<html><head><meta http-equiv="Content-Type" content="text/html charset=iso-8859-1"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space; "><div><blockquote type="cite"><div class="gmail_extra"><div class="gmail_quote"><blockquote class="gmail_quote" style="margin: 0px 0px 0px 0.8ex; border-left-width: 1px; border-left-color: rgb(204, 204, 204); border-left-style: solid; padding-left: 1ex; position: static; z-index: auto; ">1: What does this option do?<br></blockquote></div></div></blockquote><div><br></div><div>When you compare ERSP, you sometimes want to subtract the same baseline in all conditions. </div><div>Otherwise the baseline could be very different, but this difference might not be visible when you subtract the two conditions.</div><div>Subtracting common baseline means that you take the average of the baseline for all ERSP, then subtract it to the two (or more) ERSPs.</div><div><br></div><blockquote type="cite"><div class="gmail_extra"><div class="gmail_quote"><blockquote class="gmail_quote" style="margin: 0px 0px 0px 0.8ex; border-left-width: 1px; border-left-color: rgb(204, 204, 204); border-left-style: solid; padding-left: 1ex; position: static; z-index: auto; ">2: What does it mean by 'assumes adictive baseline'?<br></blockquote></div></div></blockquote><div><br></div><div>There aare different ways to remove a common baseline. One is to subtract the baseline. Another one is to divide by the baseline to get a % of activity compared to baseline. Note that subtracting the baseline in (additive model) in log power space which is the default in EEGLAB at it is equivalent to dividing by the baseline power. The newtimef function help contains more detail about this (see 'basenorm' option for example).</div><div><br></div><div>Best,</div><div><br></div><div>Arno</div><div><br></div><br><blockquote type="cite"><div class="gmail_extra"><div class="gmail_quote"><blockquote class="gmail_quote" style="margin: 0px 0px 0px 0.8ex; border-left-width: 1px; border-left-color: rgb(204, 204, 204); border-left-style: solid; padding-left: 1ex; position: static; z-index: auto; ">
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Thank you in advance.<br>
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Bethel<br>
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</blockquote></div><br><br clear="all"><div><br></div>-- <br><div dir="ltr">Makoto Miyakoshi<br>Swartz Center for Computational Neuroscience<br>Institute for Neural Computation, University of California San Diego<br></div>
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