Power-law correlations and coupling of active and quiet states underlie a class of complex systems with self-organization at criticality

F. Lombardi, J.W.J.L. Wang, X. Zhang, P.C. Ivanov, EPJ Web of Conferences 230 (2020).

Download
OA 2020_EPJWebConf_Lombardi.pdf 2.20 MB

Journal Article | Published | English
Author
Lombardi, FabrizioIST Austria ; Wang, Jilin W.J.L.; Zhang, Xiyun; Ivanov, Plamen Ch
Department
Abstract
Physical and biological systems often exhibit intermittent dynamics with bursts or avalanches (active states) characterized by power-law size and duration distributions. These emergent features are typical of systems at the critical point of continuous phase transitions, and have led to the hypothesis that such systems may self-organize at criticality, i.e. without any fine tuning of parameters. Since the introduction of the Bak-Tang-Wiesenfeld (BTW) model, the paradigm of self-organized criticality (SOC) has been very fruitful for the analysis of emergent collective behaviors in a number of systems, including the brain. Although considerable effort has been devoted in identifying and modeling scaling features of burst and avalanche statistics, dynamical aspects related to the temporal organization of bursts remain often poorly understood or controversial. Of crucial importance to understand the mechanisms responsible for emergent behaviors is the relationship between active and quiet periods, and the nature of the correlations. Here we investigate the dynamics of active (θ-bursts) and quiet states (δ-bursts) in brain activity during the sleep-wake cycle. We show the duality of power-law (θ, active phase) and exponential-like (δ, quiescent phase) duration distributions, typical of SOC, jointly emerge with power-law temporal correlations and anti-correlated coupling between active and quiet states. Importantly, we demonstrate that such temporal organization shares important similarities with earthquake dynamics, and propose that specific power-law correlations and coupling between active and quiet states are distinctive characteristics of a class of systems with self-organization at criticality.
Publishing Year
Date Published
2020-03-11
Journal Title
EPJ Web of Conferences
Volume
230
Article Number
00005
ISSN
IST-REx-ID

Cite this

Lombardi F, Wang JWJL, Zhang X, Ivanov PC. Power-law correlations and coupling of active and quiet states underlie a class of complex systems with self-organization at criticality. EPJ Web of Conferences. 2020;230. doi:10.1051/epjconf/202023000005
Lombardi, F., Wang, J. W. J. L., Zhang, X., & Ivanov, P. C. (2020). Power-law correlations and coupling of active and quiet states underlie a class of complex systems with self-organization at criticality. EPJ Web of Conferences, 230. https://doi.org/10.1051/epjconf/202023000005
Lombardi, Fabrizio, Jilin W.J.L. Wang, Xiyun Zhang, and Plamen Ch Ivanov. “Power-Law Correlations and Coupling of Active and Quiet States Underlie a Class of Complex Systems with Self-Organization at Criticality.” EPJ Web of Conferences 230 (2020). https://doi.org/10.1051/epjconf/202023000005.
F. Lombardi, J. W. J. L. Wang, X. Zhang, and P. C. Ivanov, “Power-law correlations and coupling of active and quiet states underlie a class of complex systems with self-organization at criticality,” EPJ Web of Conferences, vol. 230, 2020.
Lombardi F, Wang JWJL, Zhang X, Ivanov PC. 2020. Power-law correlations and coupling of active and quiet states underlie a class of complex systems with self-organization at criticality. EPJ Web of Conferences. 230.
Lombardi, Fabrizio, et al. “Power-Law Correlations and Coupling of Active and Quiet States Underlie a Class of Complex Systems with Self-Organization at Criticality.” EPJ Web of Conferences, vol. 230, 00005, EDP Sciences, 2020, doi:10.1051/epjconf/202023000005.
All files available under the following license(s):
Creative Commons Attribution 4.0 International Public License (CC-BY 4.0):
Main File(s)
Access Level
OA Open Access
Date Uploaded
2020-07-22


Export

Marked Publications

Open Data IST Research Explorer

Search this title in

Google Scholar