Abstract
Current theories hold that brain function is highly related with long-range physical connections through axonal bundles, namely extrinsic connectivity. However, obtaining a groupwise cortical parcellation based on extrinsic connectivity remains challenging. Current parcellation methods are computationally expensive; need tuning of several parameters or rely on ad-hoc constraints. Furthermore, none of these methods present a model for the cortical extrinsic connectivity. To tackle these problems, we propose a parsimonious model for the extrinsic connectivity and an efficient parcellation technique based on clustering of tractograms. Our technique allows the creation of single subject and groupwise parcellations of the whole cortex. The parcellations obtained with our technique are in agreement with anatomical and functional parcellations in the literature. In particular, the motor and sensory cortex are subdivided in agreement with the human homunculus of Penfield. We illustrate this by comparing our resulting parcels with an anatomical atlas and the motor strip mapping included in the Human Connectome Project data.
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Notes
- 1.
For the sake of clarity we denote all random variables with a tilde, e.g. \(\tilde{C}\).
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This work has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (ERC Advanced Grant agreement No 694665: CoBCoM).
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Gallardo, G., Fick, R., Wells, W., Deriche, R., Wassermann, D. (2017). Groupwise Structural Parcellation of the Cortex: A Sound Approach Based on Logistic Models. In: Fuster, A., Ghosh, A., Kaden, E., Rathi, Y., Reisert, M. (eds) Computational Diffusion MRI. MICCAI 2016. Mathematics and Visualization. Springer, Cham. https://doi.org/10.1007/978-3-319-54130-3_8
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