Department of Physics and Astronomy
George Mason University
United States Virgin Islands
Paul So is a theoretical physicist specialized in dynamical systems analysis and its application to neuroscience. He received his Bachelor of Science in Physics and Mathematics from Harvey Mudd College in Claremont, California in 1988 and obtained his PhD from the Chaos Group at University of Maryland in College Park, Maryland in 1995. His work on dynamical systems spanned the development of control and observer techniques for high dimensional chaotic systems, theory and experimental work in quantum chaos, analysis of synchronization and coherence in chaotic systems, and the dynamical reconstruction of complex systems using unstable periodic orbits. The overarching goal of his research is the application of these tools from dynamical systems and other physical insights from statistical physics to a better understanding on the mechanisms for information processing in the brain and on dynamical causes related to different pathological neural diseases such as epilepsy and Parkinson’s disease.
Neuroscience, Quantum chaos, Analysis of synchronization, Coherence in chaotic systems.
Networks of Theta Neurons with Time-Varying Excitability: Macroscopic Chaos, Multistability, and Final-State Uncertainty Physica D 267 16-26 (2014). Paul So, Tanushree B. Luke, and Ernest Barreto
Control of Collective Network Chaos Chaos 24 023127 (2014). Alexandre Wagemakers, Ernest Barreto, Miguel A. F. Sanjuan, and Paul So
Macroscopic Complexity from an Autonomous Network of Networs of Theta Neurons Froniter in Computational Neuroscience 8:145 DOI: 10.3389/fncom.2014.00145 (2014).