Welcome

Camille

Hi! I'm Camille Maumet, a research scientist in neuroinformatics at the Empenn team, Inria Rennes Bretagne Atlantique / IRISA.

I study neuroimaging reproducibility. My current research focuses on the variability of analytical pipelines and its impact on our ability to reuse (and use) brain imaging datasets. I am also an open science advocate and participate actively in international communities including Brainhack, the INCF, and OHBM Open Science SIG.

Latest talks

titre
Towards reproducible neuroimaging across different analysis pipelines
article
CogBases 2023, Oct 2023, Paris, France. 2023
Accès au texte intégral et bibtex
https://inria.hal.science/hal-04236791/file/Maumet_Cogbases_repro_neuroimaging.pdf BibTex
titre
Open science practices for keeping inventions alive after project ends
article
ESMRMB 2023 - 39th Annual Scientific Meeting on European Society for Magnetic Resonance in Medicine and Biology, Oct 2023, Basel (CH), Switzerland. 2023
Accès au texte intégral et bibtex
https://inria.hal.science/hal-04236827/file/Maumet_ESMRMB_keeping%20inventions%20alive%20after%20project%20ends.pdf BibTex
titre
BIDS-Prov: Recording neuroimaging provenance
article
Brain Imaging Data Structure (BIDS) derivatives meeting, Jun 2023, Copenhagen, Denmark
Accès au texte intégral et bibtex
https://inria.hal.science/hal-04137329/file/2023-06_Maumet_BIDS-derivatives_%20BIDS-Prov.pdf BibTex

Latest Publications

ref_biblio
Elodie Germani, Elisa Fromont, Camille Maumet. Exploring variability patterns in the task-fMRI analytical space. OHBM 2023 - 29th Annual Meeting of the Organization for Human Brain Mapping, Jul 2023, Montreal, Canada. ⟨hal-03991042⟩
Accès au texte intégral et bibtex
https://inria.hal.science/hal-03991042/file/abstract_OHBM.pdf BibTex
ref_biblio
Elodie Germani, Elisa Fromont, Camille Maumet. On the benefits of self-taught learning for brain decoding. GigaScience, 2023, 12, pp.1-17. ⟨10.1093/gigascience/giad029⟩. ⟨hal-03769993v6⟩
Accès au texte intégral et bibtex
https://inria.hal.science/hal-03769993/file/on_the_benefits_of_self_taught_learning.pdf BibTex
ref_biblio
Aya Kabbara, Nina Forde, Camille Maumet, Mahmoud Hassan. Successful reproduction of a large EEG study across software packages. Neuroimage: Reports, In press, 3 (2), pp.100169. ⟨10.1016/j.ynirp.2023.100169⟩. ⟨inserm-03747289⟩
Accès au texte intégral et bibtex
https://inserm.hal.science/inserm-03747289/file/Kabbara_1-s2.0-S2666956023000144-main.pdf BibTex
ref_biblio
Freya Acar, Camille Maumet, Talia Heuten, Maya Vervoort, Han Bossier, et al.. Review Paper: Reporting Practices for Task fMRI Studies. Neuroinformatics, 2022, ⟨10.1007/s12021-022-09606-2⟩. ⟨inserm-03800029⟩
Accès au texte intégral et bibtex
https://inserm.hal.science/inserm-03800029/file/Review%20paper_reporting%20practices%20for%20fMRI%20studies_Acaretal_Neuroinformatics.pdf BibTex
ref_biblio
Guiomar Niso, Rotem Botvinik-Nezer, Stefan Appelhoff, Alejandro de La Vega, Oscar Esteban, et al.. Open and reproducible neuroimaging: from study inception to publication. NeuroImage, 2022, ⟨10.1016/j.neuroimage.2022.119623⟩. ⟨inserm-03646706⟩
Accès au texte intégral et bibtex
https://inserm.hal.science/inserm-03646706/file/Open%20and%20reproducible%20neuroimage_2022.pdf BibTex