Self-organization of microtubules: complexity analysis of emergent patterns

Microtubules self-organize to structure part of the cellular cytoskeleton. As such they give cells their shape and play a crucial role in cell division and intracellular transport. Past studies have identified diverse spatio-temporal patterns into which microtubules can organize when driven by motor proteins. The question remains if there is an appropriate way to quantify these structures and gain new knowledge about the physical principles of self-organization in microtubule-motor mixtures. Here, we aim to approach this problem from a complexity science perspective. We introduce an entropy-based measure to evaluate the structural complexity of spatial patterns emerging in a simplified agent-based computational model of a microtubule-motor interactions. Our results demonstrate that the proposed quantifier discriminates well between ordered, disordered, and intermediate structures. Besides, our study indicates that the transition to steady states in such a system is likely to be discontinuous and exhibits distinct properties of self-organized criticality.