Enhancing reproducibility in developmental EEG research: BIDS, cluster-based permutation tests, and effect sizes

Developmental research using electroencephalography (EEG) offers valuable insights in brain processes early in life, but at the same time, applying this sensitive technique to young children who are often non-compliant and have short attention spans comes with practical limitations. It is thus of pa...

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Autores principales:	Marlene Meyer, Didi Lamers, Ezgi Kayhan, Sabine Hunnius, Robert Oostenveld
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	EEG reproducibility cluster-based permutation test effect size BIDS Neurophysiology and neuropsychology QP351-495
Acceso en línea:	https://doaj.org/article/17e42a216c95473a96bf915e3cd73bd5
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spelling	oai:doaj.org-article:17e42a216c95473a96bf915e3cd73bd52021-11-20T04:58:18ZEnhancing reproducibility in developmental EEG research: BIDS, cluster-based permutation tests, and effect sizes1878-929310.1016/j.dcn.2021.101036https://doaj.org/article/17e42a216c95473a96bf915e3cd73bd52021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1878929321001250https://doaj.org/toc/1878-9293Developmental research using electroencephalography (EEG) offers valuable insights in brain processes early in life, but at the same time, applying this sensitive technique to young children who are often non-compliant and have short attention spans comes with practical limitations. It is thus of particular importance to optimally use the limited resources to advance our understanding of development through reproducible and replicable research practices. Here, we describe methodological approaches that help maximize the reproducibility of developmental EEG research. We discuss how to transform EEG data into the standardized Brain Imaging Data Structure (BIDS) which organizes data according to the FAIR data sharing principles. We provide a tutorial on how to use cluster-based permutation testing to analyze developmental EEG data. This versatile test statistic solves the multiple comparison problem omnipresent in EEG analysis and thereby substantially decreases the risk of reporting false discoveries. Finally, we describe how to quantify effect sizes, in particular of cluster-based permutation results. Reporting effect sizes conveys a finding’s impact and robustness which in turn informs future research. To demonstrate these methodological approaches to data organization, analysis and report, we use a publicly accessible infant EEG dataset and provide a complete copy of the analysis code.Marlene MeyerDidi LamersEzgi KayhanSabine HunniusRobert OostenveldElsevierarticleEEGreproducibilitycluster-based permutation testeffect sizeBIDSNeurophysiology and neuropsychologyQP351-495ENDevelopmental Cognitive Neuroscience, Vol 52, Iss , Pp 101036- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	EEG reproducibility cluster-based permutation test effect size BIDS Neurophysiology and neuropsychology QP351-495
spellingShingle	EEG reproducibility cluster-based permutation test effect size BIDS Neurophysiology and neuropsychology QP351-495 Marlene Meyer Didi Lamers Ezgi Kayhan Sabine Hunnius Robert Oostenveld Enhancing reproducibility in developmental EEG research: BIDS, cluster-based permutation tests, and effect sizes
description	Developmental research using electroencephalography (EEG) offers valuable insights in brain processes early in life, but at the same time, applying this sensitive technique to young children who are often non-compliant and have short attention spans comes with practical limitations. It is thus of particular importance to optimally use the limited resources to advance our understanding of development through reproducible and replicable research practices. Here, we describe methodological approaches that help maximize the reproducibility of developmental EEG research. We discuss how to transform EEG data into the standardized Brain Imaging Data Structure (BIDS) which organizes data according to the FAIR data sharing principles. We provide a tutorial on how to use cluster-based permutation testing to analyze developmental EEG data. This versatile test statistic solves the multiple comparison problem omnipresent in EEG analysis and thereby substantially decreases the risk of reporting false discoveries. Finally, we describe how to quantify effect sizes, in particular of cluster-based permutation results. Reporting effect sizes conveys a finding’s impact and robustness which in turn informs future research. To demonstrate these methodological approaches to data organization, analysis and report, we use a publicly accessible infant EEG dataset and provide a complete copy of the analysis code.
format	article
author	Marlene Meyer Didi Lamers Ezgi Kayhan Sabine Hunnius Robert Oostenveld
author_facet	Marlene Meyer Didi Lamers Ezgi Kayhan Sabine Hunnius Robert Oostenveld
author_sort	Marlene Meyer
title	Enhancing reproducibility in developmental EEG research: BIDS, cluster-based permutation tests, and effect sizes
title_short	Enhancing reproducibility in developmental EEG research: BIDS, cluster-based permutation tests, and effect sizes
title_full	Enhancing reproducibility in developmental EEG research: BIDS, cluster-based permutation tests, and effect sizes
title_fullStr	Enhancing reproducibility in developmental EEG research: BIDS, cluster-based permutation tests, and effect sizes
title_full_unstemmed	Enhancing reproducibility in developmental EEG research: BIDS, cluster-based permutation tests, and effect sizes
title_sort	enhancing reproducibility in developmental eeg research: bids, cluster-based permutation tests, and effect sizes
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/17e42a216c95473a96bf915e3cd73bd5
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Enhancing reproducibility in developmental EEG research: BIDS, cluster-based permutation tests, and effect sizes

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