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.
ar_trialfoc(data, plot = TRUE, threshold = NULL, verbose = TRUE)Arguments
- data
eeg_ICAobject- 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
Examples
demo_sobi <- run_ICA(demo_epochs, pca = 10)
#> Reducing data to 10 dimensions using PCA.
#> Running SOBI ICA.
#> Setting tolerance to 0.0011
ar_trialfoc(demo_sobi)
#> Estimated trial focality threshold (z): 6.41
#> [1] "Comp009"