Emergence of power laws in noncritical neuronal systems
dc.contributor.author | Faqeeh, Ali | |
dc.contributor.author | Osat, Saeed | |
dc.contributor.author | Radicchi, Filippo | |
dc.contributor.author | Gleeson, James P. | |
dc.contributor.funder | Science Foundation Ireland | en |
dc.contributor.funder | National Science Foundation | en |
dc.contributor.funder | Army Research Office | en |
dc.date.accessioned | 2021-02-22T15:31:33Z | |
dc.date.available | 2021-02-22T15:31:33Z | |
dc.date.issued | 2019-07-02 | |
dc.description.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. | en |
dc.description.sponsorship | Science Foundation Ireland (Grants No. 16/IA/4470 and No. 16/RC/3918); National Science Foundation (CMMI-1552487); U.S. Army Research Office (W911NF-16-1-0104). | en |
dc.description.status | Peer reviewed | en |
dc.description.version | Published Version | en |
dc.format.mimetype | application/pdf | en |
dc.identifier.citation | Faqeeh, A., Osat, S., Radicchi, F. and Gleeson, J. P. (2019) 'Emergence of power laws in noncritical neuronal systems', Physical Review E, 100(1), 010401 (7 pp). doi: 10.1103/PhysRevE.100.010401 | en |
dc.identifier.doi | 10.1103/PhysRevE.100.010401 | en |
dc.identifier.eissn | 2470-0053 | |
dc.identifier.endpage | 7 | en |
dc.identifier.issn | 2470-0045 | |
dc.identifier.issued | 1 | en |
dc.identifier.journaltitle | Physical Review E | en |
dc.identifier.startpage | 1 | en |
dc.identifier.uri | https://hdl.handle.net/10468/11089 | |
dc.identifier.volume | 100 | en |
dc.language.iso | en | en |
dc.publisher | American Physical Society | en |
dc.relation.uri | https://journals.aps.org/pre/abstract/10.1103/PhysRevE.100.010401 | |
dc.rights | © 2019 American Physical Society | en |
dc.subject | Continuous percolation transition | en |
dc.subject | Degree distributions | en |
dc.subject | Network diffusion | en |
dc.subject | Network structure | en |
dc.subject | Neuronal dynamics | en |
dc.subject | Neuronal network activity | en |
dc.subject | Spreading | en |
dc.title | Emergence of power laws in noncritical neuronal systems | en |
dc.type | Article (peer-reviewed) | en |