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...
Main Authors: | Alessandra ePaffi, Francesca eCamera, Francesca eApollonio, Guglielmo ed'Inzeo, Micaela eLiberti |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2015-05-01
|
Series: | Frontiers in Computational Neuroscience |
Subjects: | |
Online Access: | http://journal.frontiersin.org/Journal/10.3389/fncom.2015.00042/full |
Similar Items
-
Numerical Characterization of Intraoperative and Chronic Electrodes in Deep Brain Stimulation
by: Alessandra ePaffi, et al.
Published: (2015-02-01) -
The CNP signal is able to silence a supra threshold neuronal model
by: Francesca eCamera, et al.
Published: (2015-04-01) -
Stimulation Strategies for Tinnitus Suppression in a Neuron Model
by: Alessandra Paffi, et al.
Published: (2018-01-01) -
Revealing Spectrum Features of Stochastic Neuron Spike Trains
by: Simone Orcioni, et al.
Published: (2020-06-01) -
A Computational Model for Real-Time Calculation of Electric Field due to Transcranial Magnetic Stimulation in Clinics
by: Alessandra Paffi, et al.
Published: (2015-01-01)