[Eeglablist] ICA after PREP pipeline incl channel interpolation

[Alexandra Yvonne Vossen]

Dear all,

I realise this is a popular question but I am really uncertain what happens to my data in my preprocessing pipeline. I am quite new to ICA/PCA decomposition.

First, the raw data are run through the PREP pipeline (in EEGLAB 13.5.4b), including the (spherical) interpolation of noisy channels.

Then after rejection of very noisy epochs I run ICA (for identification of artefact components) with EEG = pop_runica(EEG,'extended',1) %this is somebody else's code that I am re-using. 
(Minor question: At this point I do not baseline correct each epoch, is this recommended?)

I get the info: "Data rank (115) is smaller than the number of channels (128).  Input data size [115,525723] = 115 channels, 525723 frames/nAfter PCA dimension reduction,  
finding 115 ICA components using extended ICA."

Here is where I am losing track. For this example, there are 116 non-interpolated channels and the data set was re-referenced to common reference before ICA. 
So I guess this might be behind the rank reduction, although I am not sure how runica knows about this (where is such information retrieved?)

What precisely is used as the input data now? Any first 115 channels or only the non-interpolated channels? 
What happens when the resulting (clean) components are projected back onto channel space if some of the channels are not actually included in the data set used to calculate the components?

Many thanks in advance,


Alexandra Vossen
PhD student
School of Psychology
College of Science & Engineering
University of Glasgow