4.7 Article

Ventral tegmental area integrity measured with high-resolution 7-Tesla MRI relates to motivation across depression and anxiety diagnoses

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NEUROIMAGE
卷 264, 期 -, 页码 -

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ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2022.119704

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  1. NIMH [K01 MH120433, R01 MH116953]
  2. Friedman Brain Institute [FSV7]
  3. Ehrenkranz Laboratory for Human Resilience

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This study investigates the anatomy of the ventral tegmental area (VTA) using ultra-high field MRI and machine learning techniques. The results show that individuals with depression and anxiety disorders have larger VTA volumes but lower signal intensity, indicating reduced structural integrity of the dopaminergic VTA. Furthermore, VTA integrity is associated with extrinsic motivation cognitive measures.
The ventral tegmental area (VTA) is one of the major sources of dopamine in the brain and has been associated with reward prediction, error-based reward learning, volitional drive and anhedonia. However, precise anatomical investigations of the VTA have been prevented by the use of standard-resolution MRI, reliance on subjective manual tracings, and lack of quantitative measures of dopamine-related signal. Here, we combine ultra-high field 400 mu m3 quantitative MRI with dopamine -related signal mapping, and a mixture of machine learning and supervised computational techniques to delineate the VTA in a transdiagnostic sample of subjects with and without depression and anxiety disorders. Subjects also underwent cognitive testing to measure intrinsic and extrinsic motivational tone. Fifty-one subjects were scanned in total, including healthy control (HC) and mood/anxiety (MA) disorder subjects. MA subjects had significantly larger VTA volumes compared to HC but significantly lower signal intensity within VTA compared to HC, indicating reduced structural integrity of the dopaminergic VTA. Interestingly, while VTA integrity did not significantly correlate with self-reported depression or anxiety symptoms, it was correlated with an objective cognitive measure of extrinsic motivation, whereby lower VTA integrity was associated with lower motivation. This is the first study to demonstrate a computational pipeline for detecting and delineating the VTA in human subjects with 400 m3 resolution. We highlight the use of objective transdiagnostic measures of cognitive function that link neural integrity to behavior across clinical and non-clinical groups.

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