Diffusion approximation of neuronal models revisited.
Leaky integrate-and-fire neuronal models with reversal potentials have a number of different diffusion approximations, each depending on the form of the amplitudes of the postsynaptic potentials. Probability distributions of the first-passage times of the membrane potential in the original model and its diffusion approximations are numerically compared in order to find which of the approximations is the most suitable one. The properties of the random amplitudes of postsynaptic potentials are discussed. It is shown on a simple example that the quality of the approximation depends directly on them.
Institute of Physiology, Academy of Sciences of the Czech Republic, Videnska 1083, 142 20 Prague 4, Czech Republic. xcupera@mail.muni.cz.
Jakub
J
Cupera
D000200:Action Potentials / Q000502:physiology; D003198:Computer Simulation; D004058:Diffusion; D006801:Humans; D008433:Mathematics; D008564:Membrane Potentials / Q000502:physiology; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology*; D016011:Normal Distribution; D016012:Poisson Distribution; D011336:Probability; D013269:Stochastic Processes; D055366:Synaptic Potentials