scholarly journals A probabilistic atlas of the human ventral tegmental area (VTA) based on 7 Tesla MRI data

2021 ◽  
Vol 226 (4) ◽  
pp. 1155-1167 ◽  
Author(s):  
Anne C. Trutti ◽  
Laura Fontanesi ◽  
Martijn J. Mulder ◽  
Pierre-Louis Bazin ◽  
Bernhard Hommel ◽  
...  
Keyword(s):  
Ventral Tegmental Area ◽  
Region Of Interest ◽  
Reward Processing ◽  
7 Tesla ◽  
Subcortical Structures ◽  
7 Tesla Mri ◽  
Subcortical Nuclei ◽  
Ventral Tegmental ◽  
The Brain

AbstractFunctional magnetic resonance imaging (fMRI) BOLD signal is commonly localized by using neuroanatomical atlases, which can also serve for region of interest analyses. Yet, the available MRI atlases have serious limitations when it comes to imaging subcortical structures: only 7% of the 455 subcortical nuclei are captured by current atlases. This highlights the general difficulty in mapping smaller nuclei deep in the brain, which can be addressed using ultra-high field 7 Tesla (T) MRI. The ventral tegmental area (VTA) is a subcortical structure that plays a pivotal role in reward processing, learning and memory. Despite the significant interest in this nucleus in cognitive neuroscience, there are currently no available, anatomically precise VTA atlases derived from 7 T MRI data that cover the full region of the VTA. Here, we first provide a protocol for multimodal VTA imaging and delineation. We then provide a data description of a probabilistic VTA atlas based on in vivo 7 T MRI data.

scholarly journals Multi-contrast anatomical subcortical structures parcellation

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Pierre-Louis Bazin ◽  
Anneke Alkemade ◽  
Martijn J Mulder ◽  
Amanda G Henry ◽  
Birte U Forstmann
Keyword(s):  
Open Source ◽  
Quantitative Mri ◽  
7 Tesla ◽  
Subcortical Structures ◽  
Structural Neuroimaging ◽  
Terra Incognita ◽  
Close Proximity ◽  
Subcortical Nuclei ◽  
The Brain

The human subcortex is comprised of more than 450 individual nuclei which lie deep in the brain. Due to their small size and close proximity, up until now only 7% have been depicted in standard MRI atlases. Thus, the human subcortex can largely be considered as terra incognita. Here, we present a new open-source parcellation algorithm to automatically map the subcortex. The new algorithm has been tested on 17 prominent subcortical structures based on a large quantitative MRI dataset at 7 Tesla. It has been carefully validated against expert human raters and previous methods, and can easily be extended to other subcortical structures and applied to any quantitative MRI dataset. In sum, we hope this novel parcellation algorithm will facilitate functional and structural neuroimaging research into small subcortical nuclei and help to chart terra incognita.

scholarly journals Multi-contrast Anatomical Subcortical Structures Parcellation

2020 ◽  
Author(s):  
Pierre-Louis Bazin ◽  
Anneke Alkemade ◽  
Martijn Mulder ◽  
Amanda G Henry ◽  
Birte Forstmann
Keyword(s):  
Open Source ◽  
Quantitative Mri ◽  
7 Tesla ◽  
Subcortical Structures ◽  
Structural Neuroimaging ◽  
Terra Incognita ◽  
Close Proximity ◽  
Subcortical Nuclei ◽  
The Brain

The human subcortex is comprised of more than 450 individual nuclei which lie deep in the brain. Due to their small size and close proximity, up until now only 7% have been depicted in standard MRI atlases. Thus, the human subcortex can largely be considered as terra incognita. Here we present a new open source parcellation algorithm to automatically map the subcortex . The new algorithm has been tested on 17 prominent subcortical structures based on a large quantitative MRI dataset at 7 Tesla. It has been carefully validated against expert human raters and previous methods, and can easily be extended to other subcortical structures and applied to any quantitative MRI dataset. In sum, we hope this novel parcellation algorithm will facilitate functional and structural neuroimaging research into small subcortical nuclei and help to chart terra incognita.

scholarly journals Insulin in the ventral tegmental area reduces cocaine‐evoked dopamine in the nucleus accumbens in vivo

2018 ◽  
Vol 50 (3) ◽  
pp. 2146-2155 ◽  
Author(s):  
Lindsay Naef ◽  
Lauren Seabrook ◽  
Jeff Hsiao ◽  
Calvin Li ◽  
Stephanie L. Borgland
Keyword(s):  
Nucleus Accumbens ◽  
Ventral Tegmental Area ◽  
Ventral Tegmental

scholarly journals Quantifying the contrast of the human locus coeruleus in vivo at 7 Tesla MRI

PLoS ONE ◽  
2019 ◽  
Vol 14 (2) ◽  
pp. e0209842 ◽  
Author(s):  
Klodiana-Daphne Tona ◽  
Matthias J. P. van Osch ◽  
Sander Nieuwenhuis ◽  
Max C. Keuken
Keyword(s):  
Locus Coeruleus ◽  
7 Tesla ◽  
7 Tesla Mri

scholarly journals In Vivo High-Resolution 7 Tesla MRI Shows Early and Diffuse Cortical Alterations in CADASIL

PLoS ONE ◽  
2014 ◽  
Vol 9 (8) ◽  
pp. e106311 ◽  
Author(s):  
François De Guio ◽  
Sonia Reyes ◽  
Alexandre Vignaud ◽  
Marco Duering ◽  
Stefan Ropele ◽  
...  
Keyword(s):  
High Resolution ◽  
7 Tesla ◽  
7 Tesla Mri

scholarly journals In-vivo and numerical analysis of the eigenmodes produced by a multi-level Tic-Tac-Toe head transmit array for 7 Tesla MRI

PLoS ONE ◽  
2018 ◽  
Vol 13 (11) ◽  
pp. e0206127 ◽  
Author(s):  
Tales Santini ◽  
Yujuan Zhao ◽  
Sossena Wood ◽  
Narayanan Krishnamurthy ◽  
Junghwan Kim ◽  
...  
Keyword(s):  
Numerical Analysis ◽  
7 Tesla ◽  
7 Tesla Mri ◽  
Multi Level
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