ar_eogcor: Detect high component correlation with eye channels

In craddm/eegUtils: Utilities for Electroencephalographic (EEG) Analysis

Detect high component correlation with eye channels

Description

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.

Author(s)

Matt Craddock, [e-mail]

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

craddm/eegUtils documentation built on March 1, 2025, 3:23 p.m.