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No Access Submitted: 05 April 2019 Accepted: 08 August 2019 Published Online: 28 August 2019

  • Impact of targeted attack on the spontaneous activity in spatial and biologically-inspired neuronal networks

Chaos 29, 083126 (2019); https://doi.org/10.1063/1.5099038
Sergio Faci-Lázaro1,2, Jordi Soriano3,4, and Jesús Gómez-Gardeñes1,2
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  • Sergio Faci-Lázaro
  • Jordi Soriano
  • Jesús Gómez-Gardeñes
ABSTRACT
We study the structural and dynamical consequences of damage in spatial neuronal networks. Inspired by real in vitro networks, we construct directed networks embedded in a two-dimensional space and follow biological rules for designing the wiring of the system. As a result, synthetic cultures display strong metric correlations similar to those observed in real experiments. In its turn, neuronal dynamics is incorporated through the Izhikevich model adopting the parameters derived from observation in real cultures. We consider two scenarios for damage, targeted attacks on those neurons with the highest out-degree and random failures. By analyzing the evolution of both the giant connected component and the dynamical patterns of the neurons as nodes are removed, we observe that network activity halts for a removal of 50% of the nodes in targeted attacks, much lower than the 70% node removal required in the case of random failures. Notably, the decrease of neuronal activity is not gradual. Both damage scenarios portray “boosts” of activity just before full silencing that are not present in equivalent random (Erdös–Rényi) graphs. These boosts correspond to small, spatially compact subnetworks that are able to maintain high levels of activity. Since these subnetworks are absent in the equivalent random graphs, we hypothesize that metric correlations facilitate the existence of local circuits sufficiently integrated to maintain activity, shaping an intrinsic mechanism for resilience.

ACKNOWLEDGMENTS

We acknowledge financial support from the Spanish Ministerio de Economia y Competitividad through Project Nos. FIS2015-71582-C2, FIS2016-78507-C2-2-P, FIS2017-87519-P, and FIS2017-90782-REDT (IBERSINC), from the Generalitat de Catalunya through Grant No. 2017-SGR-1061, and from the Departamento de Industria e Innovación del Gobierno de Aragón y Fondo Social Europeo (FENOL group). S.F.L. acknowledges financial support from Gobierno de Aragon through a doctoral fellowship.

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  1. © 2019 Author(s). Published under license by AIP Publishing.

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