Self-organization without conservation: Are neuronal avalanches generically critical?

TL;DR

This paper challenges the idea that cortical neural networks naturally exhibit critical avalanches, showing that such criticality is unlikely without fine-tuning, and suggests more complex mechanisms may be needed if true criticality is observed.

Contribution

The study demonstrates that neural networks with dissipation and loading are not generically critical, contrasting with previous claims and models, and emphasizes the need for more complex explanations.

Findings

Neural networks are typically sub- or super-critical without fine-tuning.

Pseudo-critical regions are broad but do not imply true criticality.

Experimental evidence of true criticality would require explanations beyond simple self-organization.

Abstract

Recent experiments on cortical neural networks have revealed the existence of well-defined avalanches of electrical activity. Such avalanches have been claimed to be generically scale-invariant -- i.e. power-law distributed -- with many exciting implications in Neuroscience. Recently, a self-organized model has been proposed by Levina, Herrmann and Geisel to justify such an empirical finding. Given that (i) neural dynamics is dissipative and (ii) there is a loading mechanism "charging" progressively the background synaptic strength, this model/dynamics is very similar in spirit to forest-fire and earthquake models, archetypical examples of non-conserving self-organization, which have been recently shown to lack true criticality. Here we show that cortical neural networks obeying (i) and (ii) are not generically critical; unless parameters are fine tuned, their dynamics is either sub- or super-critical, even if the pseudo-critical region is relatively broad. This conclusion seems to be in agreement with the most recent experimental observations. The main implication of our work is that, if future experimental research on cortical networks were to support that truly critical avalanches are the norm and not the exception, then one should look for more elaborate (adaptive/evolutionary) explanations, beyond simple self-organization, to account for this.