Evaluating two-step PCA of ERP data with Geomin, Infomax, Oblimin, Promax, and Varimax rotations

Joseph Dien

Research output: Contribution to journalArticle


Principal components analysis (PCA) can facilitate analysis of event-related potential (ERP) components. Geomin, Oblimin, Varimax, Promax, and Infomax (independent components analysis) were compared using a simulated data set. Kappa settings for Oblimin and Promax were also systematically compared. Finally, the rotations were also analyzed in a two-step PCA procedure, including a contrast between spatiotemporal and temporospatial procedures. Promax was found to give the best overall results for temporal PCA, and Infomax was found to give the best overall results for spatial PCA. The current practice of kappa values of 3 or 4 for Promax and 0 for Oblimin was supported. Source analysis was meaningfully improved by temporal Promax PCA over the conventional windowed difference wave approach (from a median 32.9 mm error to 6.7 mm). It was also found that temporospatial PCA produced modestly improved results over spatiotemporal PCA.

Original languageEnglish (US)
Pages (from-to)170-183
Number of pages14
Issue number1
StatePublished - Jan 2010



  • Event-related potentials
  • Independent components analysis
  • Principal components analysis

ASJC Scopus subject areas

  • Neuroscience(all)
  • Neuropsychology and Physiological Psychology
  • Experimental and Cognitive Psychology
  • Neurology
  • Endocrine and Autonomic Systems
  • Developmental Neuroscience
  • Cognitive Neuroscience
  • Biological Psychiatry

Cite this