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Neural Coding With Bursts—Current State and Future Perspectives

Overview of attention for article published in Frontiers in Computational Neuroscience, July 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

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17 X users

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231 Mendeley
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Title
Neural Coding With Bursts—Current State and Future Perspectives
Published in
Frontiers in Computational Neuroscience, July 2018
DOI 10.3389/fncom.2018.00048
Pubmed ID
Authors

Fleur Zeldenrust, Wytse J. Wadman, Bernhard Englitz

Abstract

Neuronal action potentials or spikes provide a long-range, noise-resistant means of communication between neurons. As point processes single spikes contain little information in themselves, i.e., outside the context of spikes from other neurons. Moreover, they may fail to cross a synapse. A burst, which consists of a short, high frequency train of spikes, will more reliably cross a synapse, increasing the likelihood of eliciting a postsynaptic spike, depending on the specific short-term plasticity at that synapse. Both the number and the temporal pattern of spikes in a burst provide a coding space that lies within the temporal integration realm of single neurons. Bursts have been observed in many species, including the non-mammalian, and in brain regions that range from subcortical to cortical. Despite their widespread presence and potential relevance, the uncertainties of how to classify bursts seems to have limited the research into the coding possibilities for bursts. The present series of research articles provides new insights into the relevance and interpretation of bursts across different neural circuits, and new methods for their analysis. Here, we provide a succinct introduction to the history of burst coding and an overview of recent work on this topic.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 231 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 231 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 45 19%
Researcher 34 15%
Student > Master 33 14%
Student > Bachelor 30 13%
Student > Postgraduate 9 4%
Other 27 12%
Unknown 53 23%
Readers by discipline Count As %
Neuroscience 79 34%
Engineering 28 12%
Agricultural and Biological Sciences 14 6%
Biochemistry, Genetics and Molecular Biology 9 4%
Computer Science 9 4%
Other 31 13%
Unknown 61 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 July 2021.
All research outputs
#3,770,156
of 26,332,460 outputs
Outputs from Frontiers in Computational Neuroscience
#168
of 1,490 outputs
Outputs of similar age
#68,722
of 344,368 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#5
of 34 outputs
Altmetric has tracked 26,332,460 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,490 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.1. This one has done well, scoring higher than 88% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 344,368 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 34 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.