Literature DB >> 21726652

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

Eugenia Solano-Castiella1, Andreas Schäfer, Enrico Reimer, Erik Türke, Thomas Pröger, Gabriele Lohmann, Robert Trampel, Robert Turner.   

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.
Copyright © 2011 Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 21726652     DOI: 10.1016/j.neuroimage.2011.06.047

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  29 in total

Review 1.  Connectivity-based parcellation: Critique and implications.

Authors:  Simon B Eickhoff; Bertrand Thirion; Gaël Varoquaux; Danilo Bzdok
Journal:  Hum Brain Mapp       Date:  2015-09-27       Impact factor: 5.038

2.  Multimodal evaluation of the amygdala's functional connectivity.

Authors:  Rebecca Kerestes; Henry W Chase; Mary L Phillips; Cecile D Ladouceur; Simon B Eickhoff
Journal:  Neuroimage       Date:  2017-01-09       Impact factor: 6.556

Review 3.  The future of ultra-high field MRI and fMRI for study of the human brain.

Authors:  Jeff H Duyn
Journal:  Neuroimage       Date:  2011-10-28       Impact factor: 6.556

4.  Functional connectivity-based parcellation of amygdala using self-organized mapping: a data driven approach.

Authors:  Arabinda Mishra; Baxter P Rogers; Li Min Chen; John C Gore
Journal:  Hum Brain Mapp       Date:  2013-02-18       Impact factor: 5.038

5.  Eliminating susceptibility induced hyperintensities in T1w MPRAGE brain images at 7 T.

Authors:  Ruoyun Ma; Thomas R Henry; Pierre-François Van de Moortele
Journal:  Magn Reson Imaging       Date:  2019-08-22       Impact factor: 2.546

Review 6.  Brain-heart interactions: challenges and opportunities with functional magnetic resonance imaging at ultra-high field.

Authors:  Catie Chang; Erika P Raven; Jeff H Duyn
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2016-05-13       Impact factor: 4.226

7.  A reliable protocol for the manual segmentation of the human amygdala and its subregions using ultra-high resolution MRI.

Authors:  Jonathan J Entis; Priya Doerga; Lisa Feldman Barrett; Bradford C Dickerson
Journal:  Neuroimage       Date:  2012-01-05       Impact factor: 6.556

8.  High-resolution magnetic resonance imaging reveals nuclei of the human amygdala: manual segmentation to automatic atlas.

Authors:  Z M Saygin; D Kliemann; J E Iglesias; A J W van der Kouwe; E Boyd; M Reuter; A Stevens; K Van Leemput; A McKee; M P Frosch; B Fischl; J C Augustinack
Journal:  Neuroimage       Date:  2017-05-04       Impact factor: 6.556

9.  The human amygdala and pain: evidence from neuroimaging.

Authors:  Laura E Simons; Eric A Moulton; Clas Linnman; Elizabeth Carpino; Lino Becerra; David Borsook
Journal:  Hum Brain Mapp       Date:  2012-10-25       Impact factor: 5.038

10.  Regionally specific increased volume of the amygdala in Williams syndrome: evidence from surface-based modeling.

Authors:  Brian W Haas; Kristen Sheau; Ryan G Kelley; Paul M Thompson; Allan L Reiss
Journal:  Hum Brain Mapp       Date:  2012-11-14       Impact factor: 5.038

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