Applying principal components analysis to event-related potentials: A tutorial

Joseph Dien

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish (US)
Pages (from-to)497-517
Number of pages21
JournalDevelopmental Neuropsychology
Volume37
Issue number6
DOIs
StatePublished - Aug 1 2012

ASJC Scopus subject areas

  • Neuropsychology and Physiological Psychology
  • Developmental and Educational Psychology

Fingerprint Dive into the research topics of 'Applying principal components analysis to event-related potentials: A tutorial'. Together they form a unique fingerprint.

  • Cite this