Dear Baris,<div><br></div><div>In the study I had visually inspected the artifactual ICs, but in the plug in i provide two ways for the identification of the artifactual ICs. First Fractal Dimension [1] and second the correlation with the EOG signals. Regarding the EOGs, they are bipolar which is mentioned inside the manuscript. I report how they were extracted...Honestly I am not sure if it is correct to take monopolar EOGs. In this study I haven't included the EOG in the ICA, but in another study [2] I have compared the performance of artifact rejection when the signals are included during the ICA decomposition and when they are not... </div>
<div><br></div><div>Regarding you initial question, in my master thesis (which is in Greek) I have used PLV (phase locking value) in order to see the phase distortion intoduced by several regression-based, ICA-based and REGICA based artifact rejection techniques, but the results was the absolute zero, for all the techniques...You can check it by your self employing an estimator about the introduced error by the artifact rejection techniques you want to compare...</div>
<div><br></div><div>Regarding the connectivity... Althought now functional connectivity is one of my primary fields of interest I haven't tried to assess the performance of different artifact rejection techniques in cerebral networks...May be I'll do it in the future... </div>
<div><br></div><div><br></div><div><br></div><div>If you need anything else don't hesitate to contact with me :)</div><div>Manousos Klados</div><div><br></div><div>[1]
<a href="http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=4052205">http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=4052205</a> </div><div>[2]
<a href="http://www.sciencedirect.com/science/article/pii/S0304394011008421">http://www.sciencedirect.com/science/article/pii/S0304394011008421</a> <br><br><div class="gmail_quote">2012/2/21 Baris Demiral <span dir="ltr"><<a href="mailto:demiral.007@googlemail.com">demiral.007@googlemail.com</a>></span><br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">Hi Manousos,<br>
<br>
Thank you for pointing out the link, I am actually aware of your<br>
paper, and I think it is a good alternative to just taking out the<br>
artifactual ICs by visual inspection.<br>
I have some questions though:<br>
<br>
a) As I understand, you apply regression based correction on the<br>
artifactual ICs by using EOG channels. How do you decide which ICs are<br>
artifactual at the first place?<br>
<br>
b) Are the EOGs recorded as monopolar or bipolor? I assume they are<br>
monopolar. Does it matter?<br>
<br>
c) Do you include EOGs in the ICA?<br>
<br>
Overall, my question initially was theoretical, to asses how much<br>
impact such corrections have on phase information and connectivity.<br>
<br>
Thanks,<br>
Baris<br>
<div class="im"><br>
<br>
On Sat, Feb 18, 2012 at 2:21 PM, Manousos Klados <<a href="mailto:mklados@med.auth.gr">mklados@med.auth.gr</a>> wrote:<br>
> Dear Baris,<br>
><br>
> Check this out--><br>
</div>> <a href="http://www.sciencedirect.com/science/article/pii/S1746809411000061" target="_blank">http://www.sciencedirect.com/science/article/pii/S1746809411000061</a> Manousos,<br>
<div><div class="h5"><br>
<br>
><br>
> REGICA is a hybrid method combining the ICA with the regression-based<br>
> techniques, dealing with the known problems of both methodologies...<br>
><br>
> If you search the EEGLAB site you can find the REGICA plugin...<br>
><br>
> Best Regards<br>
><br>
> Manousos Klados<br>
><br>
> 2012/2/16 Baris Demiral <<a href="mailto:demiral.007@googlemail.com">demiral.007@googlemail.com</a>><br>
>><br>
>> Hi,<br>
>><br>
>> Here are the questions:<br>
>><br>
>> a) If we take out artifactual ICs (say, eye blinks), do the final<br>
>> sensor data loose their crucial phase information?<br>
>> b) If we apply linear regression based algorithms to exclude<br>
>> artifacts, will this influence the sensor level phase information?<br>
>> c) How do these two methods influence sensor based connectivity analysis?<br>
>> d) Which sensor-based connectivity measures are robust against volume<br>
>> conduction?<br>
>><br>
>> I favor source- and ICA-based multivariate connectivity analyses where<br>
>> you really do not need to take out ICs, but work on the components of<br>
>> interest.<br>
>> But, there are plenty of papers out there reporting only pairwise<br>
>> sensor connectivity while ignoring the effects of volume conduction<br>
>> and artifact correction.<br>
>><br>
>> Thanks,<br>
>> Baris<br>
>> --<br>
>> Ş. Barış Demiral, PhD.<br>
>> Department of Psychiatry<br>
>> Washington University<br>
>> School of Medicine<br>
>> 660 S. Euclid Avenue<br>
>> Box 8134<br>
>> Saint Louis, MO 63110<br>
>> Phone: <a href="tel:%2B1%20%28314%29%20747%201603" value="+13147471603">+1 (314) 747 1603</a><br>
>><br>
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><br>
><br>
><br>
><br>
> --<br>
> Manousos A. Klados<br>
> ________________________________________________<br>
> B.Sc Mathematics<br>
> M.Sc Medical Informatics<br>
> ________________________________________________<br>
> PhD Candidate -- Research Assistant<br>
> Group of Applied Neurosciences<br>
> Lab of Medical Informatics<br>
> School of Medicine<br>
> Aristotle University of Thessaloniki<br>
> P.O. Box 323 54124 Thessaloniki Greece<br>
> _________________________________________________<br>
> Tel: <a href="tel:%2B30-2310-999332" value="+302310999332">+30-2310-999332</a><br>
> Fax:<a href="tel:%2B30-2310-999263" value="+302310999263">+30-2310-999263</a><br>
> Website: <a href="http://lomiweb.med.auth.gr/gan/mklados" target="_blank">http://lomiweb.med.auth.gr/gan/mklados</a><br>
><br>
> ________________________________________________________________<br>
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><br>
<br>
<br>
<br>
--<br>
Ş. Barış Demiral, PhD.<br>
Department of Psychiatry<br>
Washington University<br>
School of Medicine<br>
660 S. Euclid Avenue<br>
Box 8134<br>
Saint Louis, MO 63110<br>
</div></div>Phone: +1 (314) 7477 1603<br>
</blockquote></div><br><br clear="all"><div><br></div>-- <br>Manousos A. Klados<div>________________________________________________<br><div><div>B.Sc Mathematics</div><div>M.Sc Medical Informatics</div><div>________________________________________________</div>
PhD Candidate -- Research Assistant<br>Group of Applied Neurosciences<br>Lab of Medical Informatics<br>School of Medicine<br>Aristotle University of Thessaloniki<br>P.O. Box 323 54124 Thessaloniki Greece<br>_________________________________________________<br>
Tel: +30-2310-999332<br>Fax:+30-2310-999263<br>Website: <a href="http://lomiweb.med.auth.gr/gan/mklados" target="_blank">http://lomiweb.med.auth.gr/gan/mklados</a><br><br>________________________________________________________________<br>
Δρώ γιατί Αντιδρώ: Δεν τυπώνω αυτό το mail γιατί προστατεύω το περιβάλλον.<br>Acting by Reacting: By not printing this e-mail I help protect the environment.<br>________________________________________________________________</div>
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