title: The role of noise in self-organized decision making by the true slime mold Physarum polycephalum.
abstract: Self-organized mechanisms are frequently encountered in nature and known to achieve flexible, adaptive control and decision-making. Noise plays a crucial role in such systems: It can enable a self-organized system to reliably adapt to short-term changes in the environment while maintaining a generally stable behavior. This is fundamental in biological systems because they must strike a delicate balance between stable and flexible behavior. In the present paper we analyse the role of noise in the decision-making of the true slime mold Physarum polycephalum, an important model species for the investigation of computational abilities in simple organisms. We propose a simple biological experiment to investigate the reaction of P. polycephalum to time-variant risk factors and present a stochastic extension of an established mathematical model for P. polycephalum to analyze this experiment. It predicts that-due to the mechanism of stochastic resonance-noise can enable P. polycephalum to correctly assess time-variant risk factors, while the corresponding noise-free system fails to do so. Beyond the study of P. polycephalum we demonstrate that the influence of noise on self-organized decision-making is not tied to a specific organism. Rather it is a general property of the underlying process dynamics, which appears to be universal across a wide range of systems. Our study thus provides further evidence that stochastic resonance is a fundamental component of the decision-making in self-organized macroscopic and microscopic groups and organisms.
authors.affiliation: Faculty of Information Technology, Monash University, Melbourne, Victoria, Australia.
authors.forename: Bernd
authors.identifier: http://orcid.org/0000-0003-1080-0338
authors.initials: B
authors.lastname: Meyer
authors.affiliation: Institute for Geophysics and Meteorology, University of Cologne, Cologne, Germany.
authors.forename: Cedrick
authors.initials: C
authors.lastname: Ansorge
authors.affiliation: Research Institute for Electronic Science, Hokkaido University, Sapporo, Japan.
authors.forename: Toshiyuki
authors.initials: T
authors.lastname: Nakagaki
mesh_terms: D000066949:Biobehavioral Sciences; D004777:Environment; D018782:Maze Learning / Q000502:physiology*; D044367:Phase Transition; D016839:Physarum polycephalum / Q000502:physiology*; D013269:Stochastic Processes