English

Mechanisms of self-organized quasicriticality in neuronal networks models

Disordered Systems and Neural Networks 2020-10-22 v1 Adaptation and Self-Organizing Systems

Abstract

The critical brain hypothesis states that there are information processing advantages for neuronal networks working close to the critical region of a phase transition. If this is true, we must ask how the networks achieve and maintain this critical state. Here we review several proposed biological mechanisms that turn the critical region into an attractor of a dynamics in network parameters like synapses, neuronal gains and firing thresholds. Since neuronal networks (biological and models) are nonconservative but dissipative, we expect not exact criticality but self-organized quasicriticality (SOqC), where the system hovers around the critical point.

Keywords

Cite

@article{arxiv.2010.10622,
  title  = {Mechanisms of self-organized quasicriticality in neuronal networks models},
  author = {Osame Kinouchi and Renata Pazzini and Mauro Copelli},
  journal= {arXiv preprint arXiv:2010.10622},
  year   = {2020}
}

Comments

35 pages, 1 figure, in press Frontiers of Physics