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- W2017783568 abstract "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." @default.
- W2017783568 created "2016-06-24" @default.
- W2017783568 creator A5050111644 @default.
- W2017783568 date "2010-01-01" @default.
- W2017783568 modified "2023-10-16" @default.
- W2017783568 title "Evaluating two-step PCA of ERP data with Geomin, Infomax, Oblimin, Promax, and Varimax rotations" @default.
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- W2017783568 doi "https://doi.org/10.1111/j.1469-8986.2009.00885.x" @default.
- W2017783568 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/19761521" @default.
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