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Open Access 01-05-2021 | Magnetic Resonance Imaging | Original Article

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

Authors: Anne C. Trutti, Laura Fontanesi, Martijn J. Mulder, Pierre-Louis Bazin, Bernhard Hommel, Birte U. Forstmann

Published in: Brain Structure and Function | Issue 4/2021

Abstract

Functional 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.

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Title: A probabilistic atlas of the human ventral tegmental area (VTA) based on 7 Tesla MRI data
Authors: Anne C. Trutti
Laura Fontanesi
Martijn J. Mulder
Pierre-Louis Bazin
Bernhard Hommel
Birte U. Forstmann
Publication date: 01-05-2021
Publisher: Springer Berlin Heidelberg
Keywords: Magnetic Resonance Imaging
Magnetic Resonance Imaging
Published in: Brain Structure and Function / Issue 4/2021
Print ISSN: 1863-2653
Electronic ISSN: 1863-2661
DOI: https://doi.org/10.1007/s00429-021-02231-w

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

Abstract

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