This title appears in the Scientific Report :
2013
Please use the identifier:
http://dx.doi.org/10.1016/j.neuroimage.2013.04.003 in citations.
Microstructural grey matter parcellation and its relevance for connectome analyses.
Microstructural grey matter parcellation and its relevance for connectome analyses.
The human brain connectome is closely linked to the anatomical framework provided by the structural segregation of the cortex into distinct cortical areas. Therefore, a thorough anatomical reference for the analysis and interpretation of connectome data is indispensable to understand the structure a...
| Personal Name(s): | Caspers, Svenja (Corresponding author) |
|---|---|
| Eickhoff, Simon / Zilles, Karl / Amunts, Katrin | |
| Contributing Institute: |
Strukturelle und funktionelle Organisation des Gehirns; INM-1 |
| Published in: | NeuroImage, 80 (2013) S. 18-26 |
| Imprint: |
Orlando, Fla.
Academic Press
2013
|
| PubMed ID: |
23571419 |
| DOI: |
10.1016/j.neuroimage.2013.04.003 |
| Document Type: |
Journal Article |
| Research Program: |
Helmholtz Alliance on Systems Biology Pathophysiological Mechanisms of Neurological and Psychiatric Diseases |
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| 520 | |a The human brain connectome is closely linked to the anatomical framework provided by the structural segregation of the cortex into distinct cortical areas. Therefore, a thorough anatomical reference for the analysis and interpretation of connectome data is indispensable to understand the structure and function of different regions of the cortex, the white matter fibre architecture connecting them, and the interplay between these different entities. This article focuses on parcellation schemes of the cerebral grey matter and their relevance for connectome analyses. In particular, benefits and limitations of using different available atlases and parcellation schemes are reviewed. It is furthermore discussed how atlas information is currently used in connectivity analyses with major focus on seed-based and seed-target analyses, connectivity-based parcellation results, and the robust anatomical interpretation of connectivity data. Particularly this last aspect opens the possibility of integrating connectivity information into given anatomical frameworks, paving the way to multi-modal atlases of the human brain for a thorough understanding of structure-function relationships. | ||
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