ArticlePLoS computational biology2011
Accurate and fast simulation of channel noise in conductance-based model neurons by diffusion approximation.
Article in PLoS computational biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
27 citing papers in PubMed, 90 citations in OpenAlex.
- Power spectral analysis of voltage-gated channels in neurons.Frontiers in neuroinformatics · 2024Article
- Article
- Dimensional reduction in networks of non-Markovian spiking neurons: Equivalence of synaptic filtering and heterogeneous propagation delays.PLoS computational biology · 2019Article
- Data-driven inference for stationary jump-diffusion processes with application to membrane voltage fluctuations in pyramidal neurons.Journal of mathematical neuroscience · 2019Article
- Large Deviations Properties of Maximum Entropy Markov Chains from Spike Trains.Entropy (Basel, Switzerland) · 2018Article
- Spike timing precision of neuronal circuits.Journal of computational neuroscience · 2018Article
- Article
- Retinal Circuitry Balances Contrast Tuning of Excitation and Inhibition to Enable Reliable Computation of Direction Selectivity.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2016Article
- Channel based generating function approach to the stochastic Hodgkin-Huxley neuronal system.Scientific reports · 2016Article
- Reliability of signal transmission in stochastic nerve axon equations.Journal of computational neuroscience · 2016Article
- Article
- A temperature rise reduces trial-to-trial variability of locust auditory neuron responses.Journal of neurophysiology · 2015Article
- On the firing rate dependency of the phase response curve of rat Purkinje neurons in vitro.PLoS computational biology · 2015Article
- Modeling spontaneous activity across an excitable epithelium: Support for a coordination scenario of early neural evolution.Frontiers in computational neuroscience · 2015Article
- Diffusion approximation-based simulation of stochastic ion channels: which method to use?Frontiers in computational neuroscience · 2014Article
- Systematic analysis of the contributions of stochastic voltage gated channels to neuronal noise.Frontiers in computational neuroscience · 2014Article
- Modulatory effects of inhibition on persistent activity in a cortical microcircuit model.Frontiers in neural circuits · 2014Article
- The ISI distribution of the stochastic Hodgkin-Huxley neuron.Frontiers in computational neuroscience · 2014Article
- Volterra dendritic stimulus processors and biophysical spike generators with intrinsic noise sources.Frontiers in computational neuroscience · 2014Article
- Modeling and simulation of ion channels.Chemical reviews · 2012Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Stochastic channel gating is the major source of intrinsic neuronal noise whose functional consequences at the microcircuit- and network-levels have been only partly explored. A systematic study of this channel noise in large ensembles of biophysically detailed model neurons calls for the availability of fast numerical methods. In fact, exact techniques employ the microscopic simulation of the random opening and closing of individual ion channels, usually based on Markov models, whose computational loads are prohibitive for next generation massive computer models of the brain. In this work, we operatively define a procedure for translating any Markov model describing voltage- or ligand-gated membrane ion-conductances into an effective stochastic version, whose computer simulation is efficient, without compromising accuracy. Our approximation is based on an improved Langevin-like approach, which employs stochastic differential equations and no Montecarlo methods. As opposed to an earlier proposal recently debated in the literature, our approximation reproduces accurately the statistical properties of the exact microscopic simulations, under a variety of conditions, from spontaneous to evoked response features. In addition, our method is not restricted to the Hodgkin-Huxley sodium and potassium currents and is general for a variety of voltage- and ligand-gated ion currents. As a by-product, the analysis of the properties emerging in exact Markov schemes by standard probability calculus enables us for the first time to analytically identify the sources of inaccuracy of the previous proposal, while providing solid ground for its modification and improvement we present here.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.