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Open AccessArticle

Complexity and Vulnerability Analysis of the C. Elegans Gap Junction Connectome

Pacific Northwest Diabetes Research Institute, Seattle, WA 98122, USA
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Academic Editor: Mikhail Prokopenko
Entropy 2017, 19(3), 104; https://doi.org/10.3390/e19030104
Received: 30 December 2016 / Revised: 24 February 2017 / Accepted: 3 March 2017 / Published: 8 March 2017
(This article belongs to the Special Issue Complexity, Criticality and Computation (C³))
We apply a network complexity measure to the gap junction network of the somatic nervous system of C. elegans and find that it possesses a much higher complexity than we might expect from its degree distribution alone. This “excess” complexity is seen to be caused by a relatively small set of connections involving command interneurons. We describe a method which progressively deletes these “complexity-causing” connections, and find that when these are eliminated, the network becomes significantly less complex than a random network. Furthermore, this result implicates the previously-identified set of neurons from the synaptic network’s “rich club” as the structural components encoding the network’s excess complexity. This study and our method thus support a view of the gap junction Connectome as consisting of a rather low-complexity network component whose symmetry is broken by the unique connectivities of singularly important rich club neurons, sharply increasing the complexity of the network. View Full-Text
Keywords: complexity; computational neuroscience; C. elegans; neural connectome; rich club; vulnerability complexity; computational neuroscience; C. elegans; neural connectome; rich club; vulnerability
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Kunert-Graf, J.M.; Sakhanenko, N.A.; Galas, D.J. Complexity and Vulnerability Analysis of the C. Elegans Gap Junction Connectome. Entropy 2017, 19, 104.

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