Efficient Population-Representative Whole-Cortex Parcellation Based on Tractography
Résumé
The human brain is arranged in areas based on criteria such as cytoarchitecture or extrinsic connectivity. Current hypotheses attribute specialized functions to several areas of this patchwork. Hence, parcellating the cortex into such areas and characterizing their interaction is key to understanding brain function. Diffusion MRI enables the exploration of physical connections through axonal bundles, namely extrinsic connectivity. Current theories hold that brain function is determined by extrinsic connectivity. However, obtaining a population-representative parcellation based on extrinsic connectivity remains challenging (Jbabdi and Behrens, 2013). Particularly, whole-cortex parcellation methods (Moreno-Dominguez et al., 2014; Parisot et al., 2015) are computationally expensive and need tuning of several parameters. Our main contribution is an effcient technique to create single-subject and population-representative parcellations based on tractography. Our method creates a dendrogram using only one parameter: the minimum size of each parcel. Then, by choosing cutting criteria, we can explore different parcellation granularities without recomputing the dendrogram. Experiments show that our extrinsic based parcellations are consistent within subjects with anatomical
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