Evidence map›Paper›PMID 25360105›Full record

ArticleFrontiers in computational neuroscience2014

Systematic analysis of the contributions of stochastic voltage gated channels to neuronal noise.

Cian O'Donnell, Mark C W van Rossum

Abstract read
In one paragraph

Article in Frontiers in computational neuroscience, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed.

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  12. Sparse bursts optimize information transmission in a multiplexed neural code.Proceedings of the National Academy of Sciences of the United States of America · 2018
    Article
  13. Review
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  15. Methodology of Recurrent Laguerre-Volterra Network for Modeling Nonlinear Dynamic Systems.IEEE transactions on neural networks and learning systems · 2017
    Article
  16. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Cian O'DonnellComputational Neurobiology Laboratory, Salk Institute for Biological Studies La Jolla, CA, USA ; School of Informatics, Institute for Adaptive and Neural Computation, University of Edinburgh Edinburgh, UK.
Mark C W van RossumSchool of Informatics, Institute for Adaptive and Neural Computation, University of Edinburgh Edinburgh, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

channel noiseHodgkin–Huxleysimulationspontaneous firingvoltage-gated ion channels

Identifiers

PMID25360105
PMCPMC4199219

What OpenQuestion holds

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Registered trials

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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.