apply_ica: Recreate channel timecourses from ICA decompositions.

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

Recreate channel timecourses from ICA decompositions.

Description

This function can be used to either recreate "mixed" (i.e. channel level) timecourses from an ICA decomposition, or to apply a set of ICA weights to a given dataset for the purpose of removing specific ICA components from that dataset.

Usage

apply_ica(data, ...)

## S3 method for class 'eeg_ICA'
apply_ica(data, comps = NULL, ...)

## S3 method for class 'eeg_epochs'
apply_ica(data, decomp, comps, ...)

Arguments

data	An eeg_ICA or eeg_epochs object.
...	Other parameters.
comps	Components to remove.
decomp	An eeg_ICA object.

Methods (by class)

• eeg_ICA: From given eeg_ICA object, recreate channel timecourses.

• eeg_epochs: Combine a specific set of ICA weights with any eeg_epochs object.

Author(s)

Matt Craddock [e-mail]

Examples

test_ica <- run_ICA(demo_epochs, pca = 10)
plot_butterfly(demo_epochs)
# Reconstruct the original data from the ICA decomposition.
# Note that the ICA process subtracts the mean from each epoch,
# so the reconstructed plot may look slightly different to the original.
plot_butterfly(apply_ica(test_ica))
# Remove component 2 from the data
plot_butterfly(apply_ica(demo_epochs, test_ica, comps = 2))

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