<html><body bgcolor="#FFFFFF"><div>Dear Mahesh,</div><div><br></div><div>Let me understand something. In this kind of dataset ICA is running and the problem is with the regression part? If </div><div>so you can perform reg in smaller segments of ics... Also you are able to try another regression scheme based one a single step regression and not in adaptive filters...</div><div><br></div><div>Also watch your eog signals ... You have 4 channels but from these channels 2 bipolar signals<span class="Apple-style-span" style="-webkit-tap-highlight-color: rgba(26, 26, 26, 0.296875); -webkit-composition-fill-color: rgba(175, 192, 227, 0.230469); -webkit-composition-frame-color: rgba(77, 128, 180, 0.230469); "> are obtained which are going to be used as an input in every adaptive filter...</span></div><div><span class="Apple-style-span" style="-webkit-tap-highlight-color: rgba(26, 26, 26, 0.296875); -webkit-composition-fill-color: rgba(175, 192, 227, 0.230469); -webkit-composition-frame-color: rgba(77, 128, 180, 0.230469); "><br></span></div><div><span class="Apple-style-span" style="-webkit-tap-highlight-color: rgba(26, 26, 26, 0.296875); -webkit-composition-fill-color: rgba(175, 192, 227, 0.230469); -webkit-composition-frame-color: rgba(77, 128, 180, 0.230469); ">Everything you need About regica I am available for all of you in my e-mail or even better at Skype(mklados) you can also follow me at twitter (@mklados) where future versions of regica will be announced as well as many other artifact rejection and neuroscientific staff will be pointed</span></div><div><span class="Apple-style-span" style="-webkit-tap-highlight-color: rgba(26, 26, 26, 0.296875); -webkit-composition-fill-color: rgba(175, 192, 227, 0.230469); -webkit-composition-frame-color: rgba(77, 128, 180, 0.230469); "><br></span></div><div><span class="Apple-style-span" style="-webkit-tap-highlight-color: rgba(26, 26, 26, 0.296875); -webkit-composition-fill-color: rgba(175, 192, 227, 0.230469); -webkit-composition-frame-color: rgba(77, 128, 180, 0.230469); ">Sincerely yours</span></div><div><span class="Apple-style-span" style="-webkit-tap-highlight-color: rgba(26, 26, 26, 0.296875); -webkit-composition-fill-color: rgba(175, 192, 227, 0.230469); -webkit-composition-frame-color: rgba(77, 128, 180, 0.230469); ">Manousos Klados</span></div><div><span class="Apple-style-span" style="-webkit-tap-highlight-color: rgba(26, 26, 26, 0.296875); -webkit-composition-fill-color: rgba(175, 192, 227, 0.230469); -webkit-composition-frame-color: rgba(77, 128, 180, 0.230469); "><br></span></div><div><span class="Apple-style-span" style="-webkit-tap-highlight-color: rgba(26, 26, 26, 0.296875); -webkit-composition-fill-color: rgba(175, 192, 227, 0.230469); -webkit-composition-frame-color: rgba(77, 128, 180, 0.230469); ">P.S.</span></div><div><span class="Apple-style-span" style="-webkit-tap-highlight-color: rgba(26, 26, 26, 0.296875); -webkit-composition-fill-color: rgba(175, 192, 227, 0.230469); -webkit-composition-frame-color: rgba(77, 128, 180, 0.230469); "><br></span></div><div><span class="Apple-style-span" style="-webkit-tap-highlight-color: rgba(26, 26, 26, 0.296875); -webkit-composition-fill-color: rgba(175, 192, 227, 0.230469); -webkit-composition-frame-color: rgba(77, 128, 180, 0.230469); ">Which is Florian?</span></div><div><span class="Apple-style-span" style="-webkit-tap-highlight-color: rgba(26, 26, 26, 0.296875); -webkit-composition-fill-color: rgba(175, 192, 227, 0.230469); -webkit-composition-frame-color: rgba(77, 128, 180, 0.230469); "><br></span></div><div><span class="Apple-style-span" style="-webkit-tap-highlight-color: rgba(26, 26, 26, 0.296875); -webkit-composition-fill-color: rgba(175, 192, 227, 0.230469); -webkit-composition-frame-color: rgba(77, 128, 180, 0.230469); "><br></span></div><div>___________________________<div>Manousos Klados<br><div>PhD Candidate</div><div>Group of Applied Neuroscience </div><div>Lab of Medical Informatics</div><div>Medical School</div><div>Aristotle University of Thessaloniki</div><div>___________________________<br><div>iPhone</div></div></div></div><div><br>4 Απρ 2011, 11:10 μ.μ., ο/η Mahesh Casiraghi <<a href="mailto:mahesh.casiraghi@gmail.com">mahesh.casiraghi@gmail.com</a>> έγραψε:<br><br></div><div></div><blockquote type="cite"><div><font><font><font><font><font><p class="MsoNormal" style="color: rgb(255, 255, 255); font-family: verdana, sans-serif; font-size: small; "><span><span style="font-size:10.5pt;font-family:Constantia;color:#5F5F5F">Dear EEGLabbers,</span></span></p>
<p class="MsoNormal" style="color: rgb(255, 255, 255); font-family: verdana, sans-serif; font-size: small; "><span><span style="font-size:10.5pt;font-family:Constantia;color:#5F5F5F"><br></span></span></p><p class="MsoNormal" style="color: rgb(255, 255, 255); font-family: verdana, sans-serif; font-size: small; ">
<span><span style="font-size:10.5pt;font-family:Constantia;color:#5F5F5F">I am trying here to test if the hybrid methodology proposed by Florian and his group [</span></span><span class="Apple-style-span" style="color: rgb(255, 255, 255); font-family: verdana, sans-serif; "><a href="http://lomiweb.med.auth.gr/gan/mklados/index.php?option=com_k2&view=item&id=25:regica"><a href="http://lomiweb.med.auth.gr/gan/mklados/index.php?option=com_k2&view=item&id=25:regica">http://lomiweb.med.auth.gr/gan/mklados/index.php?option=com_k2&view=item&id=25:regica</a></a></span><span class="Apple-style-span" style="color: rgb(95, 95, 95); font-family: Constantia; font-size: 14px; ">] may be effective in removing eye-artifacts in an experiment where 10 secs epochs need to be segmented.</span></p>
<p class="MsoNormal" style="color: rgb(255, 255, 255); font-family: verdana, sans-serif; font-size: small; "><span class="Apple-style-span" style="color: rgb(95, 95, 95); font-family: Constantia; font-size: 14px; "><br></span></p>
<p class="MsoNormal"><font class="Apple-style-span" color="#5F5F5F" face="Constantia"><span class="Apple-style-span" style="font-size: 14px;">The concept of the methodology seems promising to me, but I am nonetheless a bit puzzled with respect to which regression algorithm might be adopted. When it comes to run the code on a real subject (512Hz sampling rate, continuous data, 64 EEG and 4 EOG chans, about 1.30 hours) LMS and CRLS become both unstable and fail after just few steps. H INF ew and tv algorithms, do that too. It seems to me the only option left is to make use of SCRLS_regression.m from the AAR toolbox, but as the relative documentation suggests, the function is not really optimized for fast computation, and the reg procedure seems to take ages to converge [running it in matlab 64, on a 4cores pc, for a 1.30 hours continuous EEG and it is still trying to converge after 23 hours of computation, just one processor used].</span></font></p>
<p class="MsoNormal"><font class="Apple-style-span" color="#5F5F5F" face="Constantia"><span class="Apple-style-span" style="font-size: 14px;"><br></span></font></p><p class="MsoNormal"><font class="Apple-style-span" color="#5F5F5F" face="Constantia"><span class="Apple-style-span" style="font-size: 14px;">Question is: can someone out there with some experience with AAR toolbox and/or SCRLS algorithm provide some insights on how to play around with the 'lambda', 'sigma', and 'precision' fields of the opt structure so as to come up with a sufficiently accurate output in an acceptable amount of time? I was unable to find any detailed summary or list of practical guidelines/hints concerning these parameters. Furthermore, perhaps someone is aware of a more effective SRLS reg routine...</span></font></p>
<p class="MsoNormal"><font class="Apple-style-span" color="#5F5F5F" face="Constantia"><span class="Apple-style-span" style="font-size: 14px;"><br></span></font></p><p class="MsoNormal"><font class="Apple-style-span" color="#5F5F5F" face="Constantia"><span class="Apple-style-span" style="font-size: 14px;">Here the code I used to reshape the tri-dimensional chans x samps x trials matrix, run regica, and come back to the cleaned 3 dims matrix. As you see, opt parameters are default, with the exception of .20 instead of .25 for correlation threshold, note that srls is default here. </span></font></p>
<p class="MsoNormal"><font class="Apple-style-span" color="#5F5F5F" face="Constantia"><span class="Apple-style-span" style="font-size: 14px;"><br></span></font></p><p class="MsoNormal"><font class="Apple-style-span" color="#5F5F5F" face="Constantia"></font></p>
<p class="MsoNormal"><font class="Apple-style-span" color="#5F5F5F" face="Constantia"><span class="Apple-style-span" style="font-size: 14px;"> EEG2DIM.data = reshape(EEG.data, size(EEG.data,1),size(EEG.data,3)*size(EEG.data,2));</span></font></p>
<p class="MsoNormal"><font class="Apple-style-span" color="#5F5F5F" face="Constantia"><span class="Apple-style-span" style="font-size: 14px;"> opt.EOG = [EEG2DIM.data(1,:);EEG2DIM.data((67:69),:)]; %Fp1(1) plus HEOG1, HEOG2, & VEOG</span></font></p>
<p class="MsoNormal"><font class="Apple-style-span" color="#5F5F5F" face="Constantia"><span class="Apple-style-span" style="font-size: 14px;"> opt.M=3;</span></font></p><p class="MsoNormal"><font class="Apple-style-span" color="#5F5F5F" face="Constantia"><span class="Apple-style-span" style="font-size: 14px;"> opt.lambda=0.9999;</span></font></p>
<p class="MsoNormal"><font class="Apple-style-span" color="#5F5F5F" face="Constantia"><span class="Apple-style-span" style="font-size: 14px;"> opt.sigma=0.01;</span></font></p><p class="MsoNormal"><font class="Apple-style-span" color="#5F5F5F" face="Constantia"><span class="Apple-style-span" style="font-size: 14px;"> opt.prec=50;</span></font></p>
<p class="MsoNormal"><font class="Apple-style-span" color="#5F5F5F" face="Constantia"><span class="Apple-style-span" style="font-size: 14px;"> opt.crittype = 'correlation';</span></font></p><p class="MsoNormal"><font class="Apple-style-span" color="#5F5F5F" face="Constantia"><span class="Apple-style-span" style="font-size: 14px;"> opt.corthr = 20;</span></font></p>
<p class="MsoNormal"><font class="Apple-style-span" color="#5F5F5F" face="Constantia"><span class="Apple-style-span" style="font-size: 14px;"> [EEG1] = regica(EEG2DIM.data((1:64),:),opt);</span></font></p><p class="MsoNormal">
<font class="Apple-style-span" color="#5F5F5F" face="Constantia"><span class="Apple-style-span" style="font-size: 14px;"> [EEG2] = reshape(EEG1, size(EEG1,1), size(EEG.data,2)/size(EEG.data,3), size(EEG.data,3));</span></font></p>
<font class="Apple-style-span" color="#5F5F5F" face="Constantia"><span class="Apple-style-span" style="font-size: 14px;"> EEG.data((1:64),:) = EEG2((1:64),:);</span></font><p></p><p class="MsoNormal"><font class="Apple-style-span" color="#5F5F5F" face="Constantia"><span class="Apple-style-span" style="font-size: 14px;"><br>
</span></font></p><p class="MsoNormal"><font class="Apple-style-span" color="#5F5F5F" face="Constantia"><span class="Apple-style-span" style="font-size: 14px;">Any insight would be really appreciated,</span></font></p><p class="MsoNormal">
<font class="Apple-style-span" color="#5F5F5F" face="Constantia"><span class="Apple-style-span" style="font-size: 14px;"><br></span></font></p><p class="MsoNormal"><font class="Apple-style-span" color="#5F5F5F" face="Constantia"><span class="Apple-style-span" style="font-size: 14px;">Mahesh</span></font></p>
<p class="MsoNormal"><font class="Apple-style-span" color="#5F5F5F" face="Constantia"><span class="Apple-style-span" style="font-size: 14px;"><br></span></font></p><p class="MsoNormal"><font class="Apple-style-span" color="#5F5F5F" face="Constantia"><span class="Apple-style-span" style="font-size: 14px;"> </span></font></p>
</font></font></font></font></font><div style="text-align:right"><span style="font-family:verdana, sans-serif;font-size:x-small"><font color="#C0C0C0"><br></font></span></div><div style="text-align:right"><span style="font-family:verdana, sans-serif;font-size:x-small"><font color="#C0C0C0"><br>
</font></span></div><div style="text-align:right"><span style="border-collapse:collapse"><div style="font-size:13px;font-family:arial, sans-serif"><font><span style="font-size:x-small"><font face="verdana, sans-serif" color="#999999">Mahesh M. Casiraghi</font></span></font></div>
<div style="font-size:13px;font-family:arial, sans-serif"><span style="font-size:x-small"><font face="verdana, sans-serif" color="#999999">PhD candidate - Cognitive Sciences</font></span></div><div><font size="1" face="verdana, sans-serif" color="#999999">Roberto Dell'Acqua Lab, University of Padova</font></div>
<div><font size="1" face="verdana, sans-serif" color="#999999">Pierre Jolicoeur Lab, Univesité de Montréal</font></div><div style="color:rgb(192, 192, 192)"><font size="1" face="verdana, sans-serif"><a href="mailto:mahesh.casiraghi@umontreal.ca" target="_blank"><a href="mailto:mahesh.casiraghi@umontreal.ca">mahesh.casiraghi@umontreal.ca</a></a></font></div>
</span></div><div style="text-align:right"><font size="1" face="verdana, sans-serif" color="#C0C0C0"><br></font></div><div style="text-align:right"><font size="1" face="verdana, sans-serif" color="#999999">I have the conviction that when Physiology will be far enough advanced, the poet, the philosopher, and the physiologist will all understand each other.</font></div>
<div style="text-align:right"><font size="1" face="verdana, sans-serif" color="#999999">Claude Bernard</font></div><div style="text-align:right"><font color="#CCCCCC" face="constantia, 'hoefler text', 'palatino linotype', serif" size="1"><span style="border-collapse:collapse;line-height:24px"><br>
</span></font></div><br>
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