Condensed Matter/Materials & Biological Physics Seminar with Greg Stephens on Theory, Reimagined

Physics offers countless examples for which theoretical predictions are astonishingly powerful. But it’s hard to imagine a similar precision living systems where the number and interdependencies between components simply prohibits a first-principles approach.  We describe a systems-scale perspective in which we integrate information theory, dynamical systems and statistical physics to extract understanding directly from measurements. We demonstrate our approach with a reconstructed state space of the posture dynamics of the nematode C. elegans, revealing a chaotic attractor with symmetric Lyapunov spectrum and a novel perspective of motor control. We then outline a maximally predictive coarse-graining in which nonlinear dynamics are subsumed into a linear, ensemble evolution to obtain a simple yet accurate model on multiple scales. Using this coarse-graining we connect posture to long-lived behavioral states in worm behavior. We suggest that such an ``inverse’’ approach offers an emergent, quantitative framework in which to seek rather than impose effective organizing principles of complex systems.