We introduce and operatively present a general method to simulate channel noise in conductance-based model neurons, with modest computational overheads. Our approach may be considered as an accurate generalization of previous proposal methods, to the case of voltage-, ion-, and ligand-gated channels with arbitrary complexity. We focus on the discrete Markov process descriptions, routinely employed in experimental identification of voltage-gated channels and synaptic receptors.
Model Type: Neuron or other electrically excitable cell
Region(s) or Organism(s): Neocortex
Implementer(s): Linaro, Daniele [daniele.linaro at unige.it]