plugin_ica.md

+# Description
+The ICA plugin will apply differents algorithms to extract independent components from the signals.  
+The default and most used algorithm in EEG/MEG is infomax.   
+Two extras algorithm have been added, CCA and SOBI that seem to work better on EEG signals.
+
+**This plugin can be run using the command line.**   
+
+# Running the process
+![image](uploads/9ad546ff593f3974b9208450b546d4b6/image.png)   
+
+## Select algorithm
+![image](uploads/e5c0821ef27065f2789a9f95b74b6e43/image.png)
+
+Currently only two algorithms are available: infomax and sobi.    
+Note that depending on the selected algorithm the Extra parameters section of the GUI may vary.   
+
+## Filter the data (or not)
+You may apply high pass/low pass filters on data. 
+If the values are set to zeros, a warning message will appear requesting a confirmation that you will process on raw data.   
+The Decimate Data is off by default. Check it on to speed up computation by removing some data points.   
+
+## Select the channels 
+![image](uploads/af3b92d740c92c56bd5b7b4350a9a5e6/image.png)    
+You can process ICA on raw channels present on the current data file OR choose to compute only on channels present in the current Montage.   
+
+If you process SEEG data you can also restrict the computation to a particular SEEG Electrode.   
+
+## Avoid artefacts and/or compute only on some part of the data
+If the current file contains markers, you will see a Data Input Options appears in the GUI:   
+![image](uploads/5f3f236d5493fb6ce5f55b59af24d1eb/image.png)   
+
+You may use the options to avoid marked artefacted data and or restrict the computation on some marked parts of data.  
+
+## Ignore bad channels
+That is the default behavior. If bad channels had been marked previously, they will be ignored during the computation.
+
+## Number of components
+By default the maximum of components will be extracted from the data.  
+You can however reduce the dimensions of the data (using a PCA) to get less components.   
+
+## Output
+If you are currently working on data stored in a BIDS the output MATLAB file will be stored in the derivatives folder of your BIDS.   
+If you are not working with BIDS the output MATLAB file will be generated in the current data file folder.
+The file name is BIDS alike providing useful information just by reading it.
+
+# MATLAB file description
+If you develop your own ICA algorithm in MATLAB, you can create a compatible file to load with AnyWave to see the components time series.   
+To do so you must create a file like the one AnyWave generates.
+
+| variable name | type | description/values |
+| ------ | ------ | ------ |
+| modality | string | MEG, EEG, SEEG |
+| hpf | double | high pass filter used or 0. |
+| lpf | double | low pass filter used or 0. |
+| sr | double | data sampling rate in Hz. |
+| labels | cell array of strings | labels of electrodes  |
+| mixing | matrix (m x ic) | used to reject component(s) and rebuild the signals  |
+| unmixing | matrix (ic x m)  | used to generate components time series |
+
+m = number of channels.   
+ic = number of independent components.  
+
+IMPORTANT: labels must contains the electrodes used to compute. AnyWave will unmix those channels to get the ICA time series.   
+
+**NOTE:** the order of the labels must match the columns of matrix mixing.
+The labels must exit in the data file (the names must match otherwise AnyWave will not be able to compute the time series by unmixing the original signals).    
+Each column of mixing is a component mapping for an electrode. The columns are used to compute components mappings.
+
+
+# [Run ICA from the command line](plugin_ica_cli)