ArticlePhysical review. E2019
Emergence of power laws in noncritical neuronal systems.
Article in Physical review. E, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A methodological guideline for consciousness assessment via neural electrophysiological activity.Military Medical Research · 2025Guideline
- The fractal brain: scale-invariance in structure and dynamics.Cerebral cortex (New York, N.Y. : 1991) · 2023Review
- Disentangling the critical signatures of neural activity.Scientific reports · 2022Article
- Self-organized criticality as a framework for consciousness: A review study.Frontiers in psychology · 2022Article
- Percolation and tortuosity in heart-like cells.Scientific reports · 2021Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
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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Registered trials
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