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<br><br><div class="gmail_quote">On Wed, Sep 5, 2012 at 10:28 PM, IMALI THANUJA HETTIARACHCHI <span dir="ltr"><<a href="mailto:ith@deakin.edu.au" target="_blank">ith@deakin.edu.au</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
<div link="blue" vlink="purple" lang="EN-AU">
<div>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">Thank you very much Makoto, really appreciate your guidance and help.<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 style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">I have further some questions regarding ICA artifact rejection and localisation.<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 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 style="color:#376092">Pipeline
of processing to optimize ICA for artrifact removal</span><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#376092">’
</span><span 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?<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><u></u><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"><span>1.<span style="font:7.0pt "Times New Roman"">
</span></span></span><u></u><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)<u></u><u></u></span></p>
<p><u></u><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"><span>2.<span style="font:7.0pt "Times New Roman"">
</span></span></span><u></u><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">Reject unsuitable portions of data by visual inspection<u></u><u></u></span></p>
<p><u></u><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"><span>3.<span style="font:7.0pt "Times New Roman"">
</span></span></span><u></u><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)<u></u><u></u></span></p>
<p><u></u><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"><span>4.<span style="font:7.0pt "Times New Roman"">
</span></span></span><u></u><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">Extract epochs (without baseline removal???)<u></u><u></u></span></p>
<p><u></u><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"><span>5.<span style="font:7.0pt "Times New Roman"">
</span></span></span><u></u><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">Run ICA<u></u><u></u></span></p>
<p><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"><u></u> <u></u></span></p>
<p><span 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<u></u><u></u></i></b></span></p>
<p><span 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,<u></u><u></u></span></p>
<p><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"><u></u> <u></u></span></p>
<p><u></u><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"><span>6.<span style="font:7.0pt "Times New Roman"">
</span></span></span><u></u><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<u></u><u></u></span></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 <u></u><u></u></span></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>?<u></u><u></u></span></p>
<p><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"><u></u> <u></u></span></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.<u></u><u></u></span></p>
<p><u></u><b><i><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"><span>7.<span style="font:7.0pt "Times New Roman"">
</span></span></span></i></b><u></u><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?<b><i><u></u><u></u></i></b></span></p>
<p><u></u><b><i><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"><span>8.<span style="font:7.0pt "Times New Roman"">
</span></span></span></i></b><u></u><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?<b><i><u></u><u></u></i></b></span></p>
<p><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"><u></u> <u></u></span></p>
<p><b><i><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"><u></u> <u></u></span></i></b></p>
<p><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">Many thanks,<u></u><u></u></span></p>
<p><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d">Imali<u></u><u></u></span></p>
<p class="MsoNormal" style="margin-left:36.0pt"><b><i><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"><u></u> <u></u></span></i></b></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 style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"><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"><b><span style="font-size:10.0pt;font-family:"Tahoma","sans-serif"" lang="EN-US">From:</span></b><span style="font-size:10.0pt;font-family:"Tahoma","sans-serif"" lang="EN-US"> 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<u></u><u></u></span></p>
<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">ICA returns 'one map/IC per a component' which does not change across recording time.<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal">A static location corresponds to a brain region.<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal">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></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">> 2.<span style="font-size:7.0pt"> </span>Do independent components for cognitive activity in brain represents ERP components(P1,N1, etc)?<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">Not necessarily. One IC can explain 3 ERP peaks (P1/N1/P2 as one burst).<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">> 3.<span style="font-size:7.0pt"> </span>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></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">How do I know my dipole location is correct? <u></u><u></u></p>
</div>
<div>
<p class="MsoNormal">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></p>
</div>
<div>
<p class="MsoNormal">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></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">> 4.<span style="font-size:7.0pt"> </span>With very limited neuroscience knowledge how do I get around with localisations to extract a task related neuronal activity?<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">If you don't have time to read Scott Makeig, Arnaud Delorme, or Julie Onton etc, then<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal">1. run ICA<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal">2. run dipfit (autofit)<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal">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></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">If you have further questions please ask further.<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">Makoto<u></u><u></u></p>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
<div>
<p class="MsoNormal">2012/8/31 IMALI THANUJA HETTIARACHCHI <<a href="mailto:ith@deakin.edu.au" target="_blank">ith@deakin.edu.au</a>><u></u><u></u></p>
<div>
<div>
<p class="MsoNormal">Dear EEGLAB list,<u></u><u></u></p>
<p class="MsoNormal"> <u></u><u></u></p>
<p class="MsoNormal">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></p>
<p class="MsoNormal"> <u></u><u></u></p>
<p class="MsoNormal">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></p>
<p class="MsoNormal"> <u></u><u></u></p>
<p style="margin-left:20.25pt">1.<span style="font-size:7.0pt"> </span>Am I correct if I say that with BESA, dipoles can be fitted to individual components of the ERP waveform?
<u></u><u></u></p>
<p style="margin-left:20.25pt">2.<span style="font-size:7.0pt"> </span>Do independent components for cognitive activity in brain represents ERP components(P1,N1, etc)?
<u></u><u></u></p>
<p style="margin-left:20.25pt">3.<span style="font-size:7.0pt"> </span>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></p>
<p style="margin-left:20.25pt">4.<span style="font-size:7.0pt"> </span>With very limited neuroscience knowledge how do I get around with localisations to extract a task related neuronal activity?
<u></u><u></u></p>
<p class="MsoNormal" style="margin-left:2.25pt">
<u></u><u></u></p>
<p class="MsoNormal" style="margin-left:2.25pt">
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></p>
<p class="MsoNormal" style="margin-left:2.25pt">
<u></u><u></u></p>
<p class="MsoNormal" style="margin-left:2.25pt">
Best regards<u></u><u></u></p>
<p class="MsoNormal" style="margin-left:2.25pt">
Imali<u></u><u></u></p>
<p class="MsoNormal"> <u></u><u></u></p>
<p class="MsoNormal"><b>Imali Thanuja Hettiarachchi</b><u></u><u></u></p>
<p class="MsoNormal">PhD Candidate<u></u><u></u></p>
<p class="MsoNormal">Centre for Intelligent Systems research<u></u><u></u></p>
<p class="MsoNormal">Deakin University,
<span style="font-size:10.0pt">Geelong 3217, Australia.</span><u></u><u></u></p>
<p class="MsoNormal"><span style="font-size:10.0pt">Email:
<a href="mailto:ith@deakin.edu.au" target="_blank">ith@deakin.edu.au</a><br>
</span><a href="http://www.deakin.edu.au/cisr" target="_blank">www.deakin.edu.au/cisr</a><u></u><u></u></p>
<p class="MsoNormal"> <u></u><u></u></p>
<p class="MsoNormal"><span style="font-size:9.0pt;font-family:"Helvetica","sans-serif""><img src="cid:image001.jpg@01CD8C26.7CA73070" alt="Description: Description: Description: cid:1216BE20-1800-4A47-8B9F-E7B9D94831CD@deakin.edu.au" width="70" border="0" height="73"></span><u></u><u></u></p>
<p class="MsoNormal"><span style="font-size:10.0pt;font-family:"Tahoma","sans-serif""> </span><u></u><u></u></p>
<p class="MsoNormal" style="margin-bottom:12.0pt"><u></u> <u></u></p>
<p class="MsoNormal"> <u></u><u></u></p>
</div>
</div>
<p class="MsoNormal"><br>
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<p class="MsoNormal"><br>
<br clear="all">
<u></u><u></u></p>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<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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