Modeling, optimization and validation for brain stimulation

of the Thesis Modeling, Optimization and Validation for Brain Stimulation by Kimia Shayestehfard Master of Science in Electrical Engineering Northeastern University, April 2018 Dr. Dana H. Brooks, Dr. Stratis Ioannidis Advisers For the past few years, interest in non-surgical and temporarily implanted brain stimulation methods as tools for clinical studies and research has grown substantially. In electrocorticography (ECoG) stimulation, an array of electrodes is placed on the cortical surface during a surgical procedure, most typically as part of surgical planning for resection of epileptogenic tissue. These ECoG electrodes can be used to both measure intrinsic brain activity and to stimulate superficial cortical regions. Non-invasive electrical stimulation achieved through electrodes placed on the scalp, generally referred to as trancranial Current Stimulation (tCS), is frequently used to stimulate superficial brain areas. This thesis explores some questions related to modeling and optimization of ECoG and tCS stimulation. Both topics depend on computational modeling of the distribution of current in the head induced by the stimulation, typically carried out use the Finite Element Method (FEM). FEM models have been validated for tCS but not for ECoG stimulation. In the first part of this project, as part of a larger collaboration, we analyze ECoG data recorded with arrays of electrodes during stimulation episodes and compare the results of our analysis to FEM simulations as an initial attempt to quantify accuracy of the FEM modeling.