Flow-Based Network Analysis of the Caenorhabditis elegans Connectome

PLoS Comput Biol. 2016 Aug 5;12(8):e1005055. doi: 10.1371/journal.pcbi.1005055. eCollection 2016 Aug.

Abstract

We exploit flow propagation on the directed neuronal network of the nematode C. elegans to reveal dynamically relevant features of its connectome. We find flow-based groupings of neurons at different levels of granularity, which we relate to functional and anatomical constituents of its nervous system. A systematic in silico evaluation of the full set of single and double neuron ablations is used to identify deletions that induce the most severe disruptions of the multi-resolution flow structure. Such ablations are linked to functionally relevant neurons, and suggest potential candidates for further in vivo investigation. In addition, we use the directional patterns of incoming and outgoing network flows at all scales to identify flow profiles for the neurons in the connectome, without pre-imposing a priori categories. The four flow roles identified are linked to signal propagation motivated by biological input-response scenarios.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Caenorhabditis elegans / physiology*
  • Computational Biology
  • Connectome*
  • Models, Neurological*
  • Nerve Net / physiology*

Grants and funding

KAB acknowledges an Award from the Imperial College Undergraduate Research Opportunities Programme (UROP). MTS acknowledges support from the ARC and the Belgium network DYSCO (Dynamical Systems, Control and Optimisation). YNB acknowledges support from the G. Harold and Leila Y. Mathers Foundation. MBD acknowledges support from the James S. McDonnell Foundation Postdoctoral Program in Complexity Science/Complex Systems Fellowship Award (220020349-CS/PD Fellow). MB acknowledges support from EPSRC grants EP/I017267/1 and EP/N014529/1. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.