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Sardi S, Goldental A, Amir H, et al. Vitality of Neural Networks under Reoccurring Catastrophic Failures. Sci Rep. 2016;6:31674doi: 10.1038/srep31674.
Sardi, S., Goldental, A., Amir, H., Vardi, R., & Kanter, I. (2016). Vitality of Neural Networks under Reoccurring Catastrophic Failures. Scientific reports, 631674. https://doi.org/10.1038/srep31674
Sardi, Shira, et al. "Vitality of Neural Networks under Reoccurring Catastrophic Failures." Scientific reports vol. 6 (2016): 31674. doi: https://doi.org/10.1038/srep31674
Sardi S, Goldental A, Amir H, Vardi R, Kanter I. Vitality of Neural Networks under Reoccurring Catastrophic Failures. Sci Rep. 2016 Aug 17;6:31674. doi: 10.1038/srep31674. PMID: 27530974; PMCID: PMC4987694.
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Sci Rep. 2016 Aug 17;6:31674. doi: 10.1038/srep31674.

Vitality of Neural Networks under Reoccurring Catastrophic Failures.

Scientific reports

Shira Sardi, Amir Goldental, Hamutal Amir, Roni Vardi, Ido Kanter

Affiliations

  1. Department of Physics, Bar-Ilan University, Ramat-Gan 52900, Israel.
  2. Gonda Interdisciplinary Brain Research Center and the Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan 52900, Israel.

PMID: 27530974 PMCID: PMC4987694 DOI: 10.1038/srep31674

Abstract

Catastrophic failures are complete and sudden collapses in the activity of large networks such as economics, electrical power grids and computer networks, which typically require a manual recovery process. Here we experimentally show that excitatory neural networks are governed by a non-Poissonian reoccurrence of catastrophic failures, where their repetition time follows a multimodal distribution characterized by a few tenths of a second and tens of seconds timescales. The mechanism underlying the termination and reappearance of network activity is quantitatively shown here to be associated with nodal time-dependent features, neuronal plasticity, where hyperactive nodes damage the response capability of their neighbors. It presents a complementary mechanism for the emergence of Poissonian catastrophic failures from damage conductivity. The effect that hyperactive nodes degenerate their neighbors represents a type of local competition which is a common feature in the dynamics of real-world complex networks, whereas their spontaneous recoveries represent a vitality which enhances reliable functionality.

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