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Automated in vivo patch-clamp evaluation of extracellular multielectrode array spike recording capability

Overview of attention for article published in Journal of Neurophysiology, November 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

twitter
51 tweeters
facebook
2 Facebook pages

Citations

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9 Dimensions

Readers on

mendeley
36 Mendeley
Title
Automated in vivo patch-clamp evaluation of extracellular multielectrode array spike recording capability
Published in
Journal of Neurophysiology, November 2018
DOI 10.1152/jn.00650.2017
Pubmed ID
Authors

Brian D. Allen, Caroline Moore-Kochlacs, Jacob G. Bernstein, Justin P. Kinney, Jorg Scholvin, Luís F. Seoane, Chris Chronopoulos, Charlie Lamantia, Suhasa B. Kodandaramaiah, Max Tegmark, Edward S. Boyden

Abstract

Much innovation is currently aimed at improving the number, density, and geometry of electrodes on extracellular multielectrode arrays for in vivo recording of neural activity in the mammalian brain. To choose a multielectrode array configuration for a given neuroscience purpose, or to reveal design principles of future multielectrode arrays, it would be useful to have a systematic way of evaluating the spike recording capability of such arrays. We here describe an automated system that performs robotic patch clamp recording of a neuron being simultaneously recorded via an extracellular multielectrode array. By recording a patch clamp dataset from a neuron while acquiring extracellular recordings from the same neuron, we can evaluate how well the extracellular multielectrode array captures the spiking information from that neuron. To demonstrate the utility of our system, we show that it can provide data from the mammalian cortex to evaluate how the spike sorting performance of a close-packed extracellular multielectrode array is affected by bursting, which alters the shape and amplitude of spikes in a train. We also introduce an algorithmic framework to help evaluate how the number of electrodes in a multielectrode array affects spike sorting, examining how adding more electrodes yields data that can be spike sorted more easily. Our automated methodology may thus help with the evaluation of new electrode designs and configurations, providing empirical guidance on the kinds of electrodes that will be optimal for different brain regions, cell types, and species, for improving the accuracy of spike sorting.

Twitter Demographics

The data shown below were collected from the profiles of 51 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 36 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 25%
Student > Ph. D. Student 7 19%
Student > Bachelor 4 11%
Professor 3 8%
Student > Postgraduate 2 6%
Other 6 17%
Unknown 5 14%
Readers by discipline Count As %
Engineering 10 28%
Neuroscience 8 22%
Agricultural and Biological Sciences 5 14%
Medicine and Dentistry 3 8%
Physics and Astronomy 2 6%
Other 1 3%
Unknown 7 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 31. 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 06 December 2018.
All research outputs
#700,329
of 15,916,297 outputs
Outputs from Journal of Neurophysiology
#83
of 6,031 outputs
Outputs of similar age
#21,914
of 276,765 outputs
Outputs of similar age from Journal of Neurophysiology
#4
of 110 outputs
Altmetric has tracked 15,916,297 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 6,031 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done particularly well, scoring higher than 98% 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 276,765 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 92% of its contemporaries.
We're also able to compare this research output to 110 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.