<div>Hello Eve,</div><div><br></div><div>Until you find the tools in question in BCIlab,</div><div><br></div><div>One way to do this is as follows, let the list know if you have success</div><div>with these simple steps.</div>
<div><br></div><div>1. Prepare your data (filtering, re-referencing, bad channel dropping, etc...) </div><div>up to the point that you are ready to remove "artifactual time periods".</div><div><br></div><div>2. use eeg_regepochs to make a series of "fake" contiguous epochs,</div>
<div>choosing an epoch size of your choice (.5 or 1 second).</div><div><br></div><div>3. run the epoch rejection tool of choice within eeglab, which will lead</div><div>to the dropping of some subset of the fake epochs from step 2.</div>
<div><div> [you may have to try several different methods,</div><div>and determine what works best for your data]</div></div><div><br></div><div>4. if you are happy with retained epochs</div><div>run ICA on this newly cleaned set of fake contiguous epochs.</div>
<div>Note that you need to feed ICA enough data, and preferably</div><div>only periods of time when the cognitive activity in question was occurring.</div><div>for example, don't include the minutes of data when nothing was going on,</div>
<div>or "in between" your experimental blocks.</div><div><br></div><div>5. Now, if you are happy with the ICA decomposition you get</div><div>apply your ICA decomposition to the continuous file</div><div>just before step 2 above.</div>
<div><br></div><div><br></div><div>6. At this point, you can make your "real" epochs based on </div><div>your true events, and again drop the artifactual epochs.</div><div>(for example, the epochs that have extreme values).</div>
<div>...and you should be able to move forward.</div><div><br></div><div>7. Note if you use AMICA from Jason Palmer, </div><div>it is possible for AMICA to discount artifactual periods via the "do_reject" flag.</div>
<div><br></div><div><br></div><div>Note: almost any method to remove artifactual periods from continuous data</div><div>will necessitate making "windows" within which the artifact detection method.</div><div>If you can learn to do it on your own, you could make fake epochs </div>
<div>via your own scripts, and then rejoin all the remaining epochs.</div><div><br></div><div><br></div><div><br></div><br>
<br><br><div class="gmail_quote">On Fri, Sep 21, 2012 at 3:43 PM, alotof eve <span dir="ltr"><<a href="mailto:alotof_tiger@yahoo.com" target="_blank">alotof_tiger@yahoo.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
<div><div style="font-size:12pt;font-family:times new roman,new york,times,serif"><div><br></div><div><span>Dear experts,</span></div><div style="font-style:normal;font-size:16px;background-color:transparent;font-family:times new roman,new york,times,serif">
<br><span></span></div><div style="font-style:normal;font-size:16px;background-color:transparent;font-family:times new roman,new york,times,serif"><span>I cannot find the function of </span>semi-automatic
detection of artifact for continuous data in BCIlab as Makoto
suggested. Any other way to do semi-automatic detection of artifact for
continuous data (before segment) off-line?<br><br>We do ICA but we want to do some artifact detection before it. <br></div><div style="font-style:normal;font-size:16px;background-color:transparent;font-family:times new roman,new york,times,serif">
<br></div><div style="font-style:normal;font-size:16px;background-color:transparent;font-family:times new roman,new york,times,serif">Many thanks,</div>Duo<div><br></div> <div style="font-family:times new roman,new york,times,serif;font-size:12pt">
<div style="font-family:times new roman,new york,times,serif;font-size:12pt"><div class="im"> <div dir="ltr"> <font face="Arial"> ----- Forwarded Message -----<br> <b><span style="font-weight:bold">From:</span></b> alotof eve <<a href="mailto:alotof_tiger@yahoo.com" target="_blank">alotof_tiger@yahoo.com</a>><br>
<b><span style="font-weight:bold">To:</span></b> "<a href="mailto:mmiyakoshi@ucsd.edu" target="_blank">mmiyakoshi@ucsd.edu</a>"
<<a href="mailto:mmiyakoshi@ucsd.edu" target="_blank">mmiyakoshi@ucsd.edu</a>> <br><b><span style="font-weight:bold">Cc:</span></b> "</font><font face="Arial"><font face="Arial"><a href="mailto:eeglablist@sccn.ucsd.edu" target="_blank">eeglablist@sccn.ucsd.edu</a></font>" <<a href="mailto:eeglablist@sccn.ucsd.edu" target="_blank">eeglablist@sccn.ucsd.edu</a>> <br>
<b><span style="font-weight:bold">Sent:</span></b> Friday, September 21, 2012 3:39 PM<br> <b><span style="font-weight:bold">Subject:</span></b> Re: [Eeglablist] A question on semi-automatic detection on continuous data<br>
</font> </div> <br>
</div><div><div><div style="font-size:12pt;font-family:times new roman,new york,times,serif"><div><span>Dear experts,</span></div><div style="font-style:normal;font-size:16px;background-color:transparent;font-family:times new roman,new york,times,serif">
<br><span></span></div><div style="font-style:normal;font-size:16px;background-color:transparent;font-family:times new roman,new york,times,serif"><span>I cannot find the function of </span>semi-automatic detection of artifact for continuous data in BCIlab as Makoto suggested. Any other way to do semi-automatic detection of artifact for continuous data (before segment) off-line?</div>
<div style="font-style:normal;font-size:16px;background-color:transparent;font-family:times new roman,new york,times,serif"><br></div><div style="font-style:normal;font-size:16px;background-color:transparent;font-family:times new roman,new york,times,serif">
Many thanks,</div><div style="font-style:normal;font-size:16px;background-color:transparent;font-family:times new roman,new york,times,serif">Duo<br></div><div><br></div> <div style="font-family:times new roman,new york,times,serif;font-size:12pt">
<div style="font-family:times new roman,new york,times,serif;font-size:12pt"><div class="im"> <div dir="ltr"> <font face="Arial"> <hr size="1"> <b><span style="font-weight:bold">From:</span></b> Makoto Miyakoshi <<a href="mailto:mmiyakoshi@ucsd.edu" target="_blank">mmiyakoshi@ucsd.edu</a>><br>
<b><span style="font-weight:bold">To:</span></b> alotof eve <<a href="mailto:alotof_tiger@yahoo.com" target="_blank">alotof_tiger@yahoo.com</a>> <br><b><span style="font-weight:bold">Cc:</span></b> "<a href="mailto:eeglablist@sccn.ucsd.edu" target="_blank">eeglablist@sccn.ucsd.edu</a>" <<a href="mailto:eeglablist@sccn.ucsd.edu" target="_blank">eeglablist@sccn.ucsd.edu</a>>; Christian Kothe <<a href="mailto:christiankothe@gmail.com" target="_blank">christiankothe@gmail.com</a>> <br>
<b><span style="font-weight:bold">Sent:</span></b> Thursday, September 20, 2012 7:55
AM<br> <b><span style="font-weight:bold">Subject:</span></b> Re: [Eeglablist] A question on semi-automatic detection on continuous data<br> </font> </div> <br></div><div><div class="h5">
Dear Duo,<br><br>BCIlab supports it. If you are interested in, please refer to BCIlab wiki.<br><a href="http://sccn.ucsd.edu/wiki/BCILAB" target="_blank">http://sccn.ucsd.edu/wiki/BCILAB</a><br>I also copy this to the developer of BCIlab, Christian Kothe, for comments.<br>
<br>Makoto<br><br>2012/9/19 alotof eve <<a rel="nofollow" href="mailto:alotof_tiger@yahoo.com" target="_blank">alotof_tiger@yahoo.com</a>>:<br>> Hello, experts,<br>><br>> I have a question on semi-automatic detection of artifact. I noticed that<br>
> when only the data is segmented, we can use semi-automatic method on tool<br>> panel. When the data is continuous, the automatic method is invalid. I am<br>> doing data analysis and I am asked to find a way to do automatic rejection<br>
> on continuous data. I wonder if there is any reason that EEGLab dosen't<br>> offer this function? Any suggestion on doing semi-automatic detection on<br>> continous data?<br>><br>>
Thanks,<br>> Duo<br>><br>>
_______________________________________________<br>> Eeglablist page: <a href="http://sccn.ucsd.edu/eeglab/eeglabmail.html" target="_blank">http://sccn.ucsd.edu/eeglab/eeglabmail.html</a><br>> To unsubscribe, send an empty email to <a rel="nofollow" href="mailto:eeglablist-unsubscribe@sccn.ucsd.edu" target="_blank">eeglablist-unsubscribe@sccn.ucsd.edu</a><br>
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<br>-- <br>Makoto Miyakoshi<br>JSPS Postdoctral Fellow for Research Abroad<br>Swartz Center for Computational Neuroscience<br>Institute for Neural Computation, University of California San Diego<br><br><br> </div></div></div>
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