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Emergence of power laws in noncritical neuronal systems

Ali Faqeeh, Saeed Osat, Filippo Radicchi, and James P. Gleeson
Phys. Rev. E 100, 010401(R) – Published 2 July 2019
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Abstract

Experimental and computational studies provide compelling evidence that neuronal systems are characterized by power-law distributions of neuronal avalanche sizes. This fact is interpreted as an indication that these systems are operating near criticality, and, in turn, typical properties of critical dynamical processes, such as optimal information transmission and stability, are attributed to neuronal systems. The purpose of this Rapid Communication is to show that the presence of power-law distributions for the size of neuronal avalanches is not a sufficient condition for the system to operate near criticality. Specifically, we consider a simplistic model of neuronal dynamics on networks and show that the degree distribution of the underlying neuronal network may trigger power-law distributions for neuronal avalanches even when the system is not in its critical regime. To certify and explain our findings we develop an analytical approach based on percolation theory and branching processes techniques.

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  • Received 26 February 2019

DOI:https://doi.org/10.1103/PhysRevE.100.010401

©2019 American Physical Society

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Authors & Affiliations

Ali Faqeeh1,2,*, Saeed Osat3, Filippo Radicchi2, and James P. Gleeson1

  • 1Mathematics Consortium for Science and Industry, Department of Mathematics and Statistics, University of Limerick, Limerick V94 T9PX, Ireland
  • 2Center for Complex Networks and Systems Research, School of Informatics, Computing, and Engineering, Indiana University, Bloomington, Indiana 47408, USA
  • 3Deep Quantum Labs, Skolkovo Institute of Science and Technology, Moscow 143026, Russia

  • *afaqeeh@iu.edu

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Issue

Vol. 100, Iss. 1 — July 2019

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