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Bonsai: an event-based framework for processing and controlling data streams

Overview of attention for article published in Frontiers in Neuroinformatics, April 2015
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#23 of 828)
  • High Attention Score compared to outputs of the same age (94th percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
23 X users
patent
9 patents
facebook
2 Facebook pages

Citations

dimensions_citation
424 Dimensions

Readers on

mendeley
447 Mendeley
citeulike
1 CiteULike
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Title
Bonsai: an event-based framework for processing and controlling data streams
Published in
Frontiers in Neuroinformatics, April 2015
DOI 10.3389/fninf.2015.00007
Pubmed ID
Authors

Gonçalo Lopes, Niccolò Bonacchi, João Frazão, Joana P. Neto, Bassam V. Atallah, Sofia Soares, Luís Moreira, Sara Matias, Pavel M. Itskov, Patrícia A. Correia, Roberto E. Medina, Lorenza Calcaterra, Elena Dreosti, Joseph J. Paton, Adam R. Kampff

Abstract

The design of modern scientific experiments requires the control and monitoring of many different data streams. However, the serial execution of programming instructions in a computer makes it a challenge to develop software that can deal with the asynchronous, parallel nature of scientific data. Here we present Bonsai, a modular, high-performance, open-source visual programming framework for the acquisition and online processing of data streams. We describe Bonsai's core principles and architecture and demonstrate how it allows for the rapid and flexible prototyping of integrated experimental designs in neuroscience. We specifically highlight some applications that require the combination of many different hardware and software components, including video tracking of behavior, electrophysiology and closed-loop control of stimulation.

X Demographics

X Demographics

The data shown below were collected from the profiles of 23 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 447 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Portugal 7 2%
United States 4 <1%
United Kingdom 3 <1%
Brazil 1 <1%
France 1 <1%
Norway 1 <1%
India 1 <1%
Unknown 429 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 94 21%
Researcher 86 19%
Student > Bachelor 62 14%
Student > Master 59 13%
Student > Doctoral Student 20 4%
Other 53 12%
Unknown 73 16%
Readers by discipline Count As %
Neuroscience 170 38%
Agricultural and Biological Sciences 108 24%
Engineering 20 4%
Medicine and Dentistry 17 4%
Psychology 13 3%
Other 40 9%
Unknown 79 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 36. 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 15 August 2023.
All research outputs
#1,118,805
of 25,382,360 outputs
Outputs from Frontiers in Neuroinformatics
#23
of 828 outputs
Outputs of similar age
#14,058
of 278,294 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#4
of 12 outputs
Altmetric has tracked 25,382,360 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 828 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one has done particularly well, scoring higher than 97% 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 278,294 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.