title: Noise in neurons is message dependent.
abstract: Neuronal responses are conspicuously variable. We focus on one particular aspect of that variability: the precision of action potential timing. We show that for common models of noisy spike generation, elementary considerations imply that such variability is a function of the input, and can be made arbitrarily large or small by a suitable choice of inputs. Our considerations are expected to extend to virtually any mechanism of spike generation, and we illustrate them with data from the visual pathway. Thus, a simplification usually made in the application of information theory to neural processing is violated: noise is not independent of the message. However, we also show the existence of error-correcting topologies, which can achieve better timing reliability than their components.
authors.affiliation: Center for Studies in Physics and Biology, The Rockefeller University, New York, NY 10021, USA. guille@tlon.rockefeller.edu
authors.forename: G A
authors.initials: GA
authors.lastname: Cecchi
authors.forename: M
authors.initials: M
authors.lastname: Sigman
authors.forename: J M
authors.initials: JM
authors.lastname: Alonso
authors.forename: L
authors.initials: L
authors.lastname: Martínez
authors.forename: D R
authors.initials: DR
authors.lastname: Chialvo
authors.forename: M O
authors.initials: MO
authors.lastname: Magnasco
mesh_terms: D001921:Brain / Q000502:physiology*; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology; D009474:Neurons / Q000502:physiology*; D009622:Noise; D013997:Time Factors