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Detect high trial focality of ICA components

Source: R/ar_for_ica.R
ar_trialfoc.Rd

Detect components that load heavily on a small number of trials. Looks for components that have one particular trial that has a particularly high z-score.

Usage

ar_trialfoc(data, plot = TRUE, threshold = NULL, verbose = TRUE)

Arguments

data

eeg_ICA object

plot

Produce plot showing max z-scores and threshold for all ICA components.

threshold

Specify a threshold (z-score) for high focality. NULL estimates the threshold automatically.

verbose

Print informative messages.

Value

A character vector of component names that break the threshold.

References

Chaumon, M., Bishop, D.V., Busch, N.A. (2015). A practical guide to the selection of independent components of the electroencephalogram for artifact correction. J Neurosci Methods. Jul 30;250:47-63. doi: 10.1016/j.jneumeth.2015.02.025

Author

Matt Craddock matt@mattcraddock.com

Examples

demo_sobi <- run_ICA(demo_epochs, pca = 10)
#> Reducing data to 10 dimensions using PCA.
#> Running SOBI ICA.
ar_trialfoc(demo_sobi)
#> Estimated trial focality threshold (z): 6.41

#> Components with high trial focality: Comp009 
#> [1] "Comp009"