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.

Restoring the encoding properties of a stochastic neuron model by an exogenous noise / Paffi, Alessandra; Camera, Francesca; Apollonio, Francesca; D'Inzeo, Guglielmo; Liberti, Micaela. - In: FRONTIERS IN COMPUTATIONAL NEUROSCIENCE. - ISSN 1662-5188. - ELETTRONICO. - 9:(2015). [10.3389/fncom.2015.00042]

Restoring the encoding properties of a stochastic neuron model by an exogenous noise

PAFFI, ALESSANDRA;CAMERA, FRANCESCA;APOLLONIO, Francesca;D'INZEO, Guglielmo;LIBERTI, Micaela
2015

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.
2015
single neuron; HH model; electric stimulation; exogenous noise; stochastic resonance; signal detection
01 Pubblicazione su rivista::01a Articolo in rivista
Restoring the encoding properties of a stochastic neuron model by an exogenous noise / Paffi, Alessandra; Camera, Francesca; Apollonio, Francesca; D'Inzeo, Guglielmo; Liberti, Micaela. - In: FRONTIERS IN COMPUTATIONAL NEUROSCIENCE. - ISSN 1662-5188. - ELETTRONICO. - 9:(2015). [10.3389/fncom.2015.00042]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/783136
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