Feasibility of Integrating Real-Time fMRI Neurofeedback with rTMS: Study Design, Preliminary Results, and Technical...

Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive brain stimulation technique used in the treatment of several psychiatric disorders. However, its clinical efficacy remains limited in some cases, in part due to the lack of control over ongoing brain state during stimulation. Although some studies have combined rTMS with psychotherapy to engage the brain state during stimulation, brain state is still not objectively measured in such studies. Real-time functional magnetic resonance imaging neurofeedback (rt-fMRI-nf) offers a promising approach to objectively monitor and modulate brain state during rTMS. Here, we report the first study to investigate the feasibility of combining connectivity-based rTMS with rt-fMRI-nf to modulate amygdala activity. First, participants completed an fMRI emotion-matching task to identify an individualized medial prefrontal cortex (mPFC) target showing the strongest negative functional connectivity with the right amygdala. Across four subsequent visits, participants received active rTMS to either a mPFC target or to the vertex (control site) while engaged in rt-fMRI-nf. During rt-fMRI-nf, participants were presented with aversive images and were instructed either to passively look at them or to downregulate the height of a visual gauge representing their amygdala activity. We expected that rTMS during this downregulation would decrease amygdala activation even more than during downregulation alone. Feasibility, signal quality, rTMS-induced artifacts, and participant experience were systematically evaluated. We demonstrate that while concurrent connectivity-based rTMS and rt-fMRI-nf is feasible, the integration presents substantial technical and methodological challenges. These include limitations related to RF coil selection, signal-to-noise ratio in deep brain structures, prolonged rTMS-induced artifacts, and inter-individual variability in amygdala engagement. Despite these challenges, this work establishes a methodological foundation for future studies integrating real-time neuroimaging and neuromodulation. Continued advances in hardware, acquisition strategies, and individualized targeting may enable more precise state-dependent stimulation of emotion-related circuits, with potential implications for precision interventions in psychiatric disorders.