Network control principles predict neuron function in the Caenorhabditis elegans connectome

• Published in: Nature (London) Vol. 550; no. 7677; pp. 519 - 523
• Main Authors: Yan, Gang, Vértes, Petra E., Towlson, Emma K., Chew, Yee Lian, Walker, Denise S., Schafer, William R., Barabási, Albert-László
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 26.10.2017; Nature Publishing Group
• Subjects: 631/378; 639/766/25; 64; 64/11; Ablation; Animal behavior; Animals; Bends; Caenorhabditis elegans; Caenorhabditis elegans - cytology; Caenorhabditis elegans - physiology; Complex systems; Connectome; Control theory; Controllability; Humanities and Social Sciences; Lasers; letter; Locomotion; Locomotion - physiology; Motor neurons; Motor Neurons - cytology; Motor Neurons - physiology; multidisciplinary; Muscles; Nematodes; Nerve Net - cytology; Nerve Net - physiology; Nervous system; Network control; Neurons; Neurons - classification; Neurons - physiology; Physiological aspects; Polarity; Robustness (mathematics); Science; Stability; Structure-function relationships
• ISSN: 0028-0836; 1476-4687
• DOI: 10.1038/nature24056

Application of network control theory to the neuronal connectome of Caenorhabditis elegans , allowing prediction of the involvement of individual neurons in locomotion. Theory of elegans Control theory is widely used to explore how complex biological, social or technological networks can achieve desired outcomes from specific inputs, but experimental proof of its core principles is still scarce. Now, Albert-László Barabási and colleagues apply network control theory to the neuronal connectome of the roundworm Caenorhabditis elegans to predict the involvement of individual neurons in locomotion. They successfully predict all neuronal groups previously identified as well as one new class, and reveal counterintuitive roles for individual neurons in known classes, which they validate through laser ablation and behaviour tracking experiments. The results are also robust to small perturbations of the reference connectome and suggest that the same analytical framework may be applied to larger and less-well-characterized nervous systems. 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 1 , 2 , 3 . 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 4 , 5 , 6 , 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 7 , 8 , 9 , 10 , 11 , 12 , 13 , as well as one previously uncharacterized neuron, PDB. We validate this prediction experimentally, finding that the ablation of PDB leads to a significant loss of dorsoventral polarity in large body bends. Importantly, control principles also allow us to investigate the involvement of individual neurons within each neuronal class. For example, we predict that, within the class of DD motor neurons, only three (DD04, DD05, or DD06) should affect locomotion when ablated individually. This prediction is also confirmed; single cell ablations of DD04 or DD05 specifically affect posterior body movements, whereas ablations of DD02 or DD03 do not. Our predictions are robust to deletions of weak connections, missing connections, and rewired connections in the current connectome, indicating the potential applicability of this analytical framework to larger and less well-characterized connectomes.