Amal Aaden

Transcranial Magnetic Stimulation (TMS) is an effective intervention for depression and OCD and a promising tool for treating other psychiatric conditions. TMS clinical outcomes are known to differ across patients, with one likely source of variability being individual differences in brain connectivity. Here we propose a methodology to identify personalized targets for stimulation using resting state functional connectivity using functional Magnetic Resonance Imaging (fMRI). We used data from the Midnight Scan Club (MSC, N=10), that includes 5hr of resting state fMRI to delineate functional brain networks for each participant. We identify the target for stimulation using a probabilistic atlas of brain’s functional connectivity derived from >10,000 participants. From this atlas, we localized the brain area with the highest likelihood of being part of the left hand motor cortex and used it as the TMS target for each MSC participant. The coordinate was mapped to native space and using SIMNIBS, we calculated realistic models of tissue conductivity using the Magstim 70mm Figure-of-Eight coil, optimized the location of the coil to maximize the stimulation of the target, simulated the stimulation and finally we calculated how much of the electric field goes to each functional network. We found that the median (interquartile range) distance between the target and the peak of stimulation was 7.6 (4.4-9.9) mm across participants. We also found that most of the electric field was delivered to the motor network, but it also covered the Dorsal Attention, Frontal Parietal and Cingular-Opercular networks. This study shows that using realistic and personalized maps of brain circuitry and tissue conductivity is an effective way to define a workflow for neuromodulation. This proof-of-concept can be refined to optimize the location of the coil maximizing the stimulation of a given functional network while minimizing stimulation of other non-targeted networks.