- Poster Presentation
- Open Access
Supra-threshold stochastic resonance in a population of stochastic Hogkin-Huxley neuron models with random ion channel gating
BMC Neuroscience volume 11, Article number: P177 (2010)
Supra-threshold stochastic resonance (SSR) refers to a phenomenon what an optimally added noise can enhance information transmission when a supra-threshold signal is driven into an array of non-linear systems with threshold . The noise in neurons has been considered to come up from not only randomness of synaptic vesicle secretions (extrinsic fluctuations) but also stochasticity of ion channel gating (intrinsic fluctuations). However, it is still unclear whether and how those fluctuations help enhance information transmission in the case of supra-threshold input signals. The objective of this presentation was to see how randomness of ion channel gating could affect spike firing times and mutual information, and if SSR could be observed or not through computer simulations.
Methods and results
A supra-threshold filtered Poisson process with an intensity of 10 [s-1] was applied into an array of 50 stochastic Hodgkin-Huxley (HH) neuron models possessing stochastic sodium and potassium channels with a patch area of 100, 200, ..., and 700 [um2]. The stochastic ion channel gating was implemented by the channel-number tracking algorithm . Each output spike train of neuron models was gathered and moving-averaged for calculating the rate of spike trains. Ten kinds of input realizations were applied repeatedly ten times to the array in order to estimate the total and noise entropies of the spike firing rate for calculating mutual information. Figures 1 and 2.
It follows that the mutual information was maximized at an optimal patch size in an array of stochastic HH neuron models, and therefore that SSR was observed in the presence of intrinsic fluctuations. This phenomenon may be aptly called ``intrinsic’’ SSR (ISSR). ISSR could play a key role in processing excessive input signals into sensory nervous systems.
Stocks NG: Suprathreshold stochastic resonance in multilevel threshold systems. Phys. Rev. Lett. 2000, 84: 2310-2313. 10.1103/PhysRevLett.84.2310.
Mino H, et al.: Comparison of algorithms for the simulation of action potentials with stochastic sodium channels. Ann. Biomed. Eng. 2002, 30: 578-587. 10.1114/1.1475343.
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Cite this article
Mino, H. Supra-threshold stochastic resonance in a population of stochastic Hogkin-Huxley neuron models with random ion channel gating. BMC Neurosci 11, P177 (2010). https://doi.org/10.1186/1471-2202-11-S1-P177
- Mutual Information
- Spike Train
- Neuron Model
- Spike Firing
- Optimal Patch