| POP_RUNICA | Run an ICA decomposition of an EEG dataset using runica, binica, or another ICA or other linear decomposition. |
| Usage: | >> OUT_EEG = pop_runica( EEG ); % pops-up a data entry window >> OUT_EEG = pop_runica( EEG, 'key', 'val' ); % no pop_up |
| Graphic interface: | |
"ICA algorithm to use" |
[edit box] The ICA algorithm to use for ICA decomposition. Command line equivalent: 'icatype' |
"Commandline options" |
[edit box] Command line options to forward to the ICA algorithm. Command line equivalent: 'options' |
| Inputs: | |
EEG |
input EEG dataset or array of datasets |
| Optional inputs: | |
'icatype' |
['runica'|'binica'|'jader'|'fastica'] ICA algorithm to use for the ICA decomposition. The nature of any differences in the results of these algorithms have not been well characterized. {default: binica, if found, else runica} |
'dataset' |
[integer array] dataset index or indices. |
'chanind' |
[integer array] subset of channel indices for running the ICA decomposition. |
'concatenate' |
['on'|'off'] 'on' concatenate all input datasets (assuming there are several). 'off' run ICA independently on each dataset. Default is 'on'. |
'key','val' |
ICA algorithm options (see ICA routine help messages). |
| Note: | 1) Infomax (runica, binica) is the ICA algorithm we use most. It is based on Tony Bell's infomax algorithm as implemented for automated use by Scott Makeig et al. using the natural gradient of Amari et al. It can also extract sub-Gaussian sources using the (recommended) 'extended' option of Lee and Girolami. Function runica is the all-Matlab version; function binica calls the (1.5x faster) binary version (a separate download) translated into C from runica by Sigurd Enghoff. 2) jader calls the JADE algorithm of Jean-Francois Cardoso. This is included in the EEGLAB toolbox by his permission. See >> help jader 3) To run fastica(), download the fastICA toolbox from its website, http://www.cis.hut.fi/projects/ica/fastica/, and make it available in your Matlab path. According to its authors, default parameters are not optimal: Try args 'approach', 'sym' to estimate components in parallel. |
| Outputs: | |
OUT_EEG |
The input EEGLAB dataset with new fields icaweights, icasphere and icachansind (channel indices). |
| Author: | Arnaud Delorme, CNL / Salk Institute, 2001 |
| See also: | runica, binica, jader, fastica() |