title: Stochastic resonance induced by exogenous noise in a model of a neuronal network.
abstract: This study investigates the possibility of using exogenous noise to restore the processing performances of neuronal systems where the endogenous noise is reduced due to the ageing or to degenerative diseases. This idea is based on the assumption, supported by theoretical studies, that the endogenous noise has a positive role in neuronal signal detection and that its reduction impairs the system function. Results, obtained on a two-layers feedforward network, show the onset of the Stochastic Resonance (SR) behavior, as long as the exogenous noise is properly tailored and filtered. The amount of noise to be furnished from the outside to optimize the system performance depends on the residual level of endogenous noise, indicating that both kinds of noise cooperate to the signal detection. These results support potentially new bioengineering applications where exogenous noise is furnished to enhance signal detectability.
authors: Sapienza University of Rome, Department of Information Engineering, Electronics and Telecommunication, Via Eudossiana 18, 0184 Rome, Italy. paffi@die.uniroma1.it
authors: Alessandra
authors: A
authors: Paffi
authors: Francesca
authors: F
authors: Apollonio
authors: Guglielmo
authors: G
authors: d'Inzeo
authors: Micaela
authors: M
authors: Liberti
mesh_terms: D004558:Electric Stimulation / Q000009:adverse effects / Q000379:methods; D004560:Electricity / Q000009:adverse effects*; D008959:Models, Neurological; D016571:Neural Networks, Computer; D013269:Stochastic Processes