Abstract
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 µm(3) 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 μm(3) resolution. We highlight the use of objective transdiagnostic measures of cognitive function that link neural integrity to behavior across clinical and non-clinical groups.