<div dir="ltr"><div>Dear Jumana,</div><div><br></div><div><span style="color:rgb(0,0,0);font-family:calibri,arial,helvetica,sans-serif;font-size:16px">> Do you reduce dimensional with PCA first?</span></div><div><span style="color:rgb(0,0,0);font-family:calibri,arial,helvetica,sans-serif;font-size:16px"><br></span></div><div><span style="color:rgb(0,0,0);font-family:calibri,arial,helvetica,sans-serif;font-size:16px">Yes, this PCA is to reduce the data dimension for ICA. </span></div><div><span style="color:rgb(0,0,0);font-family:calibri,arial,helvetica,sans-serif;font-size:16px"><br></span></div><div><span style="color:rgb(0,0,0);font-family:calibri,arial,helvetica,sans-serif;font-size:16px">> If we want to avoid PCA how should one run AMICA? </span></div><div><span style="color:rgb(0,0,0);font-family:calibri,arial,helvetica,sans-serif;font-size:16px"><br></span></div><div><span style="color:rgb(0,0,0);font-family:calibri,arial,helvetica,sans-serif;font-size:16px">You can just skip this PCA stage and just run AMICA/infomax.</span></div><div><span style="color:rgb(0,0,0);font-family:calibri,arial,helvetica,sans-serif;font-size:16px"><br></span></div><div><span style="color:rgb(0,0,0);font-family:calibri,arial,helvetica,sans-serif;font-size:16px">> I do not want to add non-linearity to my data. I only want to use ICA to remove eye blinks from my data.</span><br></div><div><span style="color:rgb(0,0,0);font-family:calibri,arial,helvetica,sans-serif;font-size:16px"><br></span></div><div><span style="color:rgb(0,0,0);font-family:calibri,arial,helvetica,sans-serif;font-size:16px">Does PCA dimension reduction introduce non-linearity into data? Can you point me to the source (paper, article, etc). I have never heard of it.</span></div><div><span style="color:rgb(0,0,0);font-family:calibri,arial,helvetica,sans-serif;font-size:16px"><br></span></div><div><span style="color:rgb(0,0,0);font-family:calibri,arial,helvetica,sans-serif;font-size:16px">> Also, how should one ensure they are not rank deficient after interpolating.</span></div><div><span style="color:rgb(0,0,0);font-family:calibri,arial,helvetica,sans-serif;font-size:16px"><br></span></div><div><font color="#000000" face="calibri, arial, helvetica, sans-serif"><span style="font-size:16px">After interpolation, the data are rank deficient because the interpolated channels are weighted sum of other channels (i.e. carries no unique information).</span></font></div><div><span style="color:rgb(0,0,0);font-family:calibri,arial,helvetica,sans-serif;font-size:16px"><br></span></div><div><span style="color:rgb(0,0,0);font-family:calibri,arial,helvetica,sans-serif;font-size:16px">> I will reduce one channel after average referencing, but do I need further reductions after interpolation?</span><span style="color:rgb(0,0,0);font-family:calibri,arial,helvetica,sans-serif;font-size:16px"><br></span></div><div><span style="color:rgb(0,0,0);font-family:calibri,arial,helvetica,sans-serif;font-size:16px"><br></span></div><div>Yes, if you interpolate 10 channels, the data rank is reduced by 10.</div><div>In my new code, it uses the data rank of smaller values of either estimated rank or number of channels rejected by clean_rawdata(). I found this part is a little bit tricky, and for unknown reason this rank estimation can go wrong from time to time.</div><div><br></div><div>From UA49 to Newark,</div><div><br></div><div>Makoto </div><div><br></div><br><div class="gmail_extra"><br><div class="gmail_quote">On Fri, Jan 13, 2017 at 10:02 AM, Ahmad, Jumana <span dir="ltr"><<a href="mailto:jumana.ahmad@kcl.ac.uk" target="_blank">jumana.ahmad@kcl.ac.uk</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex">
<div>
<div id="gmail-m_-1628518934926403086divtagdefaultwrapper" style="font-size:12pt;color:rgb(0,0,0);font-family:calibri,arial,helvetica,sans-serif" dir="ltr">
<p>Dear Makoto,</p>
<p>I have thought about it some more and I will re-do my analysis using your pipeline for ICA. Please can you clarify a few things:</p>
<p><br>
</p>
<p>In your code:</p>
<p><br>
</p>
<p></p>
<pre style="font-family:monospace,courier;padding:1em;border:1px dashed rgb(47,111,171);background-color:rgb(249,249,249);line-height:1.1em;font-size:12.7px"> % Step 10: Run AMICA using calculated data rank with 'pcakeep' option
if isfield(EEG.etc, 'clean_channel_mask')
dataRank = min([rank(double(EEG.data')) sum(EEG.etc.clean_channel_<wbr>mask)]);
else
dataRank = min(rank(double(EEG.data')));
end
runamica15(EEG.data, 'num_chans', EEG.nbchan,...
'outdir', ['/data/projects/example/<wbr>amicaResults/' dataName],...
'pcakeep', dataRank, 'num_models', 1,...
'do_reject', 1, 'numrej', 15, 'rejsig', 3, 'rejint', 1);
EEG.etc.amica = loadmodout15(['/data/projects/<wbr>example/amicaResults/' dataName]);
EEG.etc.amica.S = EEG.etc.amica.S(1:EEG.etc.<wbr>amica.num_pcs, :); % Weirdly, I saw size(S,1) be larger than rank. This process does not hurt anyway.
EEG.icaweights = EEG.etc.amica.W;
EEG.icasphere = EEG.etc.amica.S;
EEG = eeg_checkset(EEG, 'ica');</pre>
Do you reduce dimensional with PCA first? If we want to avoid PCA how should one run AMICA? I do not want to add non-linearity to my data. I only want to use ICA to remove eye blinks from my data.
<p></p>
<p><br>
</p>
<p>Also, how should one ensure they are not rank deficient after interpolating. I will reduce one channel after average referencing, but do I need further reductions after interpolation?</p>
<p>Sorry for so many emails about this. Thank you. </p>
<p>Best wishes,</p>
<p>Jumana </p>
<p><br>
</p>
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<div id="gmail-m_-1628518934926403086divRplyFwdMsg" dir="ltr"><font face="Calibri, sans-serif" style="font-size:11pt" color="#000000"><b>From:</b> Makoto Miyakoshi <<a href="mailto:mmiyakoshi@ucsd.edu" target="_blank">mmiyakoshi@ucsd.edu</a>><br>
<b>Sent:</b> 13 January 2017 07:43:32<br>
<b>To:</b> Ahmad, Jumana<br>
<b>Cc:</b> <a href="mailto:eeglablist@sccn.ucsd.edu" target="_blank">eeglablist@sccn.ucsd.edu</a><br>
<b>Subject:</b> Re: [Eeglablist] baseline for short trial durations</font>
<div> </div>
</div><div><div class="gmail-h5">
<div>
<div dir="ltr">
<div>Dear Jumana,</div>
<div><br>
</div>
> Is this long enough for ITC.
<div><br>
</div>
<div>No. See this timely update of my wiki page.</div>
<div><br>
</div>
<div><a href="https://emea01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fsccn.ucsd.edu%2Fwiki%2FMakoto%2527s_preprocessing_pipeline%23A_tip_to_compute_time-frequency_transform_.28i.e._ERSP_.26_ITC.29_.2801.2F11.2F2017_updated.29&data=01%7C01%7Cjumana.ahmad%40kcl.ac.uk%7Cdcb3d49543b1411bf16908d43b7736c8%7C8370cf1416f34c16b83c724071654356%7C0&sdata=UYJEIoWzBT1nzwmNoS%2FQzMbBqbS1%2FPuTM%2FqqZeVSNdE%3D&reserved=0" target="_blank">https://sccn.ucsd.edu/wiki/<wbr>Makoto%27s_preprocessing_<wbr>pipeline#A_tip_to_compute_<wbr>time-frequency_transform_.28i.<wbr>e._ERSP_.26_ITC.29_.2801.2F11.<wbr>2F2017_updated.29</a><br>
</div>
<div><br>
</div>
<div>Therefore, you still want to use -1 to 2 second even if it create massive overlap. Your data will be 6 times heavier, and it's EEGLAB's pipeline issue: if you can compute time-frequency transform first then epoch, it does not occur. Hoewver, except for
inefficiency. you can still perform a correct computation, which is good.</div>
<div><br>
</div>
<div>Makoto</div>
<div><br>
</div>
<div><br>
</div>
<div>
<div class="gmail_extra"><br>
<div class="gmail_quote">On Wed, Jan 4, 2017 at 4:03 AM, Ahmad, Jumana <span dir="ltr">
<<a href="mailto:jumana.ahmad@kcl.ac.uk" target="_blank">jumana.ahmad@kcl.ac.uk</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex">
<div lang="EN-GB">
<div class="gmail-m_-1628518934926403086gmail-m_5180087001208607787WordSection1">
<p class="MsoNormal">Dear all,<u></u><u></u></p>
<p class="MsoNormal"><u></u> <u></u></p>
<p class="MsoNormal">I am analysing data from a MMN oddball experiment with:<u></u><u></u></p>
<p class="MsoNormal"><u></u> <u></u></p>
<p class="MsoNormal">Standards, 1000Hz 50ms tone; and deviant, 1000Hz, 100ms<u></u><u></u></p>
<p class="MsoNormal"><u></u> <u></u></p>
<p class="MsoNormal">The SOA is a random 500-600ms, so includes the tones (i.e. doesn't get longer when the duration is longer). <u></u><u></u></p>
<p class="MsoNormal"><u></u> <u></u></p>
<p class="MsoNormal">I want to calculate ERPs and ITC. What duration would you recommend for a baseline?<u></u><u></u></p>
<p class="MsoNormal"><u></u> <u></u></p>
<p class="MsoNormal">I am trying to avoid subtracting as much experimental related activity as possible, and as I am focusing on the MMN which occurs fairly early (let’s say before 300ms), I wondered if I should subtract a -100ms baseline. Is this long enough
for ITC. Sampling rate is 1000Hz, in most of data (I have 600 datasets, and 10% used 256Hz which of course I have used different filter lengths for etc.). Ideally I would look at the P3 but my trials may not be long enough.<u></u><u></u></p>
<p class="MsoNormal"><u></u> <u></u></p>
<p class="MsoNormal">Thank you,<u></u><u></u></p>
<p class="MsoNormal">Jumana <u></u><u></u></p>
<p class="MsoNormal"><u></u> <u></u></p>
<p class="MsoNormal"><u></u> <u></u></p>
<p class="MsoNormal"><u></u> <u></u></p>
<p class="MsoNormal"><u></u> <u></u></p>
<p class="MsoNormal"><u></u> <u></u></p>
<p class="MsoNormal" style="background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;background-color:white">
<b><span style="font-size:10pt;color:rgb(31,73,125)">------------------------------<wbr>------------</span></b><span style="font-family:helvetica,sans-serif;color:black"><u></u><u></u></span></p>
<p class="MsoNormal" style="background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;background-color:white">
<b><span style="font-size:10pt;color:rgb(31,73,125);background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;background-color:rgb(255,238,148)">Jumana Ahmad</span></b><span style="font-family:helvetica,sans-serif;color:black"><u></u><u></u></span></p>
<p class="MsoNormal" style="background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;background-color:white">
<span style="font-size:10pt;color:rgb(31,73,125)">Post-Doctoral Research Worker in Cognitive Neuroscience </span><span style="font-family:helvetica,sans-serif;color:black"><u></u><u></u></span></p>
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<span style="font-size:10pt;color:rgb(31,73,125)">Room M1.09. Department of Forensic and Neurodevelopmental Sciences (PO 23) | Institute of Psychiatry, Psychology & Neuroscience | King’s College London | 16 De Crespigny Park | London SE5 8AF</span><span style="font-family:helvetica,sans-serif;color:black"><u></u><u></u></span></p>
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<br>
<br clear="all">
<div><br>
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-- <br>
<div class="gmail-m_-1628518934926403086gmail_signature">
<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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</div></div></div>
</blockquote></div><br><br clear="all"><div><br></div>-- <br><div class="gmail_signature"><div dir="ltr">Makoto Miyakoshi<br>Swartz Center for Computational Neuroscience<br>Institute for Neural Computation, University of California San Diego<br></div></div>
</div></div>