[Eeglablist] ICA misinformation

Arnaud Delorme arno at ucsd.edu
Sat Jun 10 10:00:11 PDT 2017

We get asked repetitively about the video below which claims that ICA adulterates EEG Phase & Coherence

https://www.youtube.com/watch?v=BfqCh2UeJik&feature=youtu.be <https://www.youtube.com/watch?v=BfqCh2UeJik&feature=youtu.be>

I posted a comment on this video which was suppressed by the author. Please repost that message again if you can and vote down this video which is basically misleading people.


My response to this video:

The measure of FFT coherence and phase lag between hemisphere that is being used in this video has no physiological basis to my knowledge (because inter-hemispheric FFT coherence and change in phase lag may be due to a single deep EEG source, so it does not reflect inter-hemispheric communication), so I do not think that ICA makes it better or worse. It just makes it different.

ICA applies a spatial filter to extract artifacts activity which can be then removed from the data. One needs to be mindful of which artefacts are being removed and also if ICA was successful at isolating such artifacts.

Arnaud Delorme, PhD - Main developer of EEGLAB, the ICA/EEG software

This is a more technical response from Jason Palmer who is a mathematician at UCSD and ICA expert

"My take: ordinary ICA can’t change the phase of any oscillations because it is just an “instantaneous” linear combination of the channels without any time shifts. Just as the channel EEG is a linear combination of the sources in the brain, each IC is a certain linear sum of all the channels, so it contains all the oscillations except that ICA is formulated to separate sources in different ICs.

The only way to distort phase is to do some kind of filtering, or convolution, of the data. E.g. using a normal FIR filter will change the phase, ideally just adding a constant delay to each oscillation (linear phase). Typically to do high-pass filtering, we use filtfilt, which runs the filter first in the forward direction, adding a constant phase, and then in the reverse direction subtracting the phase, to leave all oscillations with zero phase shift.

But each ICs is just an instantaneous combination of the channels, with no filtering. So all oscillations (in the fourier decomposition) have the same phase, it’s just that oscillations may be separated into different ICs.

There may be some confusion if you use phase to refer to the temporal shift of a general waveform, for example the peak latency of an ERP which is itself the combination of a number of oscillations (frequencies and phases). ICA may separate an apparent peak into the sum of two independent nearby peaks, but the argument which is testable is that the sources are statistically independent (distinct) and the decomposition gives more information about the nature of the ERP. And again, the separation is done just by an instantaneous combination of the non-delayed channels. This is completely different from doing a time-domain PCA or other time of decomposition of the waveform. In ICA we are basically trying to design (instantaneous) spatial filters such that the output signals have distributions that are statistically independent.”

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