Enhancing the Reproducibility of Group Analysis with Randomized Brain Parcellations - Mota, Benoit Da; Fritsch, Virgile; Varoquaux, Gaël; Frouin, Vincent; Poline, Jean-Baptiste; Thirion, Bertrand (Medical Image Computing and Computer-Assisted Intervention, 2013)
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.