*********************************
There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
*********************************
PhD Proposal Presentation
Date: January 11, 2019
Time: 9:00 - 11:00 AM
Location:
Emory University Main Campus
Woodruff Memorial Research Building
Room 5101
Committee Members:
Robert E. Gross, Neurosurgery, Biomedical Engineering, Georgia Tech/Emory (Advisor)
Annaelle Devergnas, Neurology, Emory University
Svjetlana Miocinovic, Neurology, Biomedical Engineering, Georgia Tech/Emory
Babak Mahmoudi, Biomedical Informatics, Biomedical Engineering, Georgia Tech/Emory
Chris Rozell, Biomedical Engineering, Georgia Tech/Emory
Title: A framework for optimizing neural modulation based on electrophysiological biomarkers
Abstract: Neural modulation is a fundamental tool for understanding and treating neurological and psychiatric diseases including Parkinson’s and epilepsy. Like most neurological tools, accurately measuring the effect of an intervention is time-consuming and imprecise. However, neural modulation poses an additional problem where stimulation parameters have many degrees of freedom including amplitude, location/contact, frequency, etc. Black-box optimization techniques have the potential to automate the process of tuning stimulation parameters, efficiently search higher dimensional parameter spaces, and identify more effective parameter combinations. The objective of this proposal is to characterize the behavior different optimization algorithms for tuning stimulation parameters, and demonstrate closed-loop optimization in vivo. First, this project establishes a framework for prototyping and designing optimization algorithms in silico based on previously collected data. The platform is developed in the context of modulating of hippocampal gamma (33-50Hz) power through optogenetic stimulation of the medial septum. Next, the optimization system is implemented in vivo in real-time to directly learn the medial septum optogenetic stimulation parameters that maximize hippocampal gamma power in real-time. Finally, the closed-loop optimization framework is extended to characterize functional differences in the septohippocampal circuit in normal and epileptic rats, and for optimizing DBS therapy for patients with Parkinson’s disease.
