Dear Imali,<div><br></div><div>ICA returns 'one map/IC per a component' which does not change across recording time.</div><div>A static location corresponds to a brain region.</div><div>If you think of averaged ERP topo, for example, scalp topography changes from timepoint to timepoint. Independent components are not like that.</div>
<div><br></div><div>> 2.<span style="font-size:7pt;font-family:'Times New Roman'"> </span><u></u>Do independent components for cognitive activity in brain represents ERP components(P1,N1, etc)?</div><div>
<br></div><div>Not necessarily. One IC can explain 3 ERP peaks (P1/N1/P2 as one burst).</div><div><br></div><div>> 3.<span style="font-size:7pt;font-family:'Times New Roman'"> </span><u></u>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?</div>
<div><br></div><div>How do I know my dipole location is correct? </div><div>When you calculate dipole fit, you'll have residual variance. If this value is small, that means your dipole location is good.</div><div>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). </div>
<div><br></div><div>> 4.<span style="font-size:7pt;font-family:'Times New Roman'"> </span><u></u>With very limited neuroscience knowledge how do I get around with localisations to extract a task related neuronal activity?</div>
<div><br></div><div>If you don't have time to read Scott Makeig, Arnaud Delorme, or Julie Onton etc, then</div><div>1. run ICA</div><div>2. run dipfit (autofit)</div><div>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).</div>
<div><br></div><div>If you have further questions please ask further.</div><div><br></div><div>Makoto<br><div><br><div class="gmail_quote">2012/8/31 IMALI THANUJA HETTIARACHCHI <span dir="ltr"><<a href="mailto:ith@deakin.edu.au" target="_blank">ith@deakin.edu.au</a>></span><br>
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<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">
<u></u><span>1.<span style="font:7.0pt "Times New Roman"">
</span></span><u></u>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">
<u></u><span>2.<span style="font:7.0pt "Times New Roman"">
</span></span><u></u>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">
<u></u><span>3.<span style="font:7.0pt "Times New Roman"">
</span></span><u></u>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">
<u></u><span>4.<span style="font:7.0pt "Times New Roman"">
</span></span><u></u>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>
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<p class="MsoNormal"><b><span style="font-family:"Times New Roman","serif"">Imali Thanuja Hettiarachchi<u></u><u></u></span></b></p>
<p class="MsoNormal"><span style="font-family:"Times New Roman","serif"">PhD Candidate<u></u><u></u></span></p>
<p class="MsoNormal"><span style="font-family:"Times New Roman","serif"">Centre for Intelligent Systems research<u></u><u></u></span></p>
<p class="MsoNormal"><span style="font-family:"Times New Roman","serif"">Deakin University,
</span><span style="font-size:10.0pt;font-family:"Times New Roman","serif"">Geelong 3217, Australia.<u></u><u></u></span></p>
<p class="MsoNormal"><span style="font-size:10.0pt;font-family:"Times New Roman","serif"">Email:
<a href="mailto:ith@deakin.edu.au" target="_blank"><span style="color:blue">ith@deakin.edu.au</span></a><br>
</span><span style="font-family:"Times New Roman","serif""><a href="http://www.deakin.edu.au/cisr" target="_blank"><span style="color:blue">www.deakin.edu.au/cisr</span></a><u></u><u></u></span></p>
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<p class="MsoNormal"><span style="font-size:9.0pt;font-family:"Helvetica","sans-serif""><img border="0" width="70" height="73" src="cid:image001.jpg@01CD878D.D0157CA0" alt="Description: Description: Description: cid:1216BE20-1800-4A47-8B9F-E7B9D94831CD@deakin.edu.au"></span><span style="font-size:10.0pt;font-family:"Tahoma","sans-serif""><u></u><u></u></span></p>
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-- <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<br><br>
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