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Detect high component correlation with eye channels

Source: R/ar_for_ica.R
ar_eogcor.Rd

Checks the correlation between individual components of an eeg_ICA decomposition and the electrooculogram channels of an eeg_epochs dataset.

Usage

ar_eogcor(decomp, data, ...)

# S3 method for class 'eeg_ICA'
ar_eogcor(
  decomp,
  data,
  HEOG,
  VEOG,
  threshold = NULL,
  plot = TRUE,
  bipolarize = TRUE,
  method = c("pearson", "kendall", "spearman"),
  verbose = TRUE,
  ...
)

Arguments

decomp

An eeg_ica object

data

The original eeg_epochs object from which this decomposition was derived

...

Other parameters

HEOG

Horizontal eye channels

VEOG

Vertical eye channels

threshold

Threshold for correlation (r). Defaults to NULL, automatically determining a threshold.

plot

Plot correlation coefficient for all components

bipolarize

Bipolarize the HEOG and VEOG channels?

method

Correlation method. Defaults to Pearson.

verbose

Print informative messages. Defaults to TRUE.

Value

A character vector of component names that break the threshold.

Methods (by class)

  • ar_eogcor(eeg_ICA): Method for eeg_ICA objects.

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