Caenorhabditis elegans and the network control framework—FAQs

Emma K. Towlson, Petra E. Vértes, Gang Yan, Yee Lian Chew, Denise S. Walker, William R. Schafer, Albert-László Barabási
Phil. Trans. R. Soc. B
373: 20170372.
September 10, 2018

Abstract

Control is  essential to the functioning of any neural system. Indeed, under healthy  conditions the brain must be able to continuously maintain a tight functional  control between the system's inputs and outputs. One may therefore  hypothesize that the brain's wiring is predetermined by the need to maintain  control across multiple scales, maintaining the stability of key internal  variables, and producing behaviour in response to environmental cues. Recent  advances in network control have offered a powerful mathematical framework to  explore the structure-function relationship in complex biological, social and  technological networks, and are beginning to yield important and precise  insights on neuronal systems. The network control paradigm promises a predictive,  quantitative framework to unite the distinct datasets necessary to fully  describe a nervous system, and provide mechanistic explanations for the  observed structure and function relationships. Here, we provide a thorough  review of the network control framework as applied to Caenorhabditis elegans  (Yan et al. 2017 Nature550, 519-523. (doi:10.1038/nature24056)), in the style  of Frequently Asked Questions. We present the theoretical, computational and  experimental aspects of network control, and discuss its current capabilities  and limitations, together with the next likely advances and improvements. We  further present the Python code to enable exploration of control principles  in a manner specific to this prototypical organism.This article is part of a  discussion meeting issue 'Connectome to behaviour: modelling C. elegans at  cellular resolution'.