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Enhancing the Reproducibility of Group Analysis with Randomized Brain Parcellations

Abstract : Neuroimaging group analyses are used to compare the inter-subject variability observed in brain organization with behavioural or genetic variables and to assess risks factors of brain diseases. The lack of stability and of sensitivity of current voxel-based analysis schemes may however lead to non-reproducible results. A new approach is introduced to overcome the limitations of standard methods, in which active voxels are detected according to a consensus on several random parcellations of the brain images, while a permutation test controls the false positive risk. Both on syntetic and real data, this approach shows higher sensitivity, better recovery and higher reproducibility than standard methods and succeeds in detecting a significant association in an imaging-genetic study between a genetic variant next to the COMT gene and a region in the left thalamus on a functional Magnetic Resonance Imaging contrast.
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Submitted on : Tuesday, June 11, 2013 - 9:43:14 AM
Last modification on : Friday, November 18, 2022 - 9:27:43 AM
Long-term archiving on: : Thursday, September 12, 2013 - 4:06:19 AM


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  • HAL Id : hal-00832616, version 1



Benoit da Mota, Virgile Fritsch, Gaël Varoquaux, Vincent Frouin, Jean-Baptiste Poline, et al.. Enhancing the Reproducibility of Group Analysis with Randomized Brain Parcellations. MICCAI - 16th International Conference on Medical Image Computing and Computer Assisted Intervention - 2013, Sep 2013, Nagoya, Japan. ⟨hal-00832616⟩



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