A Student's Guide to Randomization Statistics for Multichannel Event-Related Potentials Using Ragu

In this paper, we present a multivariate approach to analyze multi-channel event-related potential (ERP) data using randomization statistics. The MATLAB-based open source toolbox (Ragu) provides, among other methods, a test for topographic consistency, a topographic analysis of variance, t-mapping a...

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Vydáno v:	Frontiers in neuroscience Ročník 12; s. 355
Hlavní autoři:	Habermann, Marie, Weusmann, Dorothea, Stein, Maria, Koenig, Thomas
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Switzerland Frontiers Research Foundation 19.06.2018 Frontiers Media S.A
Témata:	Brain research Copyright EEG Electromagnetism ERP Event-related potentials Exchange of persons programs Foreign languages Grammatical subject Hypotheses Language Mapping Medical imaging microstates N400 Neuroscience Ragu randomization statistics Second language learning Semantics Small states Statistical analysis Statistics Topography Variance analysis Switzerland ERP N400 Ragu microstates EEG randomization statistics
ISSN:	1662-453X, 1662-4548, 1662-453X
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Abstract	In this paper, we present a multivariate approach to analyze multi-channel event-related potential (ERP) data using randomization statistics. The MATLAB-based open source toolbox (Ragu) provides, among other methods, a test for topographic consistency, a topographic analysis of variance, t-mapping and microstate analyses. Up to two within-subject factors and one between-subject factor, each with an open number of levels, can be defined and analyzed in Ragu. Ragu analyses include all sensor signals and no a-priori models have to be applied during the analyses. Additionally, periods of significant effects can be controlled for multiple testing using global overall statistics over time. Here, we introduce the different alternatives to apply Ragu, based on a step by step analysis of an example study. This example study examined the neural activity in response to semantic unexpected sentence endings in exchange students at the beginning of their stay and after staying in a foreign-language country for 5 months.
AbstractList	In this paper, we present a multivariate approach to analyze multi-channel event-related potential (ERP) data using randomization statistics1. The MATLAB-based open source toolbox Randomization Graphical User interface (Ragu) provides, among other methods, a test for topographic consistency, a topographic analysis of variance, t-mapping and microstate analyses. Up to two within-subject factors and one between-subject factor, each with an open number of levels, can be defined and analyzed in Ragu. Ragu analyses include all sensor signals and no a-priori models have to be applied during the analyses. Additionally, periods of significant effects can be controlled for multiple testing using global overall statistics over time. Here, we introduce the different alternatives to apply Ragu, based on a step by step analysis of an example study. This example study examined the neural activity in response to semantic unexpected sentence endings in exchange students at the beginning of their stay and after staying in a foreign-language country for 5 months. In this paper, we present a multivariate approach to analyze multi-channel event-related potential (ERP) data using randomization statistics. The MATLAB-based open source toolbox (Ragu) provides, among other methods, a test for topographic consistency, a topographic analysis of variance, t-mapping and microstate analyses. Up to two within-subject factors and one between-subject factor, each with an open number of levels, can be defined and analyzed in Ragu. Ragu analyses include all sensor signals and no a-priori models have to be applied during the analyses. Additionally, periods of significant effects can be controlled for multiple testing using global overall statistics over time. Here, we introduce the different alternatives to apply Ragu, based on a step by step analysis of an example study. This example study examined the neural activity in response to semantic unexpected sentence endings in exchange students at the beginning of their stay and after staying in a foreign-language country for 5 months. In this paper we present an multivariate approach to analyze multi-channel ERP data using randomization statistics \footnotemark[1]. The MATLAB-based open source toolbox \textit{Randomization Graphical User interface} (Ragu) provides among other things a test for topographic consistency, topographic analysis of variance, t-mapping and microstates analysis. Up to two within-subject factors and one between-subject factor can be defined and analyzed in Ragu. Ragu includes all sensor signals and no a-priori models have to be applied. Also, periods of significant effects can be controlled for multiple testing using global overall statistics over time. Here we introduce the different options of Ragu by a step by step analysis of data from an example study examining the neural reaction of semantic unexpected sentence endings in exchange students at the beginning and after 5 months of a stay in a foreign-language country. In this paper, we present a multivariate approach to analyze multi-channel event-related potential (ERP) data using randomization statistics. The MATLAB-based open source toolbox Randomization Graphical User interface (Ragu) provides, among other methods, a test for topographic consistency, a topographic analysis of variance, t-mapping and microstate analyses. Up to two within-subject factors and one between-subject factor, each with an open number of levels, can be defined and analyzed in Ragu. Ragu analyses include all sensor signals and no a-priori models have to be applied during the analyses. Additionally, periods of significant effects can be controlled for multiple testing using global overall statistics over time. Here, we introduce the different alternatives to apply Ragu, based on a step by step analysis of an example study. This example study examined the neural activity in response to semantic unexpected sentence endings in exchange students at the beginning of their stay and after staying in a foreign-language country for 5 months.In this paper, we present a multivariate approach to analyze multi-channel event-related potential (ERP) data using randomization statistics. The MATLAB-based open source toolbox Randomization Graphical User interface (Ragu) provides, among other methods, a test for topographic consistency, a topographic analysis of variance, t-mapping and microstate analyses. Up to two within-subject factors and one between-subject factor, each with an open number of levels, can be defined and analyzed in Ragu. Ragu analyses include all sensor signals and no a-priori models have to be applied during the analyses. Additionally, periods of significant effects can be controlled for multiple testing using global overall statistics over time. Here, we introduce the different alternatives to apply Ragu, based on a step by step analysis of an example study. This example study examined the neural activity in response to semantic unexpected sentence endings in exchange students at the beginning of their stay and after staying in a foreign-language country for 5 months.
Author	Weusmann, Dorothea Stein, Maria Habermann, Marie Koenig, Thomas
AuthorAffiliation	2 Department of Clinical Psychology and Psychotherapy, University of Bern , Bern , Switzerland 1 Translational Research Center, Department of Psychiatric Neurophysiology, University Hospital of Psychiatry Bern, University of Bern , Bern , Switzerland
AuthorAffiliation_xml	– name: 1 Translational Research Center, Department of Psychiatric Neurophysiology, University Hospital of Psychiatry Bern, University of Bern , Bern , Switzerland – name: 2 Department of Clinical Psychology and Psychotherapy, University of Bern , Bern , Switzerland
Author_xml	– sequence: 1 givenname: Marie surname: Habermann fullname: Habermann, Marie – sequence: 2 givenname: Dorothea surname: Weusmann fullname: Weusmann, Dorothea – sequence: 3 givenname: Maria surname: Stein fullname: Stein, Maria – sequence: 4 givenname: Thomas surname: Koenig fullname: Koenig, Thomas
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/29973861$$D View this record in MEDLINE/PubMed
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Keywords	ERP N400 Ragu microstates EEG randomization statistics
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Snippet	In this paper, we present a multivariate approach to analyze multi-channel event-related potential (ERP) data using randomization statistics. The MATLAB-based... In this paper we present an multivariate approach to analyze multi-channel ERP data using randomization statistics \footnotemark[1]. The MATLAB-based open... In this paper, we present a multivariate approach to analyze multi-channel event-related potential (ERP) data using randomization statistics1. The MATLAB-based...
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StartPage	355
SubjectTerms	Brain research Copyright EEG Electromagnetism ERP Event-related potentials Exchange of persons programs Foreign languages Grammatical subject Hypotheses Language Mapping Medical imaging microstates N400 Neuroscience Ragu randomization statistics Second language learning Semantics Small states Statistical analysis Statistics Topography Variance analysis
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Title	A Student's Guide to Randomization Statistics for Multichannel Event-Related Potentials Using Ragu
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Volume	12
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