title: Restoring the encoding properties of a stochastic neuron model by an exogenous noise.
abstract: Here we evaluate the possibility of improving the encoding properties of an impaired neuronal system by superimposing an exogenous noise to an external electric stimulation signal. The approach is based on the use of mathematical neuron models consisting of stochastic HH-like circuit, where the impairment of the endogenous presynaptic inputs is described as a subthreshold injected current and the exogenous stimulation signal is a sinusoidal voltage perturbation across the membrane. Our results indicate that a correlated Gaussian noise, added to the sinusoidal signal can significantly increase the encoding properties of the impaired system, through the Stochastic Resonance (SR) phenomenon. These results suggest that an exogenous noise, suitably tailored, could improve the efficacy of those stimulation techniques used in neuronal systems, where the presynaptic sensory neurons are impaired and have to be artificially bypassed.
authors.affiliation: Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome Rome, Italy ; Italian Inter-University Center for the Study of Electromagnetic Fields and Biological Systems Genova, Italy.
authors.forename: Alessandra
authors.initials: A
authors.lastname: Paffi
authors.affiliation: Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome Rome, Italy ; Italian Inter-University Center for the Study of Electromagnetic Fields and Biological Systems Genova, Italy.
authors.forename: Francesca
authors.initials: F
authors.lastname: Camera
authors.affiliation: Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome Rome, Italy ; Italian Inter-University Center for the Study of Electromagnetic Fields and Biological Systems Genova, Italy.
authors.forename: Francesca
authors.initials: F
authors.lastname: Apollonio
authors.affiliation: Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome Rome, Italy ; Italian Inter-University Center for the Study of Electromagnetic Fields and Biological Systems Genova, Italy.
authors.forename: Guglielmo
authors.initials: G
authors.lastname: d'Inzeo
authors.affiliation: Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome Rome, Italy ; Italian Inter-University Center for the Study of Electromagnetic Fields and Biological Systems Genova, Italy.
authors.forename: Micaela
authors.initials: M
authors.lastname: Liberti
keywords: HH model; electric stimulation; exogenous noise; signal detection; single neuron; stochastic resonance