Flow-Based Network Analysis of the Caenorhabditis elegans Connectome

Karol A. Bacik, Michael T. Schaub, Mariano Beguerisse-Díaz, Yazan N. Billeh, Mauricio Barahona

Research output: Contribution to journalArticlepeer-review

21 Citations (SciVal)

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.

Original languageEnglish
Article numbere1005055
JournalPlos Computational Biology
Volume12
Issue number8
DOIs
Publication statusPublished - 5 Aug 2016

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Ecology
  • Modelling and Simulation
  • Molecular Biology
  • Genetics
  • Cellular and Molecular Neuroscience
  • Computational Theory and Mathematics

Fingerprint

Dive into the research topics of 'Flow-Based Network Analysis of the Caenorhabditis elegans Connectome'. Together they form a unique fingerprint.

Cite this