Better Living Through Control: With Applications to Neural and Cardiac Systems
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Some brain disorders are hypothesized to have a dynamical origin; in particular, it has been hypothesized that some symptoms of Parkinson's disease are due to pathologically synchronized neural activity in the motor control region of the brain. We have developed a procedure for determining an optimal electrical deep brain stimulus which desynchronizes the activity of a group of neurons by maximizing the Lyapunov exponent associated with their phase dynamics, work that could lead to an improved method for treating Parkinson's disease. The use of related control methods for treating other medical disorders, including cardiac arrhythmias such as alternans, will also be discussed.
Jeff Moehlis received a Ph.D. in Physics from UC Berkeley in 2000, and was a Postdoctoral Researcher in the Program in Applied and Computational Mathematics at Princeton University from 2000-
2003. He joined the Department of Mechanical Engineering at UC Santa Barbara in 2003. He has been a recipient of a Sloan Research Fellowship in Mathematics and a National Science Foundation CAREER
Award, and was Program Director of the SIAM Activity Group in Dynamical Systems from 2008- 2009. Jeff's current research includes applications of dynamical systems and control techniques to
neuroscience, cardiac dynamics, energy harvesting, and collective behavior.