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

Major depressive disorder (MDD) is one of the world's largest health problems with current treatments that are ineffective for a substantial proportion of individuals. There is a critical need for mechanistically informed interventions that are individualized and that aim to target core symptoms. Converging evidence from animal and human research in the field has implicated the ventral tegmental area (VTA), a key component of the brain's dopamine system, in regulating motivation and reward-related behaviour. Previous work has demonstrated that participants can successfully train to self-regulate their VTA activity using cognitive strategies while receiving real-time feedback. This shows that VTA self-regulation is feasible in humans. The current study builds on this previous work to further investigate the relationships between VTA activity modulation and mood and motivation related changes in individuals with MDD. Specifically, this study will aim to extend on prior findings by increasing the sample size and incorporating repeated training sessions to enhance and characterize training effects over time. A total of 60 participants with MDD will be recruited and will be randomized in a 1:1 ratio to receive either active biofeedback or sham (control) feedback. Participants will complete two training sessions with real-time 7T-MRI biofeedback. During functional MRI (fMRI) scanning, participants will be trained to use self-generated cognitive strategies to modulate their VTA activity while viewing a visual representation of their brain signal (active condition) or a yoked control signal (sham condition). The primary objective of this study is to determine how VTA modulation influences mood and motivation related measures over time. Secondary objectives include assessing changes in VTA activation and functional connectivity over time, as well as examining how neural changes relate to mood and motivation-related changes.