title: Noise-induced memory in extended excitable systems.
abstract: We describe a form of memory exhibited by extended excitable systems driven by stochastic fluctuations. Under such conditions, the system self-organizes into a state characterized by power-law correlations, thus retaining long-term memory of previous states. The exponents are robust and model independent. We discuss implications of these results for the functioning of cortical neurons as well as for networks of neurons.
authors.affiliation: Center for Studies in Physics and Biology, Rockefeller University, New York, New York 10021, USA.
authors.forename: D R
authors.initials: DR
authors.lastname: Chialvo
authors.forename: G A
authors.initials: GA
authors.lastname: Cecchi
authors.forename: M O
authors.initials: MO
authors.lastname: Magnasco
mesh_terms: D000161:Acoustic Stimulation; D000465:Algorithms; D000818:Animals; D002540:Cerebral Cortex / Q000502:physiology*; D008568:Memory / Q000502:physiology*; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009474:Neurons / Q000502:physiology*; D009622:Noise; D013269:Stochastic Processes; D013570:Synaptic Membranes / Q000502:physiology