<div dir="ltr"><div>Dear Srinivas,</div><div><br></div>> Highpass filter the data at 1HZ . Do I need to do this if I use clean_rawdata?<div><br></div><div>clean_rawdata() has a high-pass filter so if you like how it works you don't need to run eegfiltnew().</div><div><br></div><div>> should I use clean_artifacts with selected options? Any recommendations?<br><div class="gmail_extra"><br></div><div class="gmail_extra">Try it with several parameter combinations until you feel confident with it. As I wrote, in our unpublished study ASR with SD==20 showed the best. Compare SD==20 and SD==4 to see how the results differ.</div><div class="gmail_extra"><br></div><div class="gmail_extra">Makoto</div><div class="gmail_extra"><br><div class="gmail_quote">On Thu, Nov 13, 2014 at 3:07 PM, Srinivas Kota <span dir="ltr"><<a href="mailto:svkota@gmail.com" target="_blank">svkota@gmail.com</a>></span> wrote:<br><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"><div dir="ltr">Hello Christian and Makoto:<div><br></div><div>Would pipeline for preprocessing would be</div><div><br></div><div>Import Data and channel information</div><div>Highpass filter the data at 1HZ . Do I need to do this if I use clean_rawdata? or should I use clean_artifacts with selected options? Any recommendations?</div><div><br></div><div>Srinivas<br><div class="gmail_extra"><br><div class="gmail_quote">On Thu, Nov 13, 2014 at 9:07 AM, Srinivas Kota <span dir="ltr"><<a href="mailto:svkota@gmail.com" target="_blank">svkota@gmail.com</a>></span> wrote:<br><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"><div dir="ltr">Hello Tarik:<div><br></div><div>Thanks for the detailed information. The pipeline for ASR would be</div><div><br></div><div>import data</div><div> remove line noise using clean line</div><div>High-pass filter the data at 1Hz (Do we need to do this, because ASR includes a high pass filter arg_highpass?)</div><div>Import channel information</div><div>ASR</div><div>Remove bad channels (channel replacement if necessary?)</div><div>Re-reference the data to average</div><div>Epoch data </div><div>Reject epochs for cleaning</div><div><br></div><div><br></div><div>Best</div><span><font color="#888888"><div>Srinivas</div></font></span><div><div class="h5"><div><div><div><br></div><div><br></div><div><br></div><div><br></div><div class="gmail_extra"><br><div class="gmail_quote">On Wed, Nov 12, 2014 at 8:52 PM, Tarik S Bel-Bahar <span dir="ltr"><<a href="mailto:tarikbelbahar@gmail.com" target="_blank">tarikbelbahar@gmail.com</a>></span> wrote:<br><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"><div dir="ltr"><div style="color:rgb(51,51,153)">Hello Srinivas, hoping the below is of use to you, cheers!</div><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)">ASR is a cool tool! You may use it by installing it in eeglab as a plugin, running it from the gui on a continuous EEG file, and then typing eegh to get the eeglab history. Makoto might have something to add as he made the page, but the below should be useful to you.</div><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)"><span style="color:rgb(34,34,34)"><div style="color:rgb(51,51,153)">You can also find out more at the powerpoint from Christian and Makoto at:</div><div style="color:rgb(51,51,153)"><a href="http://sccn.ucsd.edu/wiki/EEGLAB_Extensions" target="_blank">http://sccn.ucsd.edu/wiki/EEGLAB_Extensions</a></div><div style="color:rgb(51,51,153)"><br></div></span></div><div style="color:rgb(51,51,153)"><span style="color:rgb(34,34,34)"><div style="color:rgb(51,51,153)">You can also download the matlab functions from there, and review the notes and examples given within the .m files. There is considerable information there.</div></span></div><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)">The change in the preprocessing pipeline suggested on the webpage would likely mean implementing ASR after importing channels.Because it removes bad channels, removes bad data, and gives you cleaned data, it's likely you can skip the other bad-channel and artifact-rejection steps. However, be sure to review the data for yourself after ASR, as it may require more cleaning, or adjustment of the parameters and running a second or different pass of artifact rejection using the same or other techniques. (however, the defaults work quite well for the methods mentioned at the very end of the pipeline webpage). <br></div><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)"><br></div></div><div class="gmail_extra"><br><div class="gmail_quote"><div><div>On Tue, Nov 11, 2014 at 6:48 PM, Srinivas Kota <span dir="ltr"><<a href="mailto:svkota@gmail.com" target="_blank">svkota@gmail.com</a>></span> wrote:<br></div></div><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"><div><div><div dir="ltr">I found this processing pipeline in EEGLAB wiki page. <div><br clear="all"><div><a href="http://sccn.ucsd.edu/wiki/Preprocess_pipeline" target="_blank">http://sccn.ucsd.edu/wiki/Preprocess_pipeline</a></div><div><br></div><div>What would be the preprocessing pipeline, if I like to try ASR? <br></div><div><br></div><div><br></div><div><br></div><div>Best,</div><div>Srinivas</div>
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</blockquote></div><br><br clear="all"><div><br></div>-- <br><div class="gmail_signature"><div dir="ltr">Makoto Miyakoshi<br>Swartz Center for Computational Neuroscience<br>Institute for Neural Computation, University of California San Diego<br></div></div>
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