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.
Highlights
Different techniques for the stimulation of neuronal systems have been developed
The main aim of this paper is to show that the reduced encoding capability of pathologically understimulated neuronal systems can be improved using an exogenous noise, opening the way for prosthetic applicators delivering the exogenous stimulation signal and noise
It is known from literature that Hodgkin and Huxley (HH) models exhibit a frequency sensitivity that depends on the model parameters, on the constant input current I0 (Liu et al, 1999; Yu et al, 2001a; Giannì et al, 2006)
Summary
Different techniques for the stimulation of neuronal systems have been developed. Some are based on magnetic coupling, such as the Transcranial Magnetic Stimulation (TMS) (Corthout et al, 2001) and low-intensity magnetic stimulation (Di Lazzaro et al, 2013), while others use electric fields, such as Deep Brain Stimulation (DBS) (Okun et al, 2012; Paffi et al, 2013a), Functional Electric Stimulation (FES) of peripheral nerves (Peckham and Knutson, 2005), cochlear prostheses (Wilson et al, 1991; Clark, 2003), and Intracortical Microstimulation (ICMS) (Brock et al, 2013; Overstreet et al, 2013).Despite great interest in such applications and the experimental activities to evaluate the effect of electromagnetic fields on single neurons and networks (Marchionni et al, 2006; Platano et al, 2007; Ahmed and Wieraszko, 2009; Moretti et al, 2013), the mechanisms of action are not clearly understood (Apollonio et al, 2013; Di Lazzaro et al, 2013) and the techniques are not yet optimized.Theoretical studies to understand neuronal system functioning are based on biophysical models. The HH model is a nonlinear active circuit, which behaves as an oscillator if the injected constant current (stimulation current) overcomes a threshold (Rinzel and Ermentrout, 1998). Unless a current is directly injected across the membrane, the interaction between the exogenous signal and the neuron membrane must be inserted as a voltage generator in series with the neuron circuital model (Figure 1), as already done in number of studies (Tsong and Astumian, 1987; Mino et al, 2004; Giannì et al, 2006; Woo et al, 2010; Paffi et al, 2013b). The use of a Lorentzian behavior is a straightforward choice since, under the passive linear approximation (Steinmetz et al, 2000), the neuronal membrane behaves like a single pole filter with a time constant equal to the membrane capacitance divided by the total conductivity of the ionic channels in the patch (Rinzel and Ermentrout, 1998)
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