Channel noise may tune electromagnetic fields detectability in neurons: Stochastic resonance paradigm in a HH-like model

Neuronal encoding of an electromagnetic (EM) signal is investigated in the presence of biological noise. This has already been shown to act as a tuning factor in neuronal processing and reliability, according to the stochastic resonant (SR) paradigm. SR was previously observed by the authors in the detectability of EM signals in the case of a white Gaussian noisy input, roughly approximating the ensemble of possible noise sources in neurons. Here attention is focused on noise arising from the stochastic gating of ionic channels, which has been recently shown to be at the basis of some well known biophysical behaviors, such as response unreliability, missing spikes during firing, or spontaneous action potentials during resting state. For this purpose, accurate models of ionic channels are considered, based on Markov state machines, and introduced into the HH neuronal description. A stochastic resonant behavior is observed in the detection of a 50 Hz sinusoidal signal, also dependent on the mean synaptic stimulation. These results suggest that neuron typologies with different channels number (and noise intensities) detect EM signals in a very different way, and related field-induced effects may also vary.