Detect high channel focality of ICA components

Detect components that load heavily on a single channel. Looks for components that have one particular channel that has a particularly high z-score.

ar_chanfoc(
  data,
  plot = TRUE,
  threshold = NULL,
  verbose = TRUE,
  measure = "max",
  ...
)

Arguments

data

An eeg_ICA object

plot

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

threshold

Specify a threshold for high focality. NULL estimates the threshold automatically.

verbose

Print informative messages.

measure

Use maximum "max" or "kurtosis".

...

additional parameters

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.
#> Setting tolerance to 0.0011
ar_chanfoc(demo_sobi)
#> Estimated threshold: 2.95
#> Components with high channel focality:  

#> character(0)