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  Parcellation of human amygdala in vivo using ultra high field structural MRI

Solano-Castiella, E., Schäfer, A., Reimer, E., Türke, E., Pröger, T., Lohmann, G., et al. (2011). Parcellation of human amygdala in vivo using ultra high field structural MRI. NeuroImage, 58(3), 741-748. doi:10.1016/j.neuroimage.2011.06.047.

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 Creators:
Solano-Castiella, Eugenia1, Author           
Schäfer, Andreas1, Author           
Reimer, Enrico1, Author           
Türke, Erik1, Author           
Pröger, Thomas1, Author
Lohmann, Gabriele1, Author           
Trampel, Robert1, Author           
Turner, Robert1, Author           
Affiliations:
1Department Neurophysics, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634550              

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Free keywords: 7 T; Gray matter; Amygdala; Segmentation; T2-weighted; T2*-weighted
 Abstract: Histological studies show that human amygdala is subdivided into several nuclei with specific connections to other brain areas. One such study has been recently used as the basis of a probabilistic amygdala map, to enable in vivo identification of specifically located functions within the amygdala and connections to it. The involvement of the amygdala in cognition, emotion and action, which may underlie several psychiatric disorders, points to a need for discrimination of these nuclei in living human brains using different techniques. Structural MRI scans of the human amygdala at standard field strengths (≤ 3 T) have shown a region of generally featureless gray matter. Apparently homogeneous regions may reveal internal structure, however, when improved imaging strategies and better SNR are available. The goal of this study is the in vivo anatomical segmentation of the amygdala using high resolution structural MR data. The use of different MRI tissue contrast mechanisms at high field strengths has been little explored so far. Combining two different contrasts, and using cutting-edge image analysis, the following study provides a robust clustering of three amygdala components in vivo using 7 T structural imaging.

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Language(s): eng - English
 Dates: 2011-06-012011-03-022011-06-162011-06-252011-10-01
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1016/j.neuroimage.2011.06.047
 Degree: -

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Title: NeuroImage
Source Genre: Journal
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Publ. Info: Orlando, FL : Academic Press
Pages: - Volume / Issue: 58 (3) Sequence Number: - Start / End Page: 741 - 748 Identifier: ISSN: 1053-8119
CoNE: https://pure.mpg.de/cone/journals/resource/954922650166