Low autocorrelation can be a sign of a poor quality channel or component. Often these are noisy, poor contact, or heavily contaminated with muscle noise. Low autocorrelation at a lag of 20ms is often associated with muscle noise.
ar_acf(data, ...)
# S3 method for class 'eeg_ICA'
ar_acf(data, ms = 20, plot = TRUE, verbose = TRUE, threshold = NULL, ...)Arguments
- data
eeg_ICAobject- ...
additional parameters
- ms
Time lag to check ACF, in milliseconds. Defaults to 20 ms.
- plot
Produce plot showing ACF and threshold for all EEG components.
- verbose
Print informative messages. Defaults to TRUE.
- threshold
Specify a threshold for low ACF. NULL estimates the threshold automatically.
Value
A character vector of component names that break the threshold.
Methods (by class)
ar_acf(eeg_ICA): Autocorrelation checker foreeg_ICAobjects
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)
#> Reducing data to 10 dimensions using PCA.
#> Running SOBI ICA.
#> Setting tolerance to 0.0011
ar_acf(demo_sobi)
#> Estimating autocorrelation at 20ms lag.
#> Estimated ACF threshold: -0.16
#> Subthreshold components:
#> character(0)