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Efficient parameter calibration and real-time simulation of large-scale spiking neural networks with GeNN and NEST

Overview of attention for article published in Frontiers in Neuroinformatics, February 2023
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

twitter
6 X users

Citations

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2 Dimensions

Readers on

mendeley
4 Mendeley
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Title
Efficient parameter calibration and real-time simulation of large-scale spiking neural networks with GeNN and NEST
Published in
Frontiers in Neuroinformatics, February 2023
DOI 10.3389/fninf.2023.941696
Pubmed ID
Authors

Felix Johannes Schmitt, Vahid Rostami, Martin Paul Nawrot

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 1 25%
Unknown 3 75%
Readers by discipline Count As %
Neuroscience 1 25%
Unknown 3 75%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 28 March 2023.
All research outputs
#6,948,528
of 23,485,296 outputs
Outputs from Frontiers in Neuroinformatics
#328
of 772 outputs
Outputs of similar age
#115,681
of 420,625 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#4
of 21 outputs
Altmetric has tracked 23,485,296 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 772 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.1. This one has gotten more attention than average, scoring higher than 57% 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 420,625 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 21 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.