<div><br></div><div>I would favor "manually" or otherwise catching/rejecting the noisy epochs</div><div>rather than "saving time", in the interest of more accurate results. </div><div>What guarantees do we have that various things like teeth grinding, </div>
<div>jaw clenching, brow furrowing, blinking, movement, etc.. is not in the data?</div><div><br></div><div>There's a plethora of algorithms, automatic methods, and toolboxes to </div><div>clean up EEG data before feeding it to ICA and post-ICA.</div>
<div>However, in a world of big data, visual inspection is so old-school!</div><div><br></div><div>For ICA, the idea is to not confuse ICA with extreme data fluctuations that can draw ICA's interest</div><div><br></div>
<div>As far as I understand </div><div>ICA will happily eat and decompose continuous or epoched data, as long as there is enough data (e.g., enough time points)</div><div><br></div><div><br></div><div><br></div><br>
<br><br><div class="gmail_quote">On Wed, Sep 12, 2012 at 4:02 AM, Gunseli, E. <span dir="ltr"><<a href="mailto:e.gunseli@vu.nl" target="_blank">e.gunseli@vu.nl</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
<div lang="NL" link="blue" vlink="purple">
<div>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">Dear all,<u></u><u></u></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"><u></u> <u></u></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">I have a question about the steps that should be taken before running ICA.<u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"><u></u> <u></u></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">If we are going to epoch the data (step 5), why are we manually rejecting the extra noisy parts earlier (step 2).
<u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">Since these extra noisy portions are mostly at beginning and end of trial blocks, they will be gone away during epoching anyway.
<u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">So, epoching the critical time window can save a fair amount of time that else we would have spent on manual inspection.<u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"><u></u> <u></u></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">At this point I have another question; I have read that, it is better to run ICA on continuous, non-epoched data.
<u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">One of the problems of running ICA on epoched data is that, “the baseline correction changes relative values across channels” (S. Luck, ERP Boot
Camp Lecture Slides). But probably that is not the only reason to run ICA on continuous data because this problem can easily be overcome via removing the baseline after running ICAs.
<u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">So I guess there should be other problems related to running ICAs on epoched data.<u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">Can anyone provide information about these potential problems?<u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"><u></u> <u></u></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">Kind regards,<u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">Eren<u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"><u></u> <u></u></span></p>
<div style="border:none;border-top:solid #b5c4df 1.0pt;padding:3.0pt 0cm 0cm 0cm">
<p class="MsoNormal"><b><span lang="EN-US" style="font-size:10.0pt;font-family:"Tahoma","sans-serif"">From:</span></b><span lang="EN-US" style="font-size:10.0pt;font-family:"Tahoma","sans-serif""> <a href="mailto:eeglablist-bounces@sccn.ucsd.edu" target="_blank">eeglablist-bounces@sccn.ucsd.edu</a> [mailto:<a href="mailto:eeglablist-bounces@sccn.ucsd.edu" target="_blank">eeglablist-bounces@sccn.ucsd.edu</a>]
<b>On Behalf Of </b>Makoto Miyakoshi<br>
<b>Sent:</b> Friday, September 07, 2012 00:58</span></p><div class="im"><br>
<b>To:</b> IMALI THANUJA HETTIARACHCHI<br>
<b>Cc:</b> <a href="mailto:eeglablist@sccn.ucsd.edu" target="_blank">eeglablist@sccn.ucsd.edu</a><br>
</div><b>Subject:</b> Re: [Eeglablist] On ICA based artifact rejection<u></u><u></u><p></p>
</div><div><div class="h5">
<p class="MsoNormal"><u></u> <u></u></p>
<p class="MsoNormal">Dear Imali,<u></u><u></u></p>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">Pipeline check?<u></u><u></u></p>
</div>
<div>
<p><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">1.</span><span style="font-size:7.0pt;color:#1f497d"> </span><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">Re-reference continues data
(The data is collected on a bipolar montage so re-reference to the common average)</span><u></u><u></u></p>
<p><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">2.</span><span style="font-size:7.0pt;color:#1f497d"> </span><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">Reject unsuitable portions
of data by visual inspection</span><u></u><u></u></p>
<p><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">3.</span><span style="font-size:7.0pt;color:#1f497d"> </span><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">High pass filter the data(cut-off
@ 0.5Hz to preserve ERP components), low pass filter the data(cut-off 30Hz)</span><u></u><u></u></p>
</div>
<div>
<p class="MsoNormal">I would say filtering should be done before data rejection, since the rejection creates boundaries which can confuse filtering.<u></u><u></u></p>
<p><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">4.</span><span style="font-size:7.0pt;color:#1f497d"> </span><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">Extract epochs (without baseline
removal???)</span><u></u><u></u></p>
<p>According to Groppe et al., whole-epoch baseline is better than usual short pre-stimulus baseline. Scott says no baseline correction is even better. So without baseline removal may be better.<u></u><u></u></p>
<p><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">5.</span><span style="font-size:7.0pt;color:#1f497d"> </span><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">Run ICA</span><u></u><u></u></p>
<p><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">6.</span><span style="font-size:7.0pt;color:#1f497d"> </span><b><i><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">A. Tools>Remove components </span></i></b><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">to
subtract ICA components or should I do</span><u></u><u></u></p>
<p><b><i><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">B.</span></i></b><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"> <b><i>Tools> Reject data Epochs> reject data(all methods),(</i></b> but
if I do this how can that be an artifact rejection<b><i> </i></b>by ICA)<b><i> </i></b>or</span><u></u><u></u></p>
<p><b><i><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">C.Tools>Reject data epochs>export marks to ICA reject </span></i></b><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">and then<b><i> Tools>Reject
data epochs>Reject marked epochs</i></b>?</span><u></u><u></u></p>
<p>6A is not necessary if you are going to use STUDY (it will create clusters for artifacts) so don't bother to do this. 6B is recommended. Theoretically, 2nd ICA after 6B improves the quality of decomposition, but in my experience it rarely changes the result
unless drastic rejection, either quantitatively or qualitatively, is performed.<u></u><u></u></p>
<p><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">Could you please make it clear to me how I should reject epochs using ICA after the first decomposition.</span><u></u><u></u></p>
<p>Just take a look at independent component activities as you check your channel EEG data. It is a good idea to use 'all methods' for obtaining statistical suggestions (but don't take them blindly). You may want to discard 5-10 % of data here, depending your
data quality. Improbability test is good but hopefully it is done after thresholding on channel EEG (therefore I recommend mild amplitude threshold on channel EEG before ICA, and then improbability test on IC activities).<u></u><u></u></p>
<p><b><i><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">7.</span></i></b><span style="font-size:7.0pt;color:#1f497d"> </span><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">Then <b>Tools>Remove
Baseline</b> and <b><i> Plot>Channel ERP’s </i></b>steps<b><i> </i></b>will give me the ERP for a particular stimulation?</span><u></u><u></u></p>
<p>Yes.<u></u><u></u></p>
<p><b><i><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">8.</span></i></b><span style="font-size:7.0pt;color:#1f497d"> </span><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">Now to do dipole
localisation Run ICA on the pruned data set and run DIPFIT, here won’t I get the same remaining ICA components from the first epoched data set?</span><u></u><u></u></p>
<p>Again, whether or not running the 2nd ICA depends on how much you care about data quality. DIPFIT does not care your IC activities. It only cares about scalp maps ICA generated. Therefore, epoch rejection does not affect DIPFIT performance. <u></u><u></u></p>
<p>You should locate two dipoles manually when you find bilateral topographies using an interactive 'fine fit' GUI of DIPFIT. <u></u><u></u></p>
<p>Makoto<u></u><u></u></p>
<p><u></u> <u></u></p>
<div>
<p class="MsoNormal">2012/9/6 Stephen Politzer-Ahles <<a href="mailto:politzerahless@gmail.com" target="_blank">politzerahless@gmail.com</a>><u></u><u></u></p>
<p class="MsoNormal">Hi Imali,<br>
<br>
I don't have experience with using "reject based on ICA", but the first option you pointed out (6A--using Tools>Reject components to remove the IC(s) with artifact) works. What I have typically done is first use Tools>Reject components to do that, and then
use Tools>Reject epochs (by inspection) on the cleaned data to go through and reject any epochs that contain other artifact. (In my case, I use ICA to remove the blink artifacts, but then must reject by inspection to remove artifact that's left over such as
skin potentials or EMG).<br>
<br>
Maybe some others on the list can give you some more information about the other methods, which I am not familiar with.<br>
<br>
Best,<br>
Steve<u></u><u></u></p>
<div>
<div>
<p class="MsoNormal" style="margin-bottom:12.0pt"><u></u> <u></u></p>
<div>
<p class="MsoNormal">On Wed, Sep 5, 2012 at 10:28 PM, IMALI THANUJA HETTIARACHCHI <<a href="mailto:ith@deakin.edu.au" target="_blank">ith@deakin.edu.au</a>> wrote:<u></u><u></u></p>
<div>
<div>
<p class="MsoNormal"><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">Thank you very much Makoto, really appreciate your guidance and help.</span><span lang="EN-AU"><u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"> </span><span lang="EN-AU"><u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">I have further some questions regarding ICA artifact rejection and localisation.</span><span lang="EN-AU"><u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"> </span><span lang="EN-AU"><u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#376092">In EEGLAb we use ICA for both artifact rejection and source localisation? As I want
to use EEGLAB for my dipole localisation, I am a bit confused with the steps that I should follow, I read the details on artifact rejection given on the wiki and a thread on ‘</span><span lang="EN-AU" style="color:#376092">Pipeline of processing to optimize
ICA for artrifact removal</span><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#376092">’
</span><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">on the discussion list, but still not clear on the steps. Below I will briefly give the steps which I understood that I should follow, can you please tell me
whether my understanding is correct and comment if I have gone wrong somewhere?</span><span lang="EN-AU"><u></u><u></u></span></p>
<p><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">1.</span><span lang="EN-AU" style="font-size:7.0pt;color:#1f497d">
</span><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">Re-reference continues data (The data is collected on a bipolar montage so re-reference to the common average)</span><span lang="EN-AU"><u></u><u></u></span></p>
<p><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">2.</span><span lang="EN-AU" style="font-size:7.0pt;color:#1f497d">
</span><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">Reject unsuitable portions of data by visual inspection</span><span lang="EN-AU"><u></u><u></u></span></p>
<p><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">3.</span><span lang="EN-AU" style="font-size:7.0pt;color:#1f497d">
</span><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">High pass filter the data(cut-off @ 0.5Hz to preserve ERP components), low pass filter the data(cut-off 30Hz)</span><span lang="EN-AU"><u></u><u></u></span></p>
<p><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">4.</span><span lang="EN-AU" style="font-size:7.0pt;color:#1f497d">
</span><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">Extract epochs (without baseline removal???)</span><span lang="EN-AU"><u></u><u></u></span></p>
<p><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">5.</span><span lang="EN-AU" style="font-size:7.0pt;color:#1f497d">
</span><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">Run ICA</span><span lang="EN-AU"><u></u><u></u></span></p>
<p><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"> </span><span lang="EN-AU"><u></u><u></u></span></p>
<p><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">Now I get confused, after the ICA decomposition I will be able to view the ICA components with
<b><i>Tools> Reject data using ICA>Reject components by map</i></b></span><span lang="EN-AU"><u></u><u></u></span></p>
<p><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">With this window I can detect the components for eye artifacts, muscle artifacts etc. Then is it,</span><span lang="EN-AU"><u></u><u></u></span></p>
<p><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"> </span><span lang="EN-AU"><u></u><u></u></span></p>
<p><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">6.</span><span lang="EN-AU" style="font-size:7.0pt;color:#1f497d">
</span><b><i><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">A. Tools>Remove components
</span></i></b><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">to subtract ICA components or should I do</span><span lang="EN-AU"><u></u><u></u></span></p>
<p><b><i><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">B.</span></i></b><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">
<b><i>Tools> Reject data Epochs> reject data(all methods),(</i></b> but if I do this how can that be an artifact rejection<b><i>
</i></b>by ICA)<b><i> </i></b>or </span><span lang="EN-AU"><u></u><u></u></span></p>
<p><b><i><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">C.Tools>Reject data epochs>export marks to ICA reject
</span></i></b><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">and then<b><i> Tools>Reject data epochs>Reject marked epochs</i></b>?</span><span lang="EN-AU"><u></u><u></u></span></p>
<p><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"> </span><span lang="EN-AU"><u></u><u></u></span></p>
<p><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">Could you please make it clear to me how I should reject epochs using ICA after the first decomposition.</span><span lang="EN-AU"><u></u><u></u></span></p>
<p><b><i><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">7.</span></i></b><b><i><span lang="EN-AU" style="font-size:7.0pt;color:#1f497d">
</span></i></b><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">Then
<b>Tools>Remove Baseline</b> and <b><i> Plot>Channel ERP’s </i></b>steps<b><i> </i>
</b>will give me the ERP for a particular stimulation?</span><span lang="EN-AU"><u></u><u></u></span></p>
<p><b><i><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">8.</span></i></b><b><i><span lang="EN-AU" style="font-size:7.0pt;color:#1f497d">
</span></i></b><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">Now to do dipole localisation Run ICA on the pruned data set and run DIPFIT, here won’t I get the same remaining ICA components from the first epoched
data set?</span><span lang="EN-AU"><u></u><u></u></span></p>
<p><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"> </span><span lang="EN-AU"><u></u><u></u></span></p>
<p><b><i><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"> </span></i></b><span lang="EN-AU"><u></u><u></u></span></p>
<p><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">Many thanks,</span><span lang="EN-AU"><u></u><u></u></span></p>
<p><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">Imali</span><span lang="EN-AU"><u></u><u></u></span></p>
<p class="MsoNormal" style="margin-left:36.0pt">
<b><i><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"> </span></i></b><span lang="EN-AU"><u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"> </span><span lang="EN-AU"><u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"> </span><span lang="EN-AU"><u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-AU" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"> </span><span lang="EN-AU"><u></u><u></u></span></p>
<p class="MsoNormal"><b><span lang="EN-US" style="font-size:10.0pt;font-family:"Tahoma","sans-serif"">From:</span></b><span lang="EN-US" style="font-size:10.0pt;font-family:"Tahoma","sans-serif""> Makoto
Miyakoshi [mailto:<a href="mailto:mmiyakoshi@ucsd.edu" target="_blank">mmiyakoshi@ucsd.edu</a>]
<br>
<b>Sent:</b> Wednesday, 5 September 2012 7:02 AM<br>
<b>To:</b> IMALI THANUJA HETTIARACHCHI<br>
<b>Cc:</b> <a href="mailto:eeglablist@sccn.ucsd.edu" target="_blank">eeglablist@sccn.ucsd.edu</a><br>
<b>Subject:</b> Re: [Eeglablist] ERP localisation with BESA and DIPFIT with ICA</span><span lang="EN-AU"><u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-AU"> <u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-AU">Dear Imali,<u></u><u></u></span></p>
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<p class="MsoNormal"><span lang="EN-AU"> <u></u><u></u></span></p>
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<p class="MsoNormal"><span lang="EN-AU">ICA returns 'one map/IC per a component' which does not change across recording time.<u></u><u></u></span></p>
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<p class="MsoNormal"><span lang="EN-AU">A static location corresponds to a brain region.<u></u><u></u></span></p>
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<p class="MsoNormal"><span lang="EN-AU">If you think of averaged ERP topo, for example, scalp topography changes from timepoint to timepoint. Independent components are not like that.<u></u><u></u></span></p>
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<p class="MsoNormal"><span lang="EN-AU"> <u></u><u></u></span></p>
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<p class="MsoNormal"><span lang="EN-AU">> 2.</span><span lang="EN-AU" style="font-size:7.0pt"> </span><span lang="EN-AU">Do independent components for cognitive activity in brain represents ERP
components(P1,N1, etc)?<u></u><u></u></span></p>
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<p class="MsoNormal"><span lang="EN-AU"> <u></u><u></u></span></p>
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<p class="MsoNormal"><span lang="EN-AU">Not necessarily. One IC can explain 3 ERP peaks (P1/N1/P2 as one burst).<u></u><u></u></span></p>
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<p class="MsoNormal"><span lang="EN-AU"> <u></u><u></u></span></p>
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<p class="MsoNormal"><span lang="EN-AU">> 3.</span><span lang="EN-AU" style="font-size:7.0pt"> </span><span lang="EN-AU">Since I have minimal(correct to say no..) experience in ERP, how do I know
my dipole localisations with ICA are correct? For instance, in a visual task I would expect to see one or more dipoles in visual area, but when changing the conditions such as colour or shape where else do I get dipoles? Or simply, how do I have a hypothesis
for the ICA component related dipoles?<u></u><u></u></span></p>
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<p class="MsoNormal"><span lang="EN-AU"> <u></u><u></u></span></p>
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<p class="MsoNormal"><span lang="EN-AU">How do I know my dipole location is correct? <u></u><u></u></span></p>
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<p class="MsoNormal"><span lang="EN-AU">When you calculate dipole fit, you'll have residual variance. If this value is small, that means your dipole location is good.<u></u><u></u></span></p>
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<p class="MsoNormal"><span lang="EN-AU">For symmetrical two dipoles, when the topography show bilateral pattern you should place two dipoles (This may require some prior knowledge about somatosensory
mu, alpha, and EOG). <u></u><u></u></span></p>
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<p class="MsoNormal"><span lang="EN-AU"> <u></u><u></u></span></p>
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<p class="MsoNormal"><span lang="EN-AU">> 4.</span><span lang="EN-AU" style="font-size:7.0pt"> </span><span lang="EN-AU">With very limited neuroscience knowledge how do I get around with localisations
to extract a task related neuronal activity?<u></u><u></u></span></p>
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<p class="MsoNormal"><span lang="EN-AU"> <u></u><u></u></span></p>
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<p class="MsoNormal"><span lang="EN-AU">If you don't have time to read Scott Makeig, Arnaud Delorme, or Julie Onton etc, then<u></u><u></u></span></p>
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<p class="MsoNormal"><span lang="EN-AU">1. run ICA<u></u><u></u></span></p>
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<p class="MsoNormal"><span lang="EN-AU">2. run dipfit (autofit)<u></u><u></u></span></p>
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<p class="MsoNormal"><span lang="EN-AU">Remember, 1 dipole for 1 (or bilateral 2) IC(s). They are always paired. ICA generates time-invariant scalp topo, and dipfit calculates the associated dipole(s)
that is also time-invariant (ICs don't change their locations throughout your data just as your brain regions don't).<u></u><u></u></span></p>
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<p class="MsoNormal"><span lang="EN-AU"> <u></u><u></u></span></p>
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<p class="MsoNormal"><span lang="EN-AU">If you have further questions please ask further.<u></u><u></u></span></p>
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<p class="MsoNormal"><span lang="EN-AU"> <u></u><u></u></span></p>
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<p class="MsoNormal"><span lang="EN-AU">Makoto<u></u><u></u></span></p>
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<p class="MsoNormal"><span lang="EN-AU"> <u></u><u></u></span></p>
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<p class="MsoNormal"><span lang="EN-AU">2012/8/31 IMALI THANUJA HETTIARACHCHI <<a href="mailto:ith@deakin.edu.au" target="_blank">ith@deakin.edu.au</a>><u></u><u></u></span></p>
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<p class="MsoNormal"><span lang="EN-AU">Dear EEGLAB list,<u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-AU"> <u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-AU">While reading through papers for my experiments, I just became curious (with some confusion) on the dipole fitting approach of the ERP data(for a specific task).
<u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-AU"> <u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-AU">According to my understanding the ERP wave consists of several components such as P1,N1, P2 , N2 and P3 mainly (stimulus dependent). As I am intending to use
ICA based source localization(using DIPFIT plugin) I wanted to find out on what degree the two dipole fitting approaches are differing in BESA and DIPFIT with ICA.<u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-AU"> <u></u><u></u></span></p>
<p style="margin-left:20.25pt"><span lang="EN-AU">1.</span><span lang="EN-AU" style="font-size:7.0pt">
</span><span lang="EN-AU">Am I correct if I say that with BESA, dipoles can be fitted to individual components of the ERP waveform?
<u></u><u></u></span></p>
<p style="margin-left:20.25pt"><span lang="EN-AU">2.</span><span lang="EN-AU" style="font-size:7.0pt">
</span><span lang="EN-AU">Do independent components for cognitive activity in brain represents ERP components(P1,N1, etc)?
<u></u><u></u></span></p>
<p style="margin-left:20.25pt"><span lang="EN-AU">3.</span><span lang="EN-AU" style="font-size:7.0pt">
</span><span lang="EN-AU">Since I have minimal(correct to say no..) experience in ERP, how do I know my dipole localisations with ICA are correct? For instance, in a visual task I would expect to see one or more dipoles in visual area, but when changing the
conditions such as colour or shape where else do I get dipoles? Or simply, how do I have a hypothesis for the ICA component related dipoles?<u></u><u></u></span></p>
<p style="margin-left:20.25pt"><span lang="EN-AU">4.</span><span lang="EN-AU" style="font-size:7.0pt">
</span><span lang="EN-AU">With very limited neuroscience knowledge how do I get around with localisations to extract a task related neuronal activity?
<u></u><u></u></span></p>
<p class="MsoNormal" style="margin-left:2.25pt">
<span lang="EN-AU"> <u></u><u></u></span></p>
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<span lang="EN-AU">Sorry about throwing a lot of questions at the list, but I have always found EEGLAB list as very friendly and a very expertized group. So, your advice will be highly appreciated to move forward in my work.<u></u><u></u></span></p>
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<span lang="EN-AU"> <u></u><u></u></span></p>
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<span lang="EN-AU">Best regards<u></u><u></u></span></p>
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<span lang="EN-AU">Imali<u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-AU"> <u></u><u></u></span></p>
<p class="MsoNormal"><b><span lang="EN-AU">Imali Thanuja Hettiarachchi</span></b><span lang="EN-AU"><u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-AU">PhD Candidate<u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-AU">Centre for Intelligent Systems research<u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-AU">Deakin University,
</span><span lang="EN-AU" style="font-size:10.0pt">Geelong 3217, Australia.</span><span lang="EN-AU"><u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-AU" style="font-size:10.0pt">Email:
<a href="mailto:ith@deakin.edu.au" target="_blank">ith@deakin.edu.au</a><br>
</span><span lang="EN-AU"><a href="http://www.deakin.edu.au/cisr" target="_blank">www.deakin.edu.au/cisr</a><u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-AU"> <u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-AU" style="font-size:9.0pt;font-family:"Helvetica","sans-serif""><img border="0" width="70" height="73" src="cid:image001.jpg@01CD90D2.26853B50" alt="Description: Description: Description: cid:1216BE20-1800-4A47-8B9F-E7B9D94831CD@deakin.edu.au"></span><span lang="EN-AU"><u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-AU" style="font-size:10.0pt;font-family:"Tahoma","sans-serif""> </span><span lang="EN-AU"><u></u><u></u></span></p>
<p class="MsoNormal" style="margin-bottom:12.0pt"><span lang="EN-AU"> <u></u><u></u></span></p>
<p class="MsoNormal"><span lang="EN-AU"> <u></u><u></u></span></p>
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<p class="MsoNormal"><span lang="EN-AU"><br>
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<p class="MsoNormal"><span lang="EN-AU" style="color:#888888"> <u></u><u></u></span></p>
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<p class="MsoNormal" style="margin-bottom:12.0pt"><span lang="EN-AU" style="color:#888888">--
<br>
Makoto Miyakoshi<br>
JSPS Postdoctral Fellow for Research Abroad<br>
Swartz Center for Computational Neuroscience<br>
Institute for Neural Computation, University of California San Diego<u></u><u></u></span></p>
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<br>
-- <u></u><u></u></p>
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<p class="MsoNormal"><span><span style="color:#888888">Stephen Politzer-Ahles</span></span><span style="color:#888888"><br>
<span>University of Kansas</span><br>
<span>Linguistics Department</span><br>
<span><a href="http://www.linguistics.ku.edu/" target="_blank">http://www.linguistics.ku.edu/</a></span></span><u></u><u></u></p>
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<p class="MsoNormal"><u></u> <u></u></p>
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<p class="MsoNormal" style="margin-bottom:12.0pt">-- <br>
Makoto Miyakoshi<br>
JSPS Postdoctral Fellow for Research Abroad<br>
Swartz Center for Computational Neuroscience<br>
Institute for Neural Computation, University of California San Diego<u></u><u></u></p>
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