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  Groupwise structural parcellation of the whole cortex: A logistic random effects model based approach

Gallardo, G., Wells, W., Deriche, R., & Wassermann, D. (2018). Groupwise structural parcellation of the whole cortex: A logistic random effects model based approach. NeuroImage, 170, 307-320. doi:10.1016/j.neuroimage.2017.01.070.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0006-B836-E Version Permalink: http://hdl.handle.net/21.11116/0000-0006-B837-D
Genre: Journal Article

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 Creators:
Gallardo, Guillermo1, Author              
Wells, William1, Author
Deriche, Rachid1, Author
Wassermann, Demian1, Author
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1External Organizations, ou_persistent22              

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Free keywords: Structural parcellation; Statistical clustering models; Tractography; Structural connectivity
 Abstract: Current theories hold that brain function is highly related to 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 of the cortex. To tackle these problems, we propose a parsimonious model for the extrinsic connectivity and an efficient parceling 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 structural 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 the motor strip mapping included in the Human Connectome Project data.

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Language(s): eng - English
 Dates: 2017-01-302016-12-052017-01-302017-02-012018-04-15
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Degree: -

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Title: NeuroImage
Source Genre: Journal
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Publ. Info: Orlando, FL : Academic Press
Pages: - Volume / Issue: 170 Sequence Number: - Start / End Page: 307 - 320 Identifier: ISSN: 1053-8119
CoNE: https://pure.mpg.de/cone/journals/resource/954922650166