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</o:shapelayout></xml><![endif]--></head><body lang=EN-US link="#0563C1" vlink="#954F72"><div class=WordSection1><p class=MsoNormal>We have conducted a study assessing resting eeg in adults that were traumatized as children and wish to compare them to control subjects without such problems in their history. Our primary data to analyze is based on 64 ch eeg sampled at 2000 c/s over two separate recordings of 10 minutes in duration. This is resting eeg not erp data.<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>We wish to analyze these data for two primary questions. First, analyze ic’s and determine sources and compare the groups for differences in regions/sources. What would you suggest using for this? Study function? MPT? Other thoughts? <o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Next, we want to measure the difference between the groups in source derived connectivity. We focus on granger causality using PDC as our primary measure. We often use, on an individual level, a SIFT like application that does this. Suggestions would be welcome. Use SIFT for this group level analysis? Other ideas?<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Alternatively, we have thought of using graph theory measures but would prefer to do at the source level not channel. Any thoughts?<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Thanks,<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Rob Coben, PhD <o:p></o:p></p></div></body></html>