Brain stimulation techniques, such as transcranial magnetic stimulation (TMS), provide a new paradigm for treating brain disorders that cannot be effectively treated by traditional pharmacotherapies.

The goal of this research project is to develop a software that uses deep neural networks for real-time prediction and visualization of the electric field evoked by TMS. The deep neural network will be used to search for the optimal coil position that maximizes the stimulation of a selected brain target. Dr. Haehn and his student Loraine Franke will contribute to the data prediction and data visualization aspects of this grant.

Project Team:

PI Dr. Lipeng Ning (Brigham and Women’s Hospital, Harvard Medical School)

Dr. Yogesh Rathi (Brigham and Women’s Hospital, Harvard Medical School)

Dr. Joan Camprodon (Massachusetts General Hospital)

Dr. Steve Pieper (Isomics, Inc.)

Dr. Daniel Haehn (UMass Boston)

Loraine Franke (UMass Boston)