<div>8 channels is quite sparse, ICA and eye blink removal algorithms rely on relatively higher scalp coverage.</div><div>However because all your channels are frontal, ICA might be resolving correctly. Some examination of the ERP, EEG signal before/after blink IC removal, and comparison of no-blink vs. after blink-removal is warranted, but you just might be able to proceed, with caution...</div>
<div><br></div><div>some possible resources from goggle scholar below,</div><div>also to give you some ideas about how test the validity of what you're doing</div><div><br></div><div><br></div>16 electrodes...<br clear="all">
<span class="Apple-style-span" style="color:rgb(34,34,34);font-family:Arial,sans-serif;font-size:13px;line-height:16px"><h3 class="gs_rt" style="margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;border-top-width:0px;border-right-width:0px;border-bottom-width:0px;border-left-width:0px;border-style:initial;border-color:initial;font-weight:normal;font-size:16px">
<a href="http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5456864" style="color:rgb(17,34,204);text-decoration:underline">Automatic removal of <b style="color:rgb(17,34,204)">eye</b>-<b style="color:rgb(17,34,204)">blink </b>artifacts based on <b style="color:rgb(17,34,204)">ICA </b>and peak <b style="color:rgb(17,34,204)">detection </b>algorithm</a></h3>
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J Gao, P Lin, Y Yang, P Wang - Informatics in Control, …, 2010 - <a href="http://ieeexplore.ieee.org">ieeexplore.ieee.org</a></div></span>
<div><br></div><div>8 electrodes</div><div><span class="Apple-style-span" style="color:rgb(34,34,34);font-family:Arial,sans-serif;font-size:13px;line-height:16px"><h3 class="gs_rt" style="margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;border-top-width:0px;border-right-width:0px;border-bottom-width:0px;border-left-width:0px;border-style:initial;border-color:initial;font-weight:normal;font-size:16px">
<a href="http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5109381" style="color:rgb(17,34,204);text-decoration:underline"><b style="color:rgb(17,34,204)">Detection </b>and removal of ocular artifacts using Independent Component Analysis and wavelets</a></h3>
<div class="gs_a" style="margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;border-top-width:0px;border-right-width:0px;border-bottom-width:0px;border-left-width:0px;border-style:initial;border-color:initial;color:rgb(0,153,51)">
H Ghandeharion… - Neural Engineering, 2009. …, 2009 - <a href="http://ieeexplore.ieee.org">ieeexplore.ieee.org</a></div></span></div><div><br></div><div><span class="Apple-style-span" style="color:rgb(34,34,34);font-family:Arial,sans-serif;font-size:13px;line-height:16px"><h3 class="gs_rt" style="margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;border-top-width:0px;border-right-width:0px;border-bottom-width:0px;border-left-width:0px;border-style:initial;border-color:initial;font-weight:normal;font-size:16px">
<a href="http://www.springerlink.com/index/K033J730W37T1513.pdf" style="color:rgb(17,34,204);text-decoration:underline;outline-style:none;outline-width:initial;outline-color:initial">Analysis of Blind Source Separation Techniques for Eye Artifact Removal</a></h3>
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TH Aspiras, <a href="http://scholar.google.com/citations?user=JLhA4-8AAAAJ&hl=en&oi=sra" style="color:rgb(0,153,51);text-decoration:underline;white-space:nowrap">VK Asari</a> - Wireless Networks and Computational Intelligence, 2012 - Springer</div>
</span></div><div><br></div><span class="Apple-style-span" style="color:rgb(34,34,34);font-family:Arial,sans-serif;font-size:13px;line-height:16px"><h3 class="gs_rt" style="margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;border-top-width:0px;border-right-width:0px;border-bottom-width:0px;border-left-width:0px;border-style:initial;border-color:initial;font-weight:normal;font-size:16px">
<a href="http://onlinelibrary.wiley.com/doi/10.1111/j.1469-8986.2010.01015.x/full" style="color:rgb(17,34,204);text-decoration:underline;outline-style:none;outline-width:initial;outline-color:initial">Validation of <b style="color:rgb(17,34,204)">ICA </b>as a tool to remove eye movement artifacts from EEG/ERP</a></h3>
<div class="gs_a" style="margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;border-top-width:0px;border-right-width:0px;border-bottom-width:0px;border-left-width:0px;border-style:initial;border-color:initial;color:rgb(0,153,51)">
<a href="http://scholar.google.com/citations?user=pLlSTVgAAAAJ&hl=en&oi=sra" style="color:rgb(0,153,51);text-decoration:underline;white-space:nowrap">M Mennes</a>, H Wouters, B Vanrumste, L Lagae… - …, 2010 - Wiley Online Library</div>
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<br></div></span><span class="Apple-style-span" style="color:rgb(34,34,34);font-family:Arial,sans-serif;font-size:13px;line-height:16px"><h3 class="gs_rt" style="margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;border-top-width:0px;border-right-width:0px;border-bottom-width:0px;border-left-width:0px;border-style:initial;border-color:initial;font-weight:normal;font-size:16px">
<span class="gs_ctc" style="font-size:11px;font-weight:bold;color:rgb(17,34,204)"><span class="gs_ct1" style="display:inline">[HTML]</span></span> <a href="http://dx.plos.org/10.1371/journal.pone.0003004" style="color:rgb(17,34,204);text-decoration:underline">The correction of <b style="color:rgb(17,34,204)">eye blink </b>artefacts in the EEG: a comparison of two prominent methods</a></h3>
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S Hoffmann, M Falkenstein - PLoS One, 2008 - <a href="http://dx.plos.org">dx.plos.org</a></div><div class="gs_a" style="margin-top:0px;margin-right:0px;margin-bottom:0px;margin-left:0px;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;border-top-width:0px;border-right-width:0px;border-bottom-width:0px;border-left-width:0px;border-style:initial;border-color:initial;color:rgb(0,153,51)">
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<br></div></span><br><div class="gmail_quote">On Wed, Aug 29, 2012 at 12:09 AM, Yaseen Gerhold <span dir="ltr"><<a href="mailto:sunshineafterdusk@gmail.com" target="_blank">sunshineafterdusk@gmail.com</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">ICA-gurus<br><br>
<p class="MsoNormal">I have a low density montage, 8 channels over the
frontal and prefrontal regions. I want to know if it is feasible to use ICA in
this context for artifact correction, or is ICAs application limited to higher
density montages?</p><p class="MsoNormal"><br> </p>
<p class="MsoNormal">RUNICA appears to resolve all the eye-blink data into one
neat component on a trial run: One can see this in spatial (scalp maps),
frequency (fractal dimension) and time domain. My concern is that with only 8
components to resolve to, and limited spatial sampling (frontal region only),
important the cortical data may also be resolved to the artifactual component.</p><p class="MsoNormal"><br></p>
<p class="MsoNormal">Can someone please share any experience they have in this
context, or provide some theoretical guidance in terms of ICA performance under
such conditions?</p><span class="HOEnZb"><font color="#888888">
<br>Yaseen<br><br>
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