Chalmers Conferences, 9th European Conference on Mathematical and Theoretical Biology

Mechanistic models of multicellular computation
David Swab

Last modified: 2014-06-09

Abstract


Populations of cells exhibit a remarkable diversity of behaviors, from the
reliable development of multicellular structures to complex coding in
neural ensembles. Proper characterization of these phenomena requires an
understanding of how dynamics at the single-cell level, when combined with
intercellular signaling and environmental cues, give rise to the collective
behaviors observed in populations. First, I will present results
characterizing the universal signaling dynamics in individual cells of
social amoebae, and discuss cell density-dependent transitions to
collective, synchronized oscillations. I will then consider population
coding in retinal ganglion cells. Recent experiments have shown that the
distribution of spiking activity in these cells is poised near a unique
critical point where the extensive parts of the entropy and energy are
exactly equal. I will demonstrate how such behavior robustly arises due to
shared stimulus input. Connections to the statistical mechanics of learning
will also be discussed.