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

• Published in: Brain Structure and Function Vol. 226; no. 4; pp. 1155 - 1167
• Main Authors: Trutti, Anne C., Fontanesi, Laura, Mulder, Martijn J., Bazin, Pierre-Louis, Hommel, Bernhard, Forstmann, Birte U.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.05.2021; Springer Nature B.V
• Subjects: Anatomy; Biomedical and Life Sciences; Biomedicine; Brain architecture; Brain mapping; Cell Biology; Cognitive ability; Functional magnetic resonance imaging; Image processing; Magnetic resonance imaging; Nervous system; Neuroimaging; Neurology; Neurosciences; Original; Original Article; Reinforcement; Ventral tegmentum; Probabilistic atlas; Midbrain; 7 T MRI; VTA; Subcortex
• ISSN: 1863-2653; 1863-2661; 1863-2661; 0340-2061
• DOI: 10.1007/s00429-021-02231-w

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.