Paving the way for precision treatment of psychiatric symptoms with functional connectivity neurofeedback

Treatment for Major Depressive Disorder (MDD) remains relatively homogeneous, despite patients having heterogeneous subsets of symptoms with differing underlying neural aberrations. Demonstrating potential for a more individualised treatment approach, we recently showed that normalisation of a neural network and a corresponding reduction in related symptoms can be achieved using real-time fMRI functional connectivity neurofeedback (FCNef). Specifically, we showed that brooding rumination but not anxiety symptoms decreased as functional connectivity between the dorsolateral prefrontal cortex (DLPFC) and posterior cingulate cortex/precuneus (PCC) normalised with FCNef. However, the robustness of this effect, how localised it is in the brain, and the best parameters for optimising therapeutic outcomes remained unknown. We therefore ran additional participants (final N = 68) in our FCNef protocol. We replicated our original findings and ran new analyses that better highlighted the precision of this effect to rumination symptoms. For the first time we also demonstrated that connectivity between the Executive Control and Default-Mode networks reduced significantly with FCNef. Finally, we manipulated core FCNef parameters between participants and found that the most effective protocol involved consecutive training days with greater external reward. These results highlight the potential of FCNef for precision medicine in psychiatry and underscore the importance of optimising parameters to enhance feasibility of BMI-based clinical interventions.