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  Diffusion tensor imaging segments the human amygdala in vivo

Solano-Castiella, E., Anwander, A., Lohmann, G., Weiss, M., Docherty, C., Geyer, S., et al. (2010). Diffusion tensor imaging segments the human amygdala in vivo. NeuroImage, 49(4), 2958-2965. doi:10.1016/j.neuroimage.2009.11.027.

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Solano-Castiella, E, Author
Anwander, A, Author
Lohmann, G1, Author           
Weiss, M, Author
Docherty, C, Author
Geyer, S, Author
Reimer, E, Author
Friederici, AD, Author
Turner, R, Author
Affiliations:
1Max Planck Institute for Human Cognitive and Brain Sciences, ou_persistent22              

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 Abstract: The amygdala plays an important role in emotion, learning, and memory. It would be highly advantageous to understand more precisely its internal structure and connectivity for individual human subjects in vivo. Earlier cytoarchitectural research in post-mortem human and animal brains has revealed multiple subdivisions and connectivity patterns, probably related to different functions. With standard magnetic resonance imaging (MRI) techniques, however, the amygdala appears as an undifferentiated area of grey matter. Using high-quality diffusion tensor imaging (DTI) at 3 Tesla, we show diffusion anisotropy in this grey matter area. Such data allowed us to subdivide the amygdala for the first time in vivo. In 15 living subjects, we applied a spectral clustering algorithm to the principal diffusion direction in each amygdala voxel and found a consistent subdivision of the amygdala into a medial and a lateral region. The topography of these regions is in good agreement with the fibre architecture visible in myelin-stained sections through the amygdala of a human post-mortem brain. From these in vivo results we derived a probabilistic map of amygdalar fibre orientations. This segmentation technique has important implications for functional studies in the processing of emotions, cognitive function, and psychiatric disorders and in studying morphometry and volumetry of amygdala subdivisions.

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 Dates: 2010
 Publication Status: Issued
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 Identifiers: DOI: 10.1016/j.neuroimage.2009.11.027
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Title: NeuroImage
Source Genre: Journal
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Publ. Info: Orlando, FL : Academic Press
Pages: - Volume / Issue: 49 (4) Sequence Number: - Start / End Page: 2958 - 2965 Identifier: ISSN: 1053-8119
CoNE: https://pure.mpg.de/cone/journals/resource/954922650166