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Channel based generating function approach to the stochastic Hodgkin-Huxley neuronal system
Author(s) -
Anqi Ling,
Yandong Huang,
Jianwei Shuai,
Yueheng Lan
Publication year - 2016
Publication title -
scientific reports
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.24
H-Index - 213
ISSN - 2045-2322
DOI - 10.1038/srep22662
Subject(s) - noise (video) , hodgkin–huxley model , action (physics) , computation , computer science , channel (broadcasting) , function (biology) , signal (programming language) , algorithm , biological system , statistical physics , neuroscience , artificial intelligence , physics , biology , telecommunications , quantum mechanics , evolutionary biology , image (mathematics) , programming language
Internal and external fluctuations, such as channel noise and synaptic noise, contribute to the generation of spontaneous action potentials in neurons. Many different Langevin approaches have been proposed to speed up the computation but with waning accuracy especially at small channel numbers. We apply a generating function approach to the master equation for the ion channel dynamics and further propose two accelerating algorithms, with an accuracy close to the Gillespie algorithm but with much higher efficiency, opening the door for expedited simulation of noisy action potential propagating along axons or other types of noisy signal transduction.

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