<div dir="ltr">Hi, I have a question concerning the proposed code, since I'm not very familiar with EEGLAB so far:<div><br></div><div>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?<br>
<div><br></div><div><div style="font-family:arial,sans-serif;font-size:12.571428298950195px"><span style="font-size:12.666666984558105px">% for your epoched data, channel 1</span><br></div><div style="font-family:arial,sans-serif;font-size:12.571428298950195px">
<div style="font-size:12.666666984558105px">[spectra,freqs] = spectopo(EEG.data(2,:,:), 0, EEG.srate);</div><div style="font-size:12.666666984558105px"><br></div><div style="font-size:12.666666984558105px"><br></div><div style="font-size:12.666666984558105px">
Thanks for the help,</div><div style="font-size:12.666666984558105px">Anderson</div><div style="font-size:12.666666984558105px"><br></div><div style="font-size:12.666666984558105px"><br></div></div></div></div></div><div class="gmail_extra">
<br><br><div class="gmail_quote">On Mon, Jun 23, 2014 at 1:15 PM, Makoto Miyakoshi <span dir="ltr"><<a href="mailto:mmiyakoshi@ucsd.edu" target="_blank">mmiyakoshi@ucsd.edu</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
<div dir="ltr"><div style="font-family:arial,sans-serif;font-size:12.571428298950195px"><span style="font-size:12.666666984558105px">Dear Florient,</span></div><div style="font-family:arial,sans-serif;font-size:12.571428298950195px">
<span style="font-size:12.666666984558105px"><br></span></div><div style="font-family:arial,sans-serif;font-size:12.571428298950195px"><span style="font-size:12.666666984558105px">Maybe this code can help you. Good luck.</span></div>
<div style="font-family:arial,sans-serif;font-size:12.571428298950195px"><span style="font-size:12.666666984558105px"><br></span></div><div style="font-family:arial,sans-serif;font-size:12.571428298950195px"><span style="font-size:12.666666984558105px">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.</span></div>
<div style="font-family:arial,sans-serif;font-size:12.571428298950195px"><span style="font-size:12.666666984558105px"><br></span></div><div style="font-family:arial,sans-serif;font-size:12.571428298950195px"><span style="font-size:12.666666984558105px">Makoto </span></div>
<div style="font-family:arial,sans-serif;font-size:12.571428298950195px"><span style="font-size:12.666666984558105px"><br></span></div><div style="font-family:arial,sans-serif;font-size:12.571428298950195px"><span style="font-size:12.666666984558105px">% for your epoched data, channel 1</span><br>
</div><div style="font-family:arial,sans-serif;font-size:12.571428298950195px"><div style="font-size:12.666666984558105px">[spectra,freqs] = spectopo(EEG.data(2,:,:), 0, EEG.srate);</div><div style="font-size:12.666666984558105px">
<br></div><div style="font-size:12.666666984558105px">% delta=1-4, <span>theta</span>=4-8, <span>alpha</span>=8-13, <span>beta</span>=13-30, gamma=30-80</div><div style="font-size:12.666666984558105px">
deltaIdx = find(freqs>1 & freqs<4);</div><div style="font-size:12.666666984558105px">thetaIdx = find(freqs>4 & freqs<8);</div><div style="font-size:12.666666984558105px">alphaIdx = find(freqs>8 & freqs<13);</div>
<div style="font-size:12.666666984558105px">betaIdx = find(freqs>13 & freqs<30);</div><div style="font-size:12.666666984558105px">gammaIdx = find(freqs>30 & freqs<80);</div><div style="font-size:12.666666984558105px">
<br></div><div style="font-size:12.666666984558105px">% compute absolute power</div><div style="font-size:12.666666984558105px">deltaPower = 10^(mean(spectra(deltaIdx))/10);</div><div style="font-size:12.666666984558105px">
thetaPower = 10^(mean(spectra(thetaIdx))/10);</div><div style="font-size:12.666666984558105px">alphaPower = 10^(mean(spectra(alphaIdx))/10);</div><div style="font-size:12.666666984558105px">betaPower = 10^(mean(spectra(betaIdx))/10);</div>
<div style="font-size:12.666666984558105px">gammaPower = 10^(mean(spectra(gammaIdx))/10);</div></div></div><div class="gmail_extra"><br><br><div class="gmail_quote"><div><div class="h5">On Thu, Jun 19, 2014 at 2:30 AM, CHOUTEAU Florient <span dir="ltr"><<a href="mailto:florient.chouteau@isae.fr" target="_blank">florient.chouteau@isae.fr</a>></span> wrote:<br>
</div></div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div><div class="h5">
<div text="#000000" bgcolor="#FFFFFF">
Hi,<br>
I am an human factor students doing a research projet on mirror
neurons and I am struggling with EEGLAB.<br>
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")<br>
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.<br>
<br>
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,<br>
<br>
Best Regards,<br>
<br>
Florient CHOUTEAU<br>
<br>
References:<br>
<br>
<div>[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. <i>Neurocomputing</i>, <i>70</i>(13),
2194-2203.</div>
<a href="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" target="_blank">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</a><br>
<br>
[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. <i>The Journal of Neuroscience</i>, <i>31</i>(40),
14243-14249.<br>
<a href="http://www.jneurosci.org/content/31/40/14243.full" target="_blank">http://www.jneurosci.org/content/31/40/14243.full</a><br>
<br>
[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. <i>Cognitive
Brain Research</i>, <i>24</i>(2), 190-198.<br>
<a href="http://www.bowdiges.org/documents/files/Mirror_neurons_in_ASD.pdf" target="_blank">http://www.bowdiges.org/documents/files/Mirror_neurons_in_ASD.pdf</a><br>
<br>
<br>
</div>
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-- <br><div dir="ltr">Makoto Miyakoshi<br>Swartz Center for Computational Neuroscience<br>Institute for Neural Computation, University of California San Diego<br></div>
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