Hi Frank, <div><br></div><div>One way to do this (without changing the color of the channel labels on the y-axis)<div>is to examine the "indelec" output from the channel rejection function. See help for that function below.</div>
<div>Turning them red on the y-axis would invovle taking the indelec output and changing the color</div><div>of those specific electrode</div><div>Another option is to show fewer channels at a time.</div><div>As long as you've filtered or removed baseline on all channels, </div>
<div>you should be able to view sub-group of channels with ease, easily detecting which ones have been marked.</div><div><br></div><div><br></div><div>the following lines run channel artifact detection, save the output variables, and spits out to the screen</div>
<div>the numbers of the channels that were detected. I have set it so it creates a new variable containing</div><div>the EEG with removed channels. The second line just outputs one of the output variables that contains</div>
<div>the numbers of the detected channels.</div><div><br></div><div>[OUTEEG, indelec] = pop_rejchan(EEG, 'elec',[1:EEG.nbchan] ,'threshold',3,'norm','on','measure','kurt');</div>
<div><br></div><div>indelec</div><div><br></div><div><br></div><div><br></div><div><br></div><div><div>>> help pop_rejchan</div><div> pop_rejchan() - reject artifacts channels in an EEG dataset using joint </div><div>
probability of the recorded electrode.</div><div> </div><div> Usage:</div><div> >> pop_rejchan( INEEG ) % pop-up interative window mode</div><div> >> [OUTEEG, locthresh, globthresh, nrej] = ...</div>
<div> <span class="Apple-tab-span" style="white-space:pre"> </span>= pop_rejchan( INEEG, 'key', 'val');</div><div> </div><div> Inputs:</div><div> INEEG - input dataset</div><div> </div><div> Optional inputs:</div>
<div> 'elec' - [n1 n2 ...] electrode number(s) to take into </div><div> consideration for rejection</div><div> 'threshold' - [max] absolute thresold or activity probability </div>
<div> limit(s) (in std. dev.) if norm is 'on'.</div><div> 'measure' - ['prob'|'kurt'] compute probability 'prob' or kurtosis 'kurt'</div><div> for each channel. Default is 'kurt'.</div>
<div> 'norm' - ['on'|'off'] normalize measure above (using trimmed </div><div> normalization as described in the function jointprob()</div><div> and rejkurt(). Default is 'off'.</div>
<div> 'precomp' - [float array] use this array instead of computing the 'prob' </div><div> or 'kurt' measures.</div><div> </div><div> Outputs:</div><div> OUTEEG - output dataset with updated joint probability array</div>
<div> indelec - indices of rejected electrodes</div><div> measure - measure value for each electrode</div><div><br></div><div><br></div><div><br></div><div><br></div><div><br></div><div><br></div><br><div class="gmail_quote">
On Wed, Nov 28, 2012 at 10:41 AM, Frank Preston <span dir="ltr"><<a href="mailto:ffpresto@uwaterloo.ca" target="_blank">ffpresto@uwaterloo.ca</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
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<p class="MsoNormal">Hi,<u></u><u></u></p>
<p class="MsoNormal"><u></u> <u></u></p>
<p class="MsoNormal">If Scroll Plot is opened after trials have been marked by EEGLab, the channel which caused the trial to be marked is highlighted in red. We would like to know which channel is marked and it is often very difficult to tell because the plotted
signal is outside of range by quite a bit. Is there an easy way to tell this, perhaps by highlighting the channel on the y-axis?<u></u><u></u></p>
<p class="MsoNormal"><u></u> <u></u></p>
<p class="MsoNormal">We are viewing results from a BioSemi Active 2 system. We record 72 electrodes, 66 of which are on the cap.<u></u><u></u></p>
<p class="MsoNormal"><u></u> <u></u></p>
<p class="MsoNormal">Thank you,<u></u><u></u></p>
<p class="MsoNormal"> .. Frank<span class="HOEnZb"><font color="#888888"><u></u><u></u></font></span></p><span class="HOEnZb"><font color="#888888">
<p class="MsoNormal"><u></u> <u></u></p>
<p class="MsoNormal"><u></u> <u></u></p>
<p class="MsoNormal"><span style="font-size:12.0pt">-- <br>
<b><span style="color:#c00000">Frank Preston</span></b><br>
Psychophysiology Lab Technician University of Waterloo<br>
PAS 2270, Psychology Department 200 University Ave. W.<br>
Phone: <a href="tel:519-888-4567%20x%2038976" value="+15198884567" target="_blank">519-888-4567 x 38976</a> Waterloo, Ontario, N2L 3G1<u></u><u></u></span></p>
<p class="MsoNormal"><u></u> <u></u></p>
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