title: Power-law statistics and universal scaling in the absence of criticality.
abstract: Critical states are sometimes identified experimentally through power-law statistics or universal scaling functions. We show here that such features naturally emerge from networks in self-sustained irregular regimes away from criticality. In these regimes, statistical physics theory of large interacting systems predict a regime where the nodes have independent and identically distributed dynamics. We thus investigated the statistics of a system in which units are replaced by independent stochastic surrogates and found the same power-law statistics, indicating that these are not sufficient to establish criticality. We rather suggest that these are universal features of large-scale networks when considered macroscopically. These results put caution on the interpretation of scaling laws found in nature.
authors.affiliation: The Mathematical Neuroscience Laboratory, CIRB/Collège de France (CNRS UMR 7241, INSERM U1050, UPMC ED 158, MEMOLIFE PSL), Paris, France.|MYCENAE Team, INRIA, Paris, France.
authors.forename: Jonathan
authors.initials: J
authors.lastname: Touboul
authors.affiliation: Unit for Neurosciences, Information and Complexity (UNIC), CNRS, Gif sur Yvette, France.|The European Institute for Theoretical Neuroscience (EITN), Paris, France.
authors.forename: Alain
authors.initials: A
authors.lastname: Destexhe