[Eeglablist] Comparing mu suppression with EEGLAB

[Makoto Miyakoshi]

Dear Anderson,

Sorry that is a typo! Below is the correction:

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

Makoto


On Wed, Jun 25, 2014 at 7:20 AM, Anderson Oliveira <asoliv at umich.edu> wrote:

> Hi, I have a question concerning the proposed code, since I'm not very
> familiar with EEGLAB so far:
>
> Why in the command below channel 1 is represented by the number 2?   if
> the matrix EEG.data has 64 channels for instance, does the code starts on
> the 2 position in the first dimension?
>
> % for your epoched data, channel 1
>  [spectra,freqs] = spectopo(EEG.data(2,:,:), 0, EEG.srate);
>
>
>  Thanks for the help,
> Anderson
>
>
>
>
> On Mon, Jun 23, 2014 at 1:15 PM, Makoto Miyakoshi <mmiyakoshi at ucsd.edu>
> wrote:
>
>> Dear Florient,
>>
>> Maybe this code can help you. Good luck.
>>
>> 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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>
>


-- 
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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