Real-time Biofeedback With 7-Tesla MRI for Treatment of Depression

Previous research has shown that modulation of a brain region in rodents, the ventral tegmental area (VTA), improves depressive symptoms. Human research has also shown that VTA self-modulation using 'biofeedback' is feasible and successful in healthy volunteers. This biofeedback procedure is a type of cognitive training that includes real-time feedback about brain signal levels from the VTA. Our question is whether VTA self-modulation with biofeedback can influence depression symptoms.

Major depressive disorder (MDD) is the world's largest health problem, and current available treatments fail at relieving symptoms for many patients. The best medical approach will depend on taking an individualized approach to treatment, targeting core symptoms such as reduced self-driven motivation. In rodent studies of depression, problems with motivation have been linked to the activity of the ventral tegmental area (VTA), a small part of the brain that releases dopamine and guides decision making for rewards. However, there have been barriers in examining the VTA in humans because current MRI scanners are relatively low-resolution. Therefore, the researchers have recently developed an ultra-high field MRI procedure that provides improved images of the VTA, compared to current standard MRI procedures. The study team now intend to further this work by conducting a randomized controlled trial that will help train individuals with MDD to modulate their own VTA activity during an ultra-high field MRI scanning session. Previous studies have shown that the activity of the VTA can be changed in healthy volunteers if they are trained to use certain thought patterns while watching their own VTA activity in 'real-time'. This procedure is called real-time biofeedback The research question is whether this same type of training is feasible in patients with MDD with ultra-high field MRI, and whether it can influence measures of motivation. Aim 1. To determine the feasibility of VTA self-regulation. The study team will recruit 30 patients with MDD and 15 will receive VTA real-time biofeedback whereas the other 15 will receive a different, control feedback. Participants will be trained to "generate a heightened state of motivation" and will simultaneously view a progress bar on the screen that represents their VTA activity. They will be trained to try to increase the level of the bar by motivating themselves. The investigators expect that the group receiving VTA real-time biofeedback will show a greater increase in VTA activity self-regulation compared to the group with non-VTA, control feedback. Aim 2. To determine the impact of VTA self-regulation on motivation. The research team will test levels of motivation using novel, validated computerized tasks before and after the real-time biofeedback training session. The researchers will also explore a measure of mood using a validated questionnaire, and as well as assess levels of clinical depression severity by a trained clinician. The investigators expect that individuals who show a greater increase in VTA activity self-regulation will also show an increase in motivation after training. If this real-time biofeedback tool is shown to be possible for changing VTA activity in patients with MDD, this work will provide a critical next step in individualized treatment for depression. By exploring how changes in VTA activity self-regulation relate to changes in motivation, the researchers will show how the brain works to regulate important behaviors associated with depression. Ultimately, this work is expected to provide new ways to treat patients with depression.