Parcellation of the human amygdala using 7T structural MRI

Solano-Castiella, Eugenia; Lohmann, Gabriele; Schäfer, Andreas; Trampel, Robert; Turner, Robert

doi:10.1016/s1053-8119(09)70447-1

Cited by 1 publication

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“…The identification of inter-nuclear boundaries in individual human high-resolution structural MRI data is notoriously difficult, motivating various strategies including spectral clustering of the diffusion tensor data (Solano-Castiella et al, 2010), bivariate clustering of structural image intensity (Solano-Castiella et al, 2009), manual heuristic segmentation based on the Mai (Mai et al, 2008) brain atlas (Entis et al, 2012; Prévost et al, 2011), parcellation based on cortical signal correlations (Bickart et al, 2012), diffusion tractography-based parcellations (Bach et al, 2011; Saygin et al, 2011), and mapping of histologically defined subregions to an MRI template (the Juelich histological atlas) (Amunts et al, 2005; Eickhoff et al, 2005; Eickhoff et al, 2006). None of these approaches have generated more than four subdivisions of the amygdala, with the majority isolating basolateral, superficial and centromedial groups.…”

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confidence: 99%

In vivo delineation of subdivisions of the human amygdaloid complex in a high‐resolution group template

Tyszka

Pauli

2016

Human Brain Mapping

152

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The nuclei of the human amygdala remain difficult to distinguish in individual subject structural magnetic resonance images. However, interpretation of the amygdala’s role in whole brain networks requires accurate localization of functional activity to a particular nucleus or subgroup of nuclei. To address this, we constructed high spatial resolution, three-dimensional templates, using joint high accuracy diffeomorphic registration of T1- and T2-weighted structural images from 168 typical adults between 22 and 35 years old released by the Human Connectome Project. Several internuclear boundaries are clearly visible in these templates, which would otherwise be impossible to delineate in individual subject data. A probabilistic atlas of major nuclei and nuclear groups was constructed in this template space and mapped back to individual spaces by inversion of the individual diffeomorphisms. Group level analyses revealed a slight (approximately 2%) bias towards larger total amygdala and nuclear volumes in the right hemisphere. No substantial sex or age differences were found in amygdala volumes normalized to total intracranial volume, or subdivision volumes normalized to amygdala volume. The current delineation provides a finer parcellation of the amygdala with more accurate external boundary definition than current histology-based atlases when used in conjunction with high accuracy registration methods, such as diffeomorphic warping. These templates and delineation are intended to be an open and evolving resource for future functional and structural imaging studies of the human amygdala.

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