. (2016). Recursive nearest agglomeration (ReNA): fast clustering for approximation of structured signals. {IEEE Transactions on Pattern Analysis and Machine Intelligence} XX: (). [www] [BibTeX]

@article{hoyosidrobo:hal-01366651,
 author = {Hoyos-Idrobo, A., Varoquaux, G., Kahn, J. and Thirion, B.},
 doi = {10.1109/TPAMI.2018.2815524},
 hal_id = {hal-01366651},
 hal_version = {v2},
 journal = {{IEEE Transactions on Pattern Analysis and Machine Intelligence}},
 keywords = {matrix sketching ; dimensionality reduction ; clustering ; neuroimaging ; classification ; approximation},
 month = {August},
 pdf = {https://inria.hal.science/hal-01366651v2/file/paper.pdf},
 publisher = {{Institute of Electrical and Electronics Engineers}},
 title = {{Recursive nearest agglomeration (ReNA): fast clustering for approximation of structured signals}},
 url = {https://inria.hal.science/hal-01366651},
 volume = {XX},
 year = {2016}
}

Full list of publications

Tweets by bthirion

Short Bio

Bertrand Thirion is researcher in the Mind team, part of Inria research institute, Saclay, France, that develops statistics and machine learning techniques for brain imaging. He contributes both algorithms and software, with a special focus on functional neuroimaging applications. He is involved in the Neurospin, CEA neuroimaging center, one of the leading high-field MRI for brain imaging places. From 2018 to 2021, Bertrand Thirion has been the head of the DATAIA Institute that federates research on AI, data science and their societal impact in Paris-Saclay University. In 2020, he has recently been appointed as member of the expert committee in charge of advising the government during the Covid-19 pandemic. In 2021, he has become the Head of science (délégué scientifique) of the Inria Saclay-Île-de-France research center. Bertrand Thirion is PI of the Karaib AI Chair of the Individual Brain CHarting project.

Contact

Email: bertrand.thirion@inria.fr

Address: Inria Saclay Île-de-France, Bâtiment Alan Turing, 1 rue Honoré d'Estienne d'Orves, Campus de l'École Polytechnique 91120 Palaiseau

Software

Nilearn - A package for statistical analysis and machine learning on functional Magnetic resonance Imaging (fMRI) data
Scikit-Learn - Machine learning in Python

Team

Engineers

Himanshu Aggarwal

Post-docs

PhD Students

Sonia Mazelet, co-advised with Remi Flamary
[Thomas Chapalain], co-advised with Evelyn Eger
Joseph Paillard, co-advised with Denis Engemann
Alexandre Blain co-advised with Pierre Neuvial
Nicolas Salvy, co advised with Hugues Talbot

Master Students

Louis Jalouzot coadvised with Christophe Pallier
Pierre-Louis Barabarant
Angel Reyero Lobo co-advised with Pierre Neuvial

Alumni

[Alan Tucholka]
[Vincent Michel]
[Cécilia Damon]
[Virgile Fritsch]
[Viviana Siless]
[Hao Xu]
[Alexandre Abraham]
[Michael Eickenberg]
[Yannick Schwartz]
[Andrés Hoyos Idrobo]
[Arthur Mensch]
[Ana Luisa Grilo Pinho]
[Kamalaker Dadi]
[Juan Jesus Tresols]
[Lucas Martin]
[Jérôme Dockès]
[Elvis Dohmatob]
[Hugo Richard]
[Jerome-Alexis Chevalier]
[Tuan Binh Nguyen]
Thomas Bazeille
[Alexandre Pasquiou]
Jospeh Benzakoun
[Alexis Thual]
Ahmad Chamma
Raphael Meudec
Judith Abecassis
[Swetha Shankar]
Nicolas Gensollen
[Gaël Varoquaux]
[Alexandre Gramfort]
[Benoit da Mota]
[Bernard Ng]
[Torsten Ruest]

Positions

PhD/Post-doc positions on machine learning and statistics with applications in neuroimaging (functional Magnetic Resonance Imaging).

This list is fuzzy so please contact me directly for potential opportunities.

Teaching

Functional brain imaging course in Master MVA Ecole Normale Supérieure de Paris Saclay: Covers the machine learning and statistical aspects of modern brain imaging, with an emphasis on cognitive analysis and population studies.