[Eeglablist] Separating out Alpha from mu oscillations
smakeig at ucsd.edu
Tue Mar 25 14:38:38 PDT 2014
The subject of the generators of EEG alpha/mu oscillations is a complex
one. Julie Onton made a poster on what ICA tells us
Basically, we have found no dramatic difference between motor mu
oscillations and occipital/parietal alpha oscillations:
They both have a peak near 10 Hz (in adults) - by convention in the range
8-12 Hz. They both are non-sinusoidal (i.e., they have harmonics in their
power spectra, for mu a bit more pronounced). They both separate into lower
and higher frequency alpha processes under Independent Modulator analysis
(as discussed here<http://sccn.ucsd.edu/~scott/pdf/Onton_CNS09_AlphaIMPoster.pdf>
They are both associated with inattention (positive disregard for the
'receptive focus' of the cortical area --> alpha/mu flooding; positive
attention to the 'receptive focus' --> alpha blocking). They differ
principally in location (alpha, across the occipital and parietal cortices;
mu, near the somatomotor strip).
Of course, at the scalp channels they are highly mixed by volume conduction
and can only be separated by ICA, so far as I am aware.
Some subsets of IC sources generating alpha band oscillations form
(somewhat) dependent subspaces (as confirmed by pairwise mutual information
measures, for which Jason Palmer has contributed a function in the EEGLAB
miscfunc folder). These dependencies may index mutual influences of various
types including (for alpha ICs with adjacent equivalent dipole locations)
the possibility of (local) alpha traveling wave phenomena.
On Tue, Mar 25, 2014 at 6:58 AM, B L <thirstyforknowledge123 at gmail.com>wrote:
> I guess this topic has been discussed in the past but I cant find an
> effective solution.
> We know that, it is very common for the alpha oscillation to have
> influence up to almost the frontal electrodes. My question is - If we are
> interested only in mu rhythm in a visual-motor task, what is the best way
> to tease out the alpha activity from the motor regions so the comparison
> across groups is more effective?
> Will ICA work better for this(just identifying the alpha component and
> removing it)? Is there any other method researchers commonly use for this
> Any help is much appreciated.
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Scott Makeig, Research Scientist and Director, Swartz Center for
Computational Neuroscience, Institute for Neural Computation, University of
California San Diego, La Jolla CA 92093-0961, http://sccn.ucsd.edu/~scott
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