Applying principal components analysis to event-related potentials: a tutorial.
Principal components analysis (PCA) has attracted increasing interest as a tool for facilitating analysis of high-density event-related potential (ERP) data. While every researcher is exposed to this statistical procedure in graduate school, its complexities are rarely covered in depth and hence researchers are often not conversant with its subtleties. Furthermore, application to ERP datasets involves unique aspects that would not be covered in a general statistics course. This tutorial seeks to provide guidance on the decisions involved in applying PCA to ERPs and their consequences, using the ERP PCA Toolkit to illustrate the analysis process on a novelty oddball dataset.
Center for Advanced Study of Language, University of Maryland, College Park, Maryland 20742-0025, USA. jdien07@mac.com
Joseph
J
Dien
D016477:Artifacts; D001931:Brain Mapping / Q000379:methods; D004569:Electroencephalography; D005071:Evoked Potentials; D006801:Humans; D025341:Principal Component Analysis / Q000379:methods*