Evaluating two-step PCA of ERP data with Geomin, Infomax, Oblimin, Promax, and Varimax rotations
Evaluating two-step PCA of ERP data with Geomin, Infomax, Oblimin, Promax, and Varimax rotations
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DOI：
10.1111/j.1469-8986.2009.00885.x
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发表时间：
2010-01-01
期刊：
影响因子：
3.7
通讯作者：
Dien, Joseph
中科院分区：
文献类型：
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作者：
Dien, Joseph
主成分分析（PCA）可以促进事件相关电位（ERP）成分的分析。使用模拟数据集比较Geomin、Oblimin、Varimax、Promax和Infomax（独立成分分析）。还系统地比较了Oblimin和Promax的Kappa设置。最后，还分析了旋转的两步PCA程序，包括时空和时空程序之间的对比。Promax被发现给时间PCA的最佳整体结果，和Infomax被发现给空间PCA的最佳整体结果。支持Promax的kappa值为3或4，Obilmin为0的现行做法。源分析有意义地改善了时间Promax PCA的传统窗口差波的方法（从中位数32.9毫米的误差为6.7毫米）。有人还发现，时空PCA产生适度改善的结果，时空PCA。
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.