ar_trialfoc: Detect high trial focality of ICA components

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

Detect high trial focality of ICA components

Description

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.

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

Examples

demo_sobi <- run_ICA(demo_epochs, pca = 10)
ar_trialfoc(demo_sobi)

craddm/eegUtils documentation built on March 24, 2022, 9:17 a.m.