Modelling and Analysis of Brain Network Dynamics via Systems and Control Theory

Understanding the relationship between cognition and the complex network dynamics of the brain constitutes one of the most challenging and impactful problems ahead of science and engineering. In this seminar, I will present recent work on the analysis of selective attention as one of the most fundamental processes in the brain that enable cognition. I will begin by reviewing some of the main experimental observations in neuroscience and showing how we can translate them into control-theoretic network properties. I will then rigorously relate these properties to network structure for a class of switched-affine models, offering a mathematical foundation for selective attention. I will present a comprehensive case study to illustrate and test this framework and will end by giving new predictions based on it for brain organization.
Erfan Nozari received his B.Sc. in Electrical Engineering-Control in 2013 from Isfahan University of Technology, Isfahan, Iran and M.Sc. in Mechanical Engineering in 2015 from University of California, San Diego, where he is currently an interdisciplinary Ph.D. candidate in Mechanical Engineering and Cognitive Science. He has been the recipient of the Best Student Paper Awards from the 57th IEEE Conference on Decision and Control and the 2018 American Control Conference and the MAE Distinguished Fellowship Award from the University of California, San Diego. His research interests include dynamical systems and control theory and its applications in computational and theoretical neuroscience and complex network systems.