Restoring the encoding properties of a stochastic neuron model by an exogenous noise
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 impa...
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2015-05-01
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Online Access: | http://journal.frontiersin.org/Journal/10.3389/fncom.2015.00042/full |
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doaj-0e654c8cc1694e98b6b1e9b2c4a413032020-11-25T00:03:47ZengFrontiers Media S.A.Frontiers in Computational Neuroscience1662-51882015-05-01910.3389/fncom.2015.00042112395Restoring the encoding properties of a stochastic neuron model by an exogenous noiseAlessandra ePaffi0Alessandra ePaffi1Francesca eCamera2Francesca eCamera3Francesca eApollonio4Francesca eApollonio5Guglielmo ed'Inzeo6Guglielmo ed'Inzeo7Micaela eLiberti8Micaela eLiberti9Sapienza University of RomeItalian Inter-University Center for the Study of Electromagnetic Fields and Biological Systems (ICEmB)Sapienza University of RomeItalian Inter-University Center for the Study of Electromagnetic Fields and Biological Systems (ICEmB)Sapienza University of RomeItalian Inter-University Center for the Study of Electromagnetic Fields and Biological Systems (ICEmB)Sapienza University of RomeItalian Inter-University Center for the Study of Electromagnetic Fields and Biological Systems (ICEmB)Sapienza University of RomeItalian Inter-University Center for the Study of Electromagnetic Fields and Biological Systems (ICEmB)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.http://journal.frontiersin.org/Journal/10.3389/fncom.2015.00042/fullElectric Stimulationstochastic resonanceSignal detectionsingle neuronHH modelexogenous noise |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Alessandra ePaffi Alessandra ePaffi Francesca eCamera Francesca eCamera Francesca eApollonio Francesca eApollonio Guglielmo ed'Inzeo Guglielmo ed'Inzeo Micaela eLiberti Micaela eLiberti |
spellingShingle |
Alessandra ePaffi Alessandra ePaffi Francesca eCamera Francesca eCamera Francesca eApollonio Francesca eApollonio Guglielmo ed'Inzeo Guglielmo ed'Inzeo Micaela eLiberti Micaela eLiberti Restoring the encoding properties of a stochastic neuron model by an exogenous noise Frontiers in Computational Neuroscience Electric Stimulation stochastic resonance Signal detection single neuron HH model exogenous noise |
author_facet |
Alessandra ePaffi Alessandra ePaffi Francesca eCamera Francesca eCamera Francesca eApollonio Francesca eApollonio Guglielmo ed'Inzeo Guglielmo ed'Inzeo Micaela eLiberti Micaela eLiberti |
author_sort |
Alessandra ePaffi |
title |
Restoring the encoding properties of a stochastic neuron model by an exogenous noise |
title_short |
Restoring the encoding properties of a stochastic neuron model by an exogenous noise |
title_full |
Restoring the encoding properties of a stochastic neuron model by an exogenous noise |
title_fullStr |
Restoring the encoding properties of a stochastic neuron model by an exogenous noise |
title_full_unstemmed |
Restoring the encoding properties of a stochastic neuron model by an exogenous noise |
title_sort |
restoring the encoding properties of a stochastic neuron model by an exogenous noise |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Computational Neuroscience |
issn |
1662-5188 |
publishDate |
2015-05-01 |
description |
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. |
topic |
Electric Stimulation stochastic resonance Signal detection single neuron HH model exogenous noise |
url |
http://journal.frontiersin.org/Journal/10.3389/fncom.2015.00042/full |
work_keys_str_mv |
AT alessandraepaffi restoringtheencodingpropertiesofastochasticneuronmodelbyanexogenousnoise AT alessandraepaffi restoringtheencodingpropertiesofastochasticneuronmodelbyanexogenousnoise AT francescaecamera restoringtheencodingpropertiesofastochasticneuronmodelbyanexogenousnoise AT francescaecamera restoringtheencodingpropertiesofastochasticneuronmodelbyanexogenousnoise AT francescaeapollonio restoringtheencodingpropertiesofastochasticneuronmodelbyanexogenousnoise AT francescaeapollonio restoringtheencodingpropertiesofastochasticneuronmodelbyanexogenousnoise AT guglielmoedinzeo restoringtheencodingpropertiesofastochasticneuronmodelbyanexogenousnoise AT guglielmoedinzeo restoringtheencodingpropertiesofastochasticneuronmodelbyanexogenousnoise AT micaelaeliberti restoringtheencodingpropertiesofastochasticneuronmodelbyanexogenousnoise AT micaelaeliberti restoringtheencodingpropertiesofastochasticneuronmodelbyanexogenousnoise |
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