A fast Markovian method for modeling channel noise in neurons.

ABSTRACT: Channel noise results from rapid transitions of protein channels from closed to open state and is generally considered as the most dominant source of electrical noise causing membrane-potential fluctuations even in the absence of synaptic inputs. The simulation of a realistic channel noise remains a source of possible error. Although the Markovian method is considered as the golden standard for appropriate description of channel noise, its computation time increasing exponentially with the number of channels, it is poorly suitable to simulate realistic features. We describe here a novel algorithm at discrete time unit for simulating ion channel noise based on Markov chains (MC). Although this new algorithm refers to a Monte-Carlo process, it only needs few random numbers whatever the numbe

SUBMITTER: Ankri N 

PROVIDER: S-EPMC10361033 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature