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Choosing MUSE: Validation of a Low-Cost, Portable EEG System for ERP Research

Overview of attention for article published in Frontiers in Neuroscience, March 2017
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

news
4 news outlets
twitter
22 X users
wikipedia
1 Wikipedia page
q&a
1 Q&A thread
video
1 YouTube creator

Citations

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252 Dimensions

Readers on

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626 Mendeley
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Title
Choosing MUSE: Validation of a Low-Cost, Portable EEG System for ERP Research
Published in
Frontiers in Neuroscience, March 2017
DOI 10.3389/fnins.2017.00109
Pubmed ID
Authors

Olave E. Krigolson, Chad C. Williams, Angela Norton, Cameron D. Hassall, Francisco L. Colino

Abstract

In recent years there has been an increase in the number of portable low-cost electroencephalographic (EEG) systems available to researchers. However, to date the validation of the use of low-cost EEG systems has focused on continuous recording of EEG data and/or the replication of large system EEG setups reliant on event-markers to afford examination of event-related brain potentials (ERP). Here, we demonstrate that it is possible to conduct ERP research without being reliant on event markers using a portable MUSE EEG system and a single computer. Specifically, we report the results of two experiments using data collected with the MUSE EEG system-one using the well-known visual oddball paradigm and the other using a standard reward-learning task. Our results demonstrate that we could observe and quantify the N200 and P300 ERP components in the visual oddball task and the reward positivity (the mirror opposite component to the feedback-related negativity) in the reward-learning task. Specifically, single sample t-tests of component existence (all p's < 0.05), computation of Bayesian credible intervals, and 95% confidence intervals all statistically verified the existence of the N200, P300, and reward positivity in all analyses. We provide with this research paper an open source website with all the instructions, methods, and software to replicate our findings and to provide researchers with an easy way to use the MUSE EEG system for ERP research. Importantly, our work highlights that with a single computer and a portable EEG system such as the MUSE one can conduct ERP research with ease thus greatly extending the possible use of the ERP methodology to a variety of novel contexts.

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X Demographics

The data shown below were collected from the profiles of 22 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 626 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 <1%
United Kingdom 1 <1%
Unknown 623 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 104 17%
Student > Master 82 13%
Student > Bachelor 81 13%
Researcher 69 11%
Student > Doctoral Student 37 6%
Other 105 17%
Unknown 148 24%
Readers by discipline Count As %
Psychology 95 15%
Engineering 85 14%
Neuroscience 66 11%
Computer Science 54 9%
Medicine and Dentistry 24 4%
Other 116 19%
Unknown 186 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 52. 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 12 August 2023.
All research outputs
#806,043
of 25,382,440 outputs
Outputs from Frontiers in Neuroscience
#340
of 11,542 outputs
Outputs of similar age
#16,712
of 321,209 outputs
Outputs of similar age from Frontiers in Neuroscience
#3
of 213 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,542 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. 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 321,209 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 213 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 98% of its contemporaries.