Surfacing Robust Function in Living Matter through Topology and Geometry
I study how robust functions such as global cycles and learning emerge in complex biological systems and will describe some recent progress in my ongoing projects. Living systems can exhibit time-scales much longer than those of the underlying components, as well as collective dynamical behavior. How such global behavior is subserved by stochastic constituents remains unclear. We present biologically plausible motifs from which two-dimensional stochastic networks can be constructed, that support macroscopic edge currents in configuration space. Our framework enables a wealth of dynamical phenomena such as a global clock, dynamical growth, and de-growth, as well as synchronization, similar to observations that are quite prevalent in biology. If time permits, I will also discuss how effective learning is accompanied by high dimensional representations of neural activity.
Evelyn Tang is a group leader in the Living Matter Physics department at the Max Planck Institute for Dynamics and Self-Organization. As a theoretical physicist engaged in the study of living matter, her goal is to understand why biological function remains so robust despite stochasticity and fluctuations on the microscopic scale. This research draws on her training in many-body physics, statistical mechanics, and novel phases of matter. Current interests include the study of global cycles and synchronization, optimal learning, and information in fluid flows.