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</o:shapelayout></xml><![endif]--></head><body lang=DA link="#0563C1" vlink="#954F72"><div class=WordSection1><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D;mso-fareast-language:EN-US'>Hi Ronald,<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D;mso-fareast-language:EN-US'><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D;mso-fareast-language:EN-US'>Depending on your specific application, I would just use PCA and then retain the 15 components with largest eigenvalues. Alternatively you could interpolate new channels from the old. <o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D;mso-fareast-language:EN-US'><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D;mso-fareast-language:EN-US'>Best,<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D;mso-fareast-language:EN-US'>Simon<o:p></o:p></span></p><p class=MsoNormal><a name="_MailEndCompose"><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D;mso-fareast-language:EN-US'><o:p> </o:p></span></a></p><div><div style='border:none;border-top:solid #E1E1E1 1.0pt;padding:3.0pt 0cm 0cm 0cm'><p class=MsoNormal><b><span style='font-size:11.0pt;font-family:"Calibri","sans-serif"'>Fra:</span></b><span style='font-size:11.0pt;font-family:"Calibri","sans-serif"'> eeglablist-bounces@sccn.ucsd.edu [mailto:eeglablist-bounces@sccn.ucsd.edu] <b>På vegne af </b>Anderson, Ronald C<br><b>Sendt:</b> 4. maj 2014 09:18<br><b>Til:</b> eeglablist@sccn.ucsd.edu<br><b>Emne:</b> [Eeglablist] Merging of Channel Time Series<o:p></o:p></span></p></div></div><p class=MsoNormal><o:p> </o:p></p><div><p class=MsoNormal><span style='font-size:10.5pt;font-family:"Calibri","sans-serif";color:black'>All:<o:p></o:p></span></p></div><div><p class=MsoNormal><span style='font-size:10.5pt;font-family:"Calibri","sans-serif";color:black'><o:p> </o:p></span></p></div><div><p class=MsoNormal><span style='font-size:10.5pt;font-family:"Calibri","sans-serif";color:black'>As part of an EEG time series analysis, our team would like to combine multiple channels of data into a single time series. As an example, taking 60 channels of EEG data and merging certain channels to make a set of 15 channels. Several analyses would be conducted on the merged data, including coherence, power, SL, and GC. I am writing to the EEGLAB list serve to see if anyone has suggestions for a best-practice method of integrating several channels into a representative time series. <o:p></o:p></span></p></div><div><p class=MsoNormal><span style='font-size:10.5pt;font-family:"Calibri","sans-serif";color:black'><o:p> </o:p></span></p></div><div><p class=MsoNormal><span style='font-size:10.5pt;font-family:"Calibri","sans-serif";color:black'>We thank you for any assistance you can provide. My apologies if this question seems simplistic or has already been addressed on the list serv. <o:p></o:p></span></p></div><div><p class=MsoNormal><span style='font-size:10.5pt;font-family:"Calibri","sans-serif";color:black'><o:p> </o:p></span></p></div><div><p class=MsoNormal><span style='font-size:10.5pt;font-family:"Calibri","sans-serif";color:black'>Regards,<o:p></o:p></span></p></div></div></body></html>