Network control principles predict neuron function in the Caenorhabditis elegans connectome.

ABSTRACT: Recent studies on the controllability of complex systems offer a powerful mathematical framework to systematically explore the structure-function relationship in biological, social, and technological networks. Despite theoretical advances, we lack direct experimental proof of the validity of these widely used control principles. Here we fill this gap by applying a control framework to the connectome of the nematode Caenorhabditis elegans, allowing us to predict the involvement of each C. elegans neuron in locomotor behaviours. We predict that control of the muscles or motor neurons requires 12 neuronal classes, which include neuronal groups previously implicated in locomotion by laser ablation, as well as one previously uncharacterized neuron, PDB. We validate this prediction experimentall

SUBMITTER: Yan G 

PROVIDER: S-EPMC5710776 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature