Background activity drives criticality of neuronal avalanches

Juanico, Dranreb Earl; Monterola, Christopher

doi:10.1088/1751-8113/40/31/008

Cited by 13 publications

(8 citation statements)

References 35 publications

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“…One class of models, based on self‐organized criticality (SOC) [ Hergarten and Neugebauer , 1998; Piegari et al , 2006], hint at some possible mechanisms yielding the observed statistics. SOC is a theory underlying the spontaneous emergence of critical‐like behavior (i.e., power laws and critical exponents) in systems for which the timescales between buildup and release of stress are separated, and for which the stress‐transfer mechanism is generally nonconservative [ Juanico et al , 2007a, 2007b; Juanico and Monterola , 2007]. SOC concepts have aroused great interest in the study of granular matter [ Jaeger et al , 1989], a well‐known example of which is the ricepile experiment [ Frette et al , 1996].…”

Section: Introductionmentioning

confidence: 99%

Avalanche statistics of driven granular slides in a miniature mound

Juanico¹,

Longjas²,

Batac³

et al. 2008

Geophysical Research Letters

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We examine avalanche statistics of rain‐ and vibration‐driven granular slides in miniature sand mounds. A crossover from power‐law to non power‐law avalanche‐size statistics is demonstrated as a generic driving rate ν is increased. For slowly‐driven mounds, the tail of the avalanche‐size distribution is a power‐law with exponent −1.97 ± 0.31, reasonably close to a value previously reported for landslide volumes. The interevent occurrence times are also analyzed for slowly‐driven mounds; its distribution exhibits a power‐law with exponent −2.670 ± 0.001.

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Section: Introductionmentioning

confidence: 99%

Avalanche statistics of driven granular slides in a miniature mound

Juanico¹,

Longjas²,

Batac³

et al. 2008

Geophysical Research Letters

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“…We study Bak-TangWiesenfeld sandpile dynamics (23,24) on networks derived from real, interdependent power grids and on sparsely coupled, random regular graphs that approximate the real topologies. Sandpile dynamics are paradigms for the cascades of load, self-organized criticality, and power law distributions of event sizes that pervade disciplines, from neuronal avalanches (25)(26)(27) to cascades among banks (28) to earthquakes (29), landslides (30), forest fires (31,32), solar flares (33,34), and electrical blackouts (15). Sandpile cascades have been extensively studied on isolated networks (35)(36)(37)(38)(39)(40)(41).…”

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confidence: 99%

Suppressing cascades of load in interdependent networks

Brummitt¹,

D’Souza

Leicht

2012

Proc. Natl. Acad. Sci. U.S.A.

491

347

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Understanding how interdependence among systems affects cascading behaviors is increasingly important across many fields of science and engineering. Inspired by cascades of load shedding in coupled electric grids and other infrastructure, we study the BakTang-Wiesenfeld sandpile model on modular random graphs and on graphs based on actual, interdependent power grids. Starting from two isolated networks, adding some connectivity between them is beneficial, for it suppresses the largest cascades in each system. Too much interconnectivity, however, becomes detrimental for two reasons. First, interconnections open pathways for neighboring networks to inflict large cascades. Second, as in real infrastructure, new interconnections increase capacity and total possible load, which fuels even larger cascades. Using a multitype branching process and simulations we show these effects and estimate the optimal level of interconnectivity that balances their trade-offs. Such equilibria could allow, for example, power grid owners to minimize the largest cascades in their grid. We also show that asymmetric capacity among interdependent networks affects the optimal connectivity that each prefers and may lead to an arms race for greater capacity. Our multitype branching process framework provides building blocks for better prediction of cascading processes on modular random graphs and on multitype networks in general.vulnerability of infrastructure | complex networks

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“…Many complex systems affecting modern life, from infrastructure systems like power grids to the natural catastrophes that threaten them, appear to be poised near criticality. For instance, power law distributions seem to characterize the sizes of electrical blackouts [1], financial fluctuations [2], neuronal avalanches [3][4][5], earthquakes [6], landslides [7], overspill in water reservoirs [8], forest fires [9,10] and solar flares [11,12]. Since its introduction in 1987 [13,14], the Bak-Tang-Wiesenfeld (BTW) sandpile has served as a useful paradigm for the self-organizing dynamics that may drive these systems toward critical points (also called self-organized criticality or SOC).…”

Section: Introductionmentioning

confidence: 99%

Bottom-up model of self-organized criticality on networks

2014

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The Bak-Tang-Wiesenfeld (BTW) sandpile process is an archetypal, stylized model of complex systems with a critical point as an attractor of their dynamics. This phenomenon, called self-organized criticality, appears to occur ubiquitously in both nature and technology. Initially introduced on the two-dimensional lattice, the BTW process has been studied on network structures with great analytical successes in the estimation of macroscopic quantities, such as the exponents of asymptotically power-law distributions. In this article, we take a microscopic perspective and study the inner workings of the process through both numerical and rigorous analysis. Our simulations reveal fundamental flaws in the assumptions of past phenomenological models, the same models that allowed accurate macroscopic predictions; we mathematically justify why universality may explain these past successes. Next, starting from scratch, we obtain microscopic understanding that enables mechanistic models; such models can, for example, distinguish a cascade's area from its size. In the special case of a 3-regular network, we use self-consistency arguments to obtain a zero-parameter mechanistic (bottom-up) approximation that reproduces nontrivial correlations observed in simulations and that allows the study of the BTW process on networks in regimes otherwise prohibitively costly to investigate. We then generalize some of these results to configuration model networks and explain how one could continue the generalization. The numerous tools and methods presented herein are known to enable studying the effects of controlling the BTW process and other self-organizing systems. More broadly, our use of multitype branching processes to capture information bouncing back and forth in a network could inspire analogous models of systems in which consequences spread in a bidirectional fashion.

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Background activity drives criticality of neuronal avalanches

Cited by 13 publications

References 35 publications

Avalanche statistics of driven granular slides in a miniature mound

Avalanche statistics of driven granular slides in a miniature mound

Suppressing cascades of load in interdependent networks

Bottom-up model of self-organized criticality on networks

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