<div>We're running ICA on a raw, epoched dataset. We've tried several different latency windows: 0, 0.5 and 1 second before S1 and 0, 0.5 and 1 second after S2.</div><br><div class="gmail_quote">On Tue, Sep 8, 2009 at 5:37 PM, Thomas Ferree <span dir="ltr"><<a href="mailto:tom.ferree@gmail.com">tom.ferree@gmail.com</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;">Are you computing ICA on the raw data or the averaged ERP?<br><br><div class="gmail_quote"><div><div class="h5">On Tue, Sep 8, 2009 at 12:01 PM, Keith Yoder <span dir="ltr"><<a href="mailto:kjyoder@gmail.com" target="_blank">kjyoder@gmail.com</a>></span> wrote:<br>
</div></div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div><div class="h5"><div>Hi all,<br></div><div>Our group has EEG time-series data collected with a BioSemi ActiveTwo 128-electrode cap. Our paradigm includes a Go-NoGo, with an alerting stimulus (S1) preceding the presentation of the Go-NoGo stimulus (S2). S1 and S2 are separated by 3 seconds. When we examine ERPs from single electrodes, we observe a typical contingent negative variation (CNV). However, when we run ICA (runica), none of the components isolate the CNV. We've tried highpass filtering at 0.5hz (obviously to high), 0.01hz and without any highpass filtering, all without success. Has anyone else run into a similar problem? Does anyone have any additional advice for isolating a CNV with ICA?</div>
<div>Thanks,</div><div>Keith Yoder</div><div>--</div><font color="#888888"><div>Research Assistant</div><div>Belmonte Autism Lab</div><div>Cornell University</div>
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<br clear="all"><br>-- <br>Thomas Ferree, PhD<br>
Department of Radiology<br>UT Southwestern Medical Center<br>Email: <a href="mailto:tom.ferree@gmail.com" target="_blank">tom.ferree@gmail.com</a><br>Voice: (214) 648-9767<br>
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