# [Eeglablist] Comparing mu suppression with EEGLAB

Makoto Miyakoshi mmiyakoshi at ucsd.edu
Mon Jun 23 10:15:38 PDT 2014

```Dear Florient,

I've seen quite a few users wanted to know how to do this. Maybe it would
be convenient if I write a simple EEGLAB plugin for this.

Makoto

% for your epoched data, channel 1
[spectra,freqs] = spectopo(EEG.data(2,:,:), 0, EEG.srate);

% delta=1-4, theta=4-8, alpha=8-13, beta=13-30, gamma=30-80
deltaIdx = find(freqs>1 & freqs<4);
thetaIdx = find(freqs>4 & freqs<8);
alphaIdx = find(freqs>8 & freqs<13);
betaIdx  = find(freqs>13 & freqs<30);
gammaIdx = find(freqs>30 & freqs<80);

% compute absolute power
deltaPower = 10^(mean(spectra(deltaIdx))/10);
thetaPower = 10^(mean(spectra(thetaIdx))/10);
alphaPower = 10^(mean(spectra(alphaIdx))/10);
betaPower  = 10^(mean(spectra(betaIdx))/10);
gammaPower = 10^(mean(spectra(gammaIdx))/10);

On Thu, Jun 19, 2014 at 2:30 AM, CHOUTEAU Florient <
florient.chouteau at isae.fr> wrote:

>  Hi,
> I am an human factor students doing a research projet on mirror neurons
> and I am struggling with EEGLAB.
> I am trying to compare several EEG signals, mainly located in C3/C4 using
> more or less the same protocol as Oberman et al 2007[1] and 2005[3]. In
> fact, I acquired three signals (subject presented to three videos including
> a baseline (white noise)) and I am trying to calculate mu suppression by
> displaying "The ratio of the power in the mu frequency" as described in
> [1], [2] and [3]. (Specific quote: "For each cleaned segment the integrated
> power in the 8–13 Hz range was computed using a fast Fourier transform")
> Problem is, I have absolutely no clue as to how "substract" the power from
> the two tests and the baseline in EEGLAB. I successfully displayed the
> power = f (frequency) for all of my signals but substracting one to the
> other and calculating the global power in the frequency range remain a
> mystery to me.
>
> Assuming that I dispose of cleaned epoched data, would you have any idea
> as to how to proceed, using EEGLAB functions or simply MATLAB ones,
>
> Best Regards,
>
> Florient CHOUTEAU
>
> References:
>
> [1]Oberman, L. M., McCleery, J. P., Ramachandran, V. S., & Pineda, J. A.
> (2007). EEG evidence for mirror neuron activity during the observation of
> human and robot actions: Toward an analysis of the human qualities of
> interactive robots. *Neurocomputing*, *70*(13), 2194-2203.
>
> http://cognitiveneurolab.ucsd.edu/Papers_files/Oberman,%20L.M.,%20McCleery,%20J.P.,%20Ramachandran,%20V.S.,%20and%20Pineda,%20J.A.%C2%A0%20EEG%20evidence%20for%20mirror%20neuron%20activity%20during%20the%20observation%20of%20human%20and%20robot%20actions_2.pdf
>
> [2]Arnstein, D., Cui, F., Keysers, C., Maurits, N. M., & Gazzola, V.
> (2011). μ-suppression during action observation and execution correlates
> with BOLD in dorsal premotor, inferior parietal, and SI cortices. *The
> Journal of Neuroscience*, *31*(40), 14243-14249.
> http://www.jneurosci.org/content/31/40/14243.full
>
> [3]Oberman, L. M., Hubbard, E. M., McCleery, J. P., Altschuler, E. L.,
> Ramachandran, V. S., & Pineda, J. A. (2005). EEG evidence for mirror neuron
> dysfunction in autism spectrum disorders. *Cognitive Brain Research*, *24*(2),
> 190-198.
> http://www.bowdiges.org/documents/files/Mirror_neurons_in_ASD.pdf
>
>
>
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--
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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