%A O'Donnell,Cian %A van Rossum,Mark C. W. %D 2014 %J Frontiers in Computational Neuroscience %C %F %G English %K Channel noise,Voltage-gated ion channels,Hodgkin-Huxley,spontaneous firing,simulation %Q %R 10.3389/fncom.2014.00105 %W %L %M %P %7 %8 2014-September-04 %9 Original Research %+ Mr Cian O'Donnell,Computational Neurobiology Laboratory, Salk Institute for Biological Studies,La Jolla, CA, USA,cian@salk.edu; %+ Mr Cian O'Donnell,School of Informatics, Institute for Adaptive and Neural Computation, University of Edinburgh,Edinburgh, UK,cian@salk.edu; %+ Dr Mark C. W. van Rossum,School of Informatics, Institute for Adaptive and Neural Computation, University of Edinburgh,Edinburgh, UK,mvanross@inf.ed.ac.uk %# %! Systematic analysis of stochastic voltage gated channels %* %< %T Systematic analysis of the contributions of stochastic voltage gated channels to neuronal noise %U https://www.frontiersin.org/articles/10.3389/fncom.2014.00105 %V 8 %0 JOURNAL ARTICLE %@ 1662-5188 %X Electrical signaling in neurons is mediated by the opening and closing of large numbers of individual ion channels. The ion channels' state transitions are stochastic and introduce fluctuations in the macroscopic current through ion channel populations. This creates an unavoidable source of intrinsic electrical noise for the neuron, leading to fluctuations in the membrane potential and spontaneous spikes. While this effect is well known, the impact of channel noise on single neuron dynamics remains poorly understood. Most results are based on numerical simulations. There is no agreement, even in theoretical studies, on which ion channel type is the dominant noise source, nor how inclusion of additional ion channel types affects voltage noise. Here we describe a framework to calculate voltage noise directly from an arbitrary set of ion channel models, and discuss how this can be use to estimate spontaneous spike rates.