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

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...

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Autores principales: Krigolson, Olave E., Williams, Chad C., Norton, Angela, Hassall, Cameron D., Colino, Francisco L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5344886/
https://www.ncbi.nlm.nih.gov/pubmed/28344546
http://dx.doi.org/10.3389/fnins.2017.00109
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author Krigolson, Olave E.
Williams, Chad C.
Norton, Angela
Hassall, Cameron D.
Colino, Francisco L.
author_facet Krigolson, Olave E.
Williams, Chad C.
Norton, Angela
Hassall, Cameron D.
Colino, Francisco L.
author_sort Krigolson, Olave E.
collection PubMed
description 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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spelling pubmed-53448862017-03-24 Choosing MUSE: Validation of a Low-Cost, Portable EEG System for ERP Research Krigolson, Olave E. Williams, Chad C. Norton, Angela Hassall, Cameron D. Colino, Francisco L. Front Neurosci Neuroscience 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. Frontiers Media S.A. 2017-03-10 /pmc/articles/PMC5344886/ /pubmed/28344546 http://dx.doi.org/10.3389/fnins.2017.00109 Text en Copyright © 2017 Krigolson, Williams, Norton, Hassall and Colino. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Krigolson, Olave E.
Williams, Chad C.
Norton, Angela
Hassall, Cameron D.
Colino, Francisco L.
Choosing MUSE: Validation of a Low-Cost, Portable EEG System for ERP Research
title Choosing MUSE: Validation of a Low-Cost, Portable EEG System for ERP Research
title_full Choosing MUSE: Validation of a Low-Cost, Portable EEG System for ERP Research
title_fullStr Choosing MUSE: Validation of a Low-Cost, Portable EEG System for ERP Research
title_full_unstemmed Choosing MUSE: Validation of a Low-Cost, Portable EEG System for ERP Research
title_short Choosing MUSE: Validation of a Low-Cost, Portable EEG System for ERP Research
title_sort choosing muse: validation of a low-cost, portable eeg system for erp research
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5344886/
https://www.ncbi.nlm.nih.gov/pubmed/28344546
http://dx.doi.org/10.3389/fnins.2017.00109
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