Description

Computes mixing and unmixing matrices using Independant Component Analysis method.
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.

Features

• This plugin can be run using the command line
• Can use the current montage instead of raw channels.
• Can filter signals before computing.
• Can decimate the number of samples to speed up computation (not recommended)
• The user can specify artifacted sections to reject.
• The user can specify data chunks to use (and not the entire data file).

Parameters

Data Input section:

The default is to compute on raw channels (channels present in file avoiding any montage).
Use current Montage option allows computing on current montage.

Modality option is usefull only for simulateneous recordings (EEG and MEG for example)

Bad channels are ignored by default.

Data Input Section

This is where you can select the data chunks to avoid and/or use.

Output

Select the number of independ components to extract.
Click the All Component to set if to the maximum possible value. 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