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</o:shapelayout></xml><![endif]--></head><body lang=EN-US link=blue vlink=purple><div class=WordSection1><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:black'>Steve,<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:black'><o:p> </o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:black'>Thanks for the reference. It seems in this work you simulated ERP epochs, and filtered the epochs? I am referring to using a 1 Hz filter (sharp, about 1024 taps) on the continuous data before epoching. Do you find a similar difference in ERP amplitude in this case?<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:black'><o:p> </o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:black'>Jason<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:black'><o:p> </o:p></span></p><div><div style='border:none;border-top:solid #B5C4DF 1.0pt;padding:3.0pt 0in 0in 0in'><p class=MsoNormal><b><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'>From:</span></b><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'> eeglablist-bounces@sccn.ucsd.edu [mailto:eeglablist-bounces@sccn.ucsd.edu] <b>On Behalf Of </b>Steve Luck<br><b>Sent:</b> Thursday, October 06, 2011 8:25 PM<br><b>To:</b> eeglablist@sccn.ucsd.edu<br><b>Subject:</b> Re: [Eeglablist] filters, ICA and erp<o:p></o:p></span></p></div></div><p class=MsoNormal><o:p> </o:p></p><div><p class=MsoNormal>Jason and Sara-<o:p></o:p></p></div><div><p class=MsoNormal><o:p> </o:p></p></div><div><p class=MsoNormal>A 1-Hz high-pass cutoff is very likely to dramatically reduce the amplitude of late components like P3 and N400. To see an example of this, take a look at Figure 7 in Kappenman & Luck (2010, Psychophysiology), which shows the effects of various high-pass cutoffs on P3 amplitude. Not only does a 1-Hz cutoff reduce peak amplitude by over 50%, it also creates a spurious negative-going peak at the beginning of the waveform.<o:p></o:p></p></div><div><p class=MsoNormal><o:p> </o:p></p></div><div><p class=MsoNormal>I like David Groppe's suggestion of using epoched data with a fairly long epoch length and doing baseline correction as a type of high-pass filter.<o:p></o:p></p></div><div><p class=MsoNormal><o:p> </o:p></p></div><div><p class=MsoNormal>Steve<o:p></o:p></p></div><div><p class=MsoNormal><br><br><o:p></o:p></p><div><p class=MsoNormal><b><span style='font-size:13.5pt;font-family:"Helvetica","sans-serif"'>From: </span></b><span style='font-size:13.5pt;font-family:"Helvetica","sans-serif"'>Jason Palmer <<a href="mailto:japalmer29@gmail.com">japalmer29@gmail.com</a>></span><o:p></o:p></p></div><div><p class=MsoNormal><b><span style='font-size:13.5pt;font-family:"Helvetica","sans-serif"'>Date: </span></b><span style='font-size:13.5pt;font-family:"Helvetica","sans-serif"'>October 5, 2011 11:56:57 AM PDT</span><o:p></o:p></p></div><div><p class=MsoNormal><b><span style='font-size:13.5pt;font-family:"Helvetica","sans-serif"'>To: </span></b><span style='font-size:13.5pt;font-family:"Helvetica","sans-serif"'>'Sara Graziadio' <<a href="mailto:sara.graziadio@newcastle.ac.uk">sara.graziadio@newcastle.ac.uk</a>>, <<a href="mailto:eeglablist@sccn.ucsd.edu">eeglablist@sccn.ucsd.edu</a>></span><o:p></o:p></p></div><div><p class=MsoNormal><b><span style='font-size:13.5pt;font-family:"Helvetica","sans-serif"'>Subject: Re: [Eeglablist] filters, ICA and erp</span></b><o:p></o:p></p></div><div><p class=MsoNormal><b><span style='font-size:13.5pt;font-family:"Helvetica","sans-serif"'>Reply-To: </span></b><span style='font-size:13.5pt;font-family:"Helvetica","sans-serif"'><<a href="mailto:japalmer@ucsd.edu">japalmer@ucsd.edu</a>></span><o:p></o:p></p></div><p class=MsoNormal style='margin-bottom:12.0pt'><br><br>Hi Sara,<br><br>In my experience, using a sharp 1Hz high pass filter is best for ICA, and<br>doesn't significantly reduce ERP amplitude--the ERPs I know of are at least<br>2 Hz, so the 1Hz high pass shouldn't be a problem. The main issue is to<br>eliminate slow drifts in the data which make the mean non-stationary.<br><br>If you want to look at low frequencies specifically, you might do low pass<br>filtering, or band pass between 0.1Hz and say 30 Hz, to try to remove high<br>frequency sources, leaving only the low frequency sources, but I doubt this<br>would improve ERP results over a ! Hz high-pass filter.<br><br>Average reference is also fine if you are doing ICA after. Spreading muscle<br>artifacts etc. to other channels is not a problem since ICA will remove the<br>muscle activity etc. and put it in a single source (usually).<br><br>After you do average reference, the data rank goes down by 1, so if you have<br>94 channels avg referenced, ICA should give you back 93 components/sources.<br><br>Hope this is helpful.<br><br>Jason<br><br>-----Original Message-----<br>From: <a href="mailto:eeglablist-bounces@sccn.ucsd.edu">eeglablist-bounces@sccn.ucsd.edu</a><br><a href="mailto:[mailto:eeglablist-bounces@sccn.ucsd.edu]">[mailto:eeglablist-bounces@sccn.ucsd.edu]</a> On Behalf Of Sara Graziadio<br>Sent: Wednesday, October 05, 2011 7:46 AM<br>To: <a href="mailto:eeglablist@sccn.ucsd.edu">eeglablist@sccn.ucsd.edu</a><br>Subject: [Eeglablist] filters, ICA and erp<br><br>Hello,<br>I would like just a suggestion about some data cleaning/analysis I am doing.<br>I am doing an ERP analysis and I want to clean my data first with the ICA.<br>In theory, though, I should not use an high-pass cutoff higher than 0.1 Hz<br>to not reduce the erp amplitude. On the other side the ICA does not work<br>well if the high-pass cutoff is lower than 0.5 Hz...what is then the best<br>method to apply? Has anybody tested how robust the ica is with a 0.1Hz<br>filter? <br>I have also another question: I am doing the analysis on 94 electrodes<br>referenced to Fz. I planned to average reference the data but actually there<br>is quite a large spread of noise on all the electrodes with this method<br>(muscular artefacts for example from the temporal electrodes). But actually<br>almost all the papers are using the average reference so I was surprised, am<br>I the only one having this problem of noise? Would not be better just to<br>keep the Fz reference and then perhaps to average the erps for every<br>different cortical area and do the analysis on these averaged erps?<br><br>Thank you very much<br><br>Best wishes <br><br>Sara Graziadio<br>Research Associate<br>Newcastle University<br><br><br><br>_______________________________________________<br>Eeglablist page: <a href="http://sccn.ucsd.edu/eeglab/eeglabmail.html">http://sccn.ucsd.edu/eeglab/eeglabmail.html</a><br>To unsubscribe, send an empty email to <a href="mailto:eeglablist-unsubscribe@sccn.ucsd.edu">eeglablist-unsubscribe@sccn.ucsd.edu</a><br>For digest mode, send an email with the subject "set digest mime" to<br><a href="mailto:eeglablist-request@sccn.ucsd.edu">eeglablist-request@sccn.ucsd.edu</a><br><br><br><br><br><o:p></o:p></p><div><p class=MsoNormal><b><span style='font-size:13.5pt;font-family:"Helvetica","sans-serif"'>From: </span></b><span style='font-size:13.5pt;font-family:"Helvetica","sans-serif"'>Sara Graziadio <<a href="mailto:sara.graziadio@newcastle.ac.uk">sara.graziadio@newcastle.ac.uk</a>></span><o:p></o:p></p></div><div><p class=MsoNormal><b><span style='font-size:13.5pt;font-family:"Helvetica","sans-serif"'>Date: </span></b><span style='font-size:13.5pt;font-family:"Helvetica","sans-serif"'>October 6, 2011 2:50:32 AM PDT</span><o:p></o:p></p></div><div><p class=MsoNormal><b><span style='font-size:13.5pt;font-family:"Helvetica","sans-serif"'>To: </span></b><span style='font-size:13.5pt;font-family:"Helvetica","sans-serif"'>'David Groppe' <<a href="mailto:david.m.groppe@gmail.com">david.m.groppe@gmail.com</a>>, "'japalmer29@gmail.com'" <<a href="mailto:japalmer29@gmail.com">japalmer29@gmail.com</a>></span><o:p></o:p></p></div><div><p class=MsoNormal><b><span style='font-size:13.5pt;font-family:"Helvetica","sans-serif"'>Cc: </span></b><span style='font-size:13.5pt;font-family:"Helvetica","sans-serif"'>"<a href="mailto:eeglablist@sccn.ucsd.edu">eeglablist@sccn.ucsd.edu</a>" <<a href="mailto:eeglablist@sccn.ucsd.edu">eeglablist@sccn.ucsd.edu</a>></span><o:p></o:p></p></div><div><p class=MsoNormal><b><span style='font-size:13.5pt;font-family:"Helvetica","sans-serif"'>Subject: Re: [Eeglablist] filters, ICA and erp</span></b><o:p></o:p></p></div><p class=MsoNormal><br><br>Hello,<br>Thanks for your suggestion. <br><br>As I was planning to do also a PSD analysis on the data I guess that to remove the mean is not the best method if it works as a non-selective high pass filter, am I right?<br><br>I am applying the PCA before applying the ICA to reduce the number of components. How the data rank would be modified in this case?<br>I have to admit that it never happened to me that the muscle artefact is put in a single source with the ICA. Usually it spreads on half of the components, is this only my experience? <br><br>Thanks again<br><br>Best wishes<br><br>Sara<br><br><br><br><o:p></o:p></p><p class=MsoNormal>-----Original Message-----<o:p></o:p></p><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>From: David Groppe <a href="mailto:[mailto:david.m.groppe@gmail.com]">[mailto:david.m.groppe@gmail.com]</a><o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>Sent: 05 October 2011 23:10<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>To: Sara Graziadio<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>Cc: <a href="mailto:eeglablist@sccn.ucsd.edu">eeglablist@sccn.ucsd.edu</a><o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>Subject: Re: [Eeglablist] filters, ICA and erp<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal><o:p> </o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>Hi Sara,<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal> I found that a good way to improve the performance of ICA for ERP<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>analysis is to<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>1) Epoch your data into one or two second chunks time locked to the<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>event of interest<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>2) Remove the mean of each epoch at each channel<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>3) Run ICA to remove artifacts<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>4) Use a standard pre-event time window to baseline your data<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>5) Compute your ERPs<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal><o:p> </o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>Removing the mean of each epoch acts as a crude high-pass filter.<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>It's not nearly as selective as a "true" high pass filter but it<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>doesn't distort the ERP waveforms as much either. Moreover we've<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>found that the procedure described above massively improves the<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>reliability of ICA when compared to standard ERP prestimulus<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>baselines:<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal><o:p> </o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>Groppe, D.M., Makeig, S., & Kutas, M. (2009) Identifying reliable<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>independent components via split-half comparisons. NeuroImage, 45<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>pp.1199-1211.<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal><o:p> </o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>Hope this helps,<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal> -David<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal><o:p> </o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal><o:p> </o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal><o:p> </o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>On Wed, Oct 5, 2011 at 10:46 AM, Sara Graziadio<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal><<a href="mailto:sara.graziadio@newcastle.ac.uk">sara.graziadio@newcastle.ac.uk</a>> wrote:<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>Hello,<o:p></o:p></p></blockquote></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>I would like just a suggestion about some data cleaning/analysis I am doing. I<o:p></o:p></p></blockquote></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>am doing an ERP analysis and I want to clean my data first with the ICA. In<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>theory, though, I should not use an high-pass cutoff higher than 0.1 Hz to not<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>reduce the erp amplitude. On the other side the ICA does not work well if the<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>high-pass cutoff is lower than 0.5 Hz...what is then the best method to apply?<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>Has anybody tested how robust the ica is with a 0.1Hz filter?<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>I have also another question: I am doing the analysis on 94 electrodes<o:p></o:p></p></blockquote></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>referenced to Fz. I planned to average reference the data but actually there is<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>quite a large spread of noise on all the electrodes with this method (muscular<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>artefacts for example from the temporal electrodes). But actually almost all<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>the papers are using the average reference so I was surprised, am I the only<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>one having this problem of noise? Would not be better just to keep the Fz<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>reference and then perhaps to average the erps for every different cortical<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>area and do the analysis on these averaged erps?<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal><o:p> </o:p></p></blockquote></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>Thank you very much<o:p></o:p></p></blockquote></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal><o:p> </o:p></p></blockquote></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>Best wishes<o:p></o:p></p></blockquote></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal><o:p> </o:p></p></blockquote></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>Sara Graziadio<o:p></o:p></p></blockquote></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>Research Associate<o:p></o:p></p></blockquote></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>Newcastle University<o:p></o:p></p></blockquote></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal><o:p> </o:p></p></blockquote></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal><o:p> </o:p></p></blockquote></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal><o:p> </o:p></p></blockquote></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>_______________________________________________<o:p></o:p></p></blockquote></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>Eeglablist page: <a href="http://sccn.ucsd.edu/eeglab/eeglabmail.html">http://sccn.ucsd.edu/eeglab/eeglabmail.html</a><o:p></o:p></p></blockquote></blockquote><blockquote 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</o:p></p></blockquote></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal><o:p> </o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal><o:p> </o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal><o:p> </o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>--<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>David Groppe, Ph.D.<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>Postdoctoral Researcher<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>North Shore LIJ Health System<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal>New Hyde Park, New York<o:p></o:p></p></blockquote><blockquote style='margin-top:5.0pt;margin-bottom:5.0pt'><p class=MsoNormal><a href="http://www.cogsci.ucsd.edu/~dgroppe/">http://www.cogsci.ucsd.edu/~dgroppe/</a><o:p></o:p></p></blockquote><p class=MsoNormal><br><br><br><br>_______________________________________________<br>eeglablist mailing list <a href="mailto:eeglablist@sccn.ucsd.edu">eeglablist@sccn.ucsd.edu</a><br>Eeglablist page: <a href="http://www.sccn.ucsd.edu/eeglab/eeglabmail.html">http://www.sccn.ucsd.edu/eeglab/eeglabmail.html</a><br>To unsubscribe, send an empty email to <a href="mailto:eeglablist-unsub@sccn.ucsd.edu">eeglablist-unsub@sccn.ucsd.edu</a><br>To switch to non-digest mode, send an empty email to <a href="mailto:eeglablist-nodigest@sccn.ucsd.edu">eeglablist-nodigest@sccn.ucsd.edu</a><o:p></o:p></p></div><p class=MsoNormal><o:p> </o:p></p><div><div><div><div><div><div><div><div><div><div><div><div><p class=MsoNormal><span style='font-size:9.0pt;font-family:"Helvetica","sans-serif";color:black'>--------------------------------------------------------------------<o:p></o:p></span></p></div><div><p class=MsoNormal><span style='font-size:9.0pt;font-family:"Helvetica","sans-serif";color:black'>Steven J. Luck, Ph.D.<o:p></o:p></span></p></div><div><p class=MsoNormal><span style='font-size:9.0pt;font-family:"Helvetica","sans-serif";color:black'>Director, Center for Mind & Brain<o:p></o:p></span></p></div><div><p class=MsoNormal><span style='font-size:9.0pt;font-family:"Helvetica","sans-serif";color:black'>Professor, Department of Psychology<o:p></o:p></span></p></div><div><p class=MsoNormal><span style='font-size:9.0pt;font-family:"Helvetica","sans-serif";color:black'>University of California, Davis<o:p></o:p></span></p></div><div><p class=MsoNormal><span style='font-size:9.0pt;font-family:"Helvetica","sans-serif";color:black'>Room 109<o:p></o:p></span></p></div><div><p class=MsoNormal><span style='font-size:9.0pt;font-family:"Helvetica","sans-serif";color:black'>267 Cousteau Place<o:p></o:p></span></p></div><div><p class=MsoNormal><span style='font-size:9.0pt;font-family:"Helvetica","sans-serif";color:black'>Davis, CA 95618<o:p></o:p></span></p></div><div><p class=MsoNormal><span style='font-size:9.0pt;font-family:"Helvetica","sans-serif";color:black'>(530) 297-4424<o:p></o:p></span></p></div><div><p class=MsoNormal><span style='font-size:9.0pt;font-family:"Helvetica","sans-serif";color:black'>E-Mail: <a href="mailto:sjluck@ucdavis.edu">sjluck@ucdavis.edu</a><o:p></o:p></span></p></div><div><p class=MsoNormal><span style='font-size:9.0pt;font-family:"Helvetica","sans-serif";color:black'>Web: <a href="http://mindbrain.ucdavis.edu/people/sjluck">http://mindbrain.ucdavis.edu/people/sjluck</a><o:p></o:p></span></p></div><div><p class=MsoNormal><span style='font-size:9.0pt;font-family:"Helvetica","sans-serif";color:black'>Calendar: <a href="http://www.google.com/calendar/embed?src=stevenjluck@gmail.com&ctz=America/Los_Angeles">http://www.google.com/calendar/embed?src=stevenjluck%40gmail.com&ctz=America/Los_Angeles</a><o:p></o:p></span></p></div><div><p class=MsoNormal><span style='font-size:9.0pt;font-family:"Helvetica","sans-serif";color:black'>--------------------------------------------------------------------<o:p></o:p></span></p></div><p class=MsoNormal><span style='font-size:9.0pt;font-family:"Helvetica","sans-serif";color:black'><br><br><o:p></o:p></span></p></div></div><p class=MsoNormal><span style='font-size:13.5pt;font-family:"Helvetica","sans-serif";color:black'><o:p> </o:p></span></p></div><p class=MsoNormal><span style='font-size:13.5pt;font-family:"Helvetica","sans-serif";color:black'><o:p> </o:p></span></p></div><p class=MsoNormal><span style='font-size:13.5pt;font-family:"Helvetica","sans-serif";color:black'><o:p> </o:p></span></p></div><p class=MsoNormal><span style='font-size:13.5pt;font-family:"Helvetica","sans-serif";color:black'><o:p> </o:p></span></p></div><p class=MsoNormal><span style='font-size:13.5pt;font-family:"Helvetica","sans-serif";color:black'><o:p> </o:p></span></p></div><p class=MsoNormal><span style='font-size:13.5pt;font-family:"Helvetica","sans-serif";color:black'><o:p> </o:p></span></p></div><p class=MsoNormal><span style='font-size:13.5pt;font-family:"Helvetica","sans-serif";color:black'><o:p> </o:p></span></p></div></div><p class=MsoNormal><o:p> </o:p></p></div><p class=MsoNormal><o:p> </o:p></p></div></body></html>