Improving Deep Brain Stimulation in Parkinsons Disease Using Feedback Control

SPEAKER: Sridevi Sarma
Massachusetts Institute of Technology
Harvard Medical School ABSTRACT: An estimated 3 to 4 million people in the United States have Parkinson's Disease (PD), a chronic progressive neural disease that occurs when specific neurons in the midbrain degenerate, causing movement disorders such as tremor, rigidity, and bradykinesia. Currently, there is no cure to stop disease progression. However, surgery and medications are available to relieve some of the symptoms in the short term. A highly promising treatment is deep brain stimulation (DBS). DBS is a surgical procedure in which an electrode is inserted through a small opening in the skull and implanted in a targeted area of the brain. The electrode is connected to a neurostimulator (sits inferior to the collar bone), which injects current back into the brain to regulate the pathological neural activity. Although DBS is virtually a breakthrough for PD, it is necessary to search for the optimal stimulation signal postoperatively. This calibration often takes several weeks or months because the process is trial-and- error. During a post-operative visit, the neurologist asks the patient to perform various motor tasks and makes subjective observations. Based on these, he/she tweaks the stimulation parameters and asks the patient to return in hours, days or even weeks. The difficulty is that there are millions of stimulation parameters to choose from, though experience has reduced this to roughly 1000 options. My current research efforts are to 1. reduce calibration time down to days by developing a systematic testing paradigm using feedback control principles, and to 2. develop a new stimulation paradigm that allows for broader classes of DBS signals to be administered. Despite the fact that DBS is simply a control signal applied to a neural system to achieve desirable motor behavior from a patient, investigators are only beginning to approach these problems from a control systems engineering perspective.BIO: Sridevi V. Sarma received a BS (1994) from Cornell University and an MS (1997) and PhD (2006) from Massachusetts Institute of Technology in Electrical Engineering and Computer Science. Sri is now a postdoctoral fellow jointly at Harvard Medical School and MIT. Her research interests include control of constrained and defective systems (applications in neuroscience) and large-scale optimization. Sri is president and cofounder of Infolenz Corporation, a Marketing Analytics company. She is a recipient of the GE faculty for the future scholarship, a National Science Foundation graduate research fellow, and a recipient of the Burroughs Wellcome Fund Careers at the Scientific Interface Award.HOST: Prof. Urbashi Mitra, ubli@usc.edu

Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248

Audiences: Everyone Is Invited

Contact: Gerrielyn Ramos