Noah Cowan
Associate Professor of Mechanical Engineering, Johns Hopkins University

Abstract
The nervous system is arguably the most sophisticated control system in the known universe, riding at the helm of an equally sophisticated plant. Understanding how the nervous system encodes and processes sensory information, and then computes motor action, therefore, involves understanding a closed loop. However it is often necessary to “isolate” all or part of the nervous system to study it. But there is no guarantee that the brain is “open-loop stable” and in fact there clear cases when it is likely unstable. Here we discuss two problems in which we first close a feedback loop around the brain, and then take steps to perform system identification of the stabilized brain in order to understand its computations.

Additional Information
Host: Howie Choset
Appointments: Peggy Martin

Speaker Biography
In 2003, Noah Cowan joined Johns Hopkins University, where he is now an associate professor of mechanical engineering. He directs the Locomotion in Mechanical and Biological Systems (LIMBS) Laboratory. LIMBS Lab conducts experiments and computational analyses on both biological and robotic systems, with a focus on applying concepts from dynamical systems and control theory to garner new insights into the principles that underlie neural computation. Dr. Cowan’s research program was recognized by a Presidential Early Career Award in Science and Engineering (PECASE) in 2010 and a James S. McDonnell Complex Systems Scholar award in 2012, and his teaching and mentorship were recognized by the William H. Huggins Excellence in Teaching Award in 2005 and the Dunn Family Award in 2014.