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Structural Properties of the Caenorhabditis elegans Neuronal Network

Overview of attention for article published in PLoS Computational Biology, February 2011
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Title
Structural Properties of the Caenorhabditis elegans Neuronal Network
Published in
PLoS Computational Biology, February 2011
DOI 10.1371/journal.pcbi.1001066
Pubmed ID
Authors

Lav R. Varshney, Beth L. Chen, Eric Paniagua, David H. Hall, Dmitri B. Chklovskii

Abstract

Despite recent interest in reconstructing neuronal networks, complete wiring diagrams on the level of individual synapses remain scarce and the insights into function they can provide remain unclear. Even for Caenorhabditis elegans, whose neuronal network is relatively small and stereotypical from animal to animal, published wiring diagrams are neither accurate nor complete and self-consistent. Using materials from White et al. and new electron micrographs we assemble whole, self-consistent gap junction and chemical synapse networks of hermaphrodite C. elegans. We propose a method to visualize the wiring diagram, which reflects network signal flow. We calculate statistical and topological properties of the network, such as degree distributions, synaptic multiplicities, and small-world properties, that help in understanding network signal propagation. We identify neurons that may play central roles in information processing, and network motifs that could serve as functional modules of the network. We explore propagation of neuronal activity in response to sensory or artificial stimulation using linear systems theory and find several activity patterns that could serve as substrates of previously described behaviors. Finally, we analyze the interaction between the gap junction and the chemical synapse networks. Since several statistical properties of the C. elegans network, such as multiplicity and motif distributions are similar to those found in mammalian neocortex, they likely point to general principles of neuronal networks. The wiring diagram reported here can help in understanding the mechanistic basis of behavior by generating predictions about future experiments involving genetic perturbations, laser ablations, or monitoring propagation of neuronal activity in response to stimulation.

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Geographical breakdown

Country Count As %
United States 19 2%
Germany 11 1%
United Kingdom 10 1%
Netherlands 3 <1%
Hungary 3 <1%
Canada 3 <1%
Brazil 2 <1%
Japan 2 <1%
China 2 <1%
Other 17 2%
Unknown 740 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 234 29%
Researcher 139 17%
Student > Bachelor 98 12%
Student > Master 82 10%
Student > Doctoral Student 41 5%
Other 102 13%
Unknown 116 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 203 25%
Neuroscience 139 17%
Computer Science 62 8%
Physics and Astronomy 62 8%
Biochemistry, Genetics and Molecular Biology 61 8%
Other 158 19%
Unknown 127 16%