Transcranial magnetic stimulation (TMS) has shown promise as a treatment option in mental disorders. However, treatment outcomes across patients are still variable, which calls for optimization of treatment protocols. This variability likely arises from adopting one-size-fits-all application of TMS to target the dorsolateral prefrontal cortex (DLPFC), a key brain region involved in depression. Furthermore, individual brain anatomy contributes to this variability.

PhD student Nipun Perera (Biomedical Engineering), in a project called “Optimizing TMS coil placement for targeting dorsolateral prefrontal cortex,” is developing a novel computational method leveraging patient specific electric field simulations and EEG evoked potentials, to optimally target DLPFC subnetworks. To test the new method, the research team will perform a validation experiment in human participants. If successful, this research will lead to more precise targeting of DLPFC and eventually improved clinical outcomes.

Some funding for this project was provided by a 2023 Research Computing-MnDRIVE PhD Graduate Assistantship (formerly the UMII PhD Graduate Assistantships). The RC-MnDRIVE Graduate Assistantship program supports U of M PhD candidates pursuing research at the intersection of informatics and any of the five MnDRIVE areas:

  • Robotics
  • Global Food
  • Environment
  • Conditions
  • Cancer Clinical Trials

This project is part of the Brain Conditions MnDRIVE area. See the complete list of the RC-MnDRIVE Graduate Assistantships for 2023.

Graphical Abstract of project