title: Self-organized criticality as a fundamental property of neural systems.
abstract: The neural criticality hypothesis states that the brain may be poised in a critical state at a boundary between different types of dynamics. Theoretical and experimental studies show that critical systems often exhibit optimal computational properties, suggesting the possibility that criticality has been evolutionarily selected as a useful trait for our nervous system. Evidence for criticality has been found in cell cultures, brain slices, and anesthetized animals. Yet, inconsistent results were reported for recordings in awake animals and humans, and current results point to open questions about the exact nature and mechanism of criticality, as well as its functional role. Therefore, the criticality hypothesis has remained a controversial proposition. Here, we provide an account of the mathematical and physical foundations of criticality. In the light of this conceptual framework, we then review and discuss recent experimental studies with the aim of identifying important next steps to be taken and connections to other fields that should be explored.
authors.affiliation: Computational Neurophysiology Group, Institute for Theoretical Biology, Humboldt Universität zu Berlin Berlin, Germany ; Bernstein Center for Computational Neuroscience Berlin Berlin, Germany ; École Normale Supérieure Paris, France.
authors.forename: Janina
authors.initials: J
authors.lastname: Hesse
authors.affiliation: Department of Engineering Mathematics, Merchant Venturers School of Engineering, University of Bristol Bristol, UK.
authors.forename: Thilo
authors.initials: T
authors.lastname: Gross
keywords: brain; dynamics; neural network; phase transition; self-organized criticality