Bring a map when exploring the ERP data processing multiverse: A commentary on Clayson et al. 2021.
EEG
ERPs
Electroencephalography
Error positivity
Error-related negativity
Event-related potentials
Multiverse analyses
Journal
NeuroImage
ISSN: 1095-9572
Titre abrégé: Neuroimage
Pays: United States
ID NLM: 9215515
Informations de publication
Date de publication:
01 10 2022
01 10 2022
Historique:
received:
03
04
2022
revised:
30
05
2022
accepted:
01
07
2022
pubmed:
7
7
2022
medline:
20
7
2022
entrez:
6
7
2022
Statut:
ppublish
Résumé
Clayson et al. (2021) describe an innovative multiverse analysis to evaluate effects of data processing choices on event-related potential (ERP) measures. Based on their results, they provide data processing recommendations for studies measuring the error-related negativity and error positivity components. We argue that, although their data-driven approach is useful for identifying how data processing choices influence ERP results, it is not sufficient for devising optimal data processing pipelines. As an example, we focus on the inappropriate use of pre-response ERP baselines in their analyses, which leads to biased error positivity amplitude measures. Results of multiverse analyses should be supplemented with further investigation into why differences in ERP results occur across data processing choices before devising general recommendations.
Identifiants
pubmed: 35792288
pii: S1053-8119(22)00560-2
doi: 10.1016/j.neuroimage.2022.119443
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Comment
Langues
eng
Sous-ensembles de citation
IM
Pagination
119443Commentaires et corrections
Type : CommentOn
Informations de copyright
Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.