<div dir="ltr">Lipstick on a pig, eh? I can't stop laughing. Hopefully I can get enough interest with this project to get a better looking pig. Thanks for the link!<br></div><div class="gmail_extra"><br><br><div class="gmail_quote">
On Sun, Feb 16, 2014 at 11:27 PM, Tom Campbell <span dir="ltr"><<a href="mailto:tom_campbell75@hotmail.com" target="_blank">tom_campbell75@hotmail.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 dir="ltr">
<div dir="ltr"><font face="Times New Roman">Hi,<br> <br>The most serious noise issue concerns the electrodes. So the electronics are rather good at putting lipstick on a pig! The device has built-in filters, though additional offline filtering is an option. People use this device for BCI without offline filtering. It is possible to customise with better electrodes:<span style="line-height:200%;font-family:"Times New Roman","serif";font-size:12pt" lang="EN-GB"><u></u><a href="https://github.com/SmartphoneBrainScanner/smartphonebrainscanner2-hardware/blob/master/easycap/build_instructions.md" rel="nofollow" target="_blank">https://github.com/SmartphoneBrainScanner/smartphonebrainscanner2-hardware/blob/master/easycap/build_instructions.md</a><u></u></span><br>
<br>These may be of interest:<br> <br></font></div><p style="margin:0in 0in 0pt 0.25in;line-height:200%" dir="ltr"><span style="line-height:200%;font-family:"Times New Roman","serif";font-size:12pt" lang="EN-GB">Debener, S., Minow, F., Emkes, R., Gandras,
K. & de Vos, M. How about taking a low-cost, small, and wireless eeg for a
walk?. <i>Psychophysiology</i> <b>49</b> 1617</span><span style="line-height:200%;font-family:"Times New Roman","serif";font-size:12pt" lang="EN-GB">–</span><span style="line-height:200%;font-family:"Times New Roman","serif";font-size:12pt" lang="EN-GB">1621 doi:</span><a href="http://dx.doi.org/10.1111/j.1469-8986.2012.01471.x" target="_blank"><span style="line-height:200%;font-family:"Times New Roman","serif";font-size:12pt;text-decoration:none" lang="EN-GB"><font color="#0000ee">http://dx.doi.org/10.1111/j.1469-8986.2012.01471.x</font></span></a><span style="line-height:200%;font-family:"Times New Roman","serif";font-size:12pt" lang="EN-GB"> ( 2012) </span></p>
<p style="margin:0in 0in 0pt 0.25in;line-height:200%" dir="ltr"><span style="line-height:200%;font-family:"Times New Roman","serif";font-size:12pt" lang="EN-GB"><font face="Times New Roman"></font></span> </p>
<p style="margin:0in 0in 0pt 0.25in;line-height:200%" dir="ltr"><span style="line-height:200%;font-family:"Times New Roman","serif";font-size:12pt" lang="EN-GB"><u></u><u></u></span> </p><div dir="ltr">
<font face="Times New Roman">
</font></div><div dir="ltr"><font face="Times New Roman">T.<br><br></font><br></div><div dir="ltr"> </div><div dir="ltr"><br> <br></div><div dir="ltr"><hr>From: <a href="mailto:arno@salk.edu" target="_blank">arno@salk.edu</a><br>
Date: Fri, 14 Feb 2014 20:44:45 -0800<br>To: <a href="mailto:sharonjalene@gmail.com" target="_blank">sharonjalene@gmail.com</a><br>CC: <a href="mailto:eeglablist@sccn.ucsd.edu" target="_blank">eeglablist@sccn.ucsd.edu</a><br>
Subject: Re: [Eeglablist] (Too) long of an explanation and questions at the end<div><div class="h5"><br><br><div><blockquote><div dir="ltr"><div><b><span><span>1.<span style="line-height:normal;font-family:"Times New Roman";font-style:normal;font-variant:normal;font-weight:normal;font-size-adjust:none;font-stretch:normal">
</span></span></span></b><b>Should
I epoch the data before statistical analyses even though I am looking at the
differences between the Grand Average – within subjects?</b><br></div></div></blockquote><div>Yes, you need to extract data epochs to compute the grand average ERP. If you are computing the spectrum (based on the rest of your message), then epoch extraction is not necessary.</div>
<blockquote><div dir="ltr"><div><b><span><span>2.<span style="line-height:normal;font-family:"Times New Roman";font-style:normal;font-variant:normal;font-weight:normal;font-size-adjust:none;font-stretch:normal">
</span></span></span></b>I am HP filtering at 1Hz and using
Cleanline, automatic artifact rejection, visual artifact rejection.<span> </span>I have played with ICA component rejection,
but am not sure I have enough good data to do so. (I recorded pilot data on one
subject – I have 3 minutes of data for each condition and 14 electrodes).<span> </span><b>Is
there an optimal filtering method since I am using the EMOTIV?</b><br></div></div></blockquote><div>This is a very noisy system. To extract meaningful ICA components, the more filtering the better.</div><blockquote><div dir="ltr">
<div>
<b><span><span>a.<span style="line-height:normal;font-family:"Times New Roman";font-style:normal;font-variant:normal;font-weight:normal;font-size-adjust:none;font-stretch:normal">
</span></span></span></b>One of my committee said I should NOT filter
the data or remove artifacts since I am just looking for the Grand Average of
certain freq bands.<b><span> </span></b>Although I see his logic, I believe I should
still remove spurious data so that the mean is not skewed by muscle and other
artifacts… right?<br></div></div></blockquote><div>Yes, if you have strong drifts in your data or DC shifts, you will need to filter. Otherwise, it will ruin the whole spectrum.</div><blockquote><div dir="ltr">
<b><span><span>3.<span style="line-height:normal;font-family:"Times New Roman";font-style:normal;font-variant:normal;font-weight:normal;font-size-adjust:none;font-stretch:normal">
</span></span></span></b>I was able to create a STUDY.<span> </span>I saved separate data sets with the
electrodes of interest. I was able to run power spectrum channel stats as a 3
(conditions) X 2(Left and Right) ANOVA.<span>
</span>I saw the t-tests between conditions and the interaction.<span> </span><br>
<b><span><span>a.<span style="line-height:normal;font-family:"Times New Roman";font-style:normal;font-variant:normal;font-weight:normal;font-size-adjust:none;font-stretch:normal">
</span></span></span></b>Is the power spectrum giving me the average
of the specified freq range?<br></div></blockquote>Yes<br><blockquote><div dir="ltr"><div>
<b><span><span>b.<span style="line-height:normal;font-family:"Times New Roman";font-style:normal;font-variant:normal;font-weight:normal;font-size-adjust:none;font-stretch:normal">
</span></span></span></b>If I epoch the data, can I use Bootstrapping
instead of parametric or permutation?<br></div></div></blockquote><div><br></div>No, this is independent.<br><blockquote><div dir="ltr"><div>
<b><span><span>c.<span style="line-height:normal;font-family:"Times New Roman";font-style:normal;font-variant:normal;font-weight:normal;font-size-adjust:none;font-stretch:normal">
</span></span></span></b>How can I get the actual values, including
the p values, of the stats?<span> </span>I see the
option to show a table with statistics containing the median, mean, mode, etc.,
but it rarely populates and is inconsistent. IS that statcond – on?<br></div></div></blockquote><div>Look at the history and add output to the function that plot the STUDY spectrum (the function name is std_spec). This function will return the statistics (which are computed by statcond).</div>
<br><blockquote><div dir="ltr"><div>
<b><span><span>d.<span style="line-height:normal;font-family:"Times New Roman";font-style:normal;font-variant:normal;font-weight:normal;font-size-adjust:none;font-stretch:normal">
</span></span></span></b>If I show results from a bootsrap, what
statistical test was used to obtain the results? <br></div></div></blockquote><div>The t-value (paired or unpaired) or the F-value is computed. The bootstrap procedure randomly samples the data and allow EEGLAB to obtain confidence intervals for these values under the null hypothesis.</div>
<br><blockquote><div dir="ltr"><div>
<b><span><span>e.<span style="line-height:normal;font-family:"Times New Roman";font-style:normal;font-variant:normal;font-weight:normal;font-size-adjust:none;font-stretch:normal">
</span></span></span></b>Would I be better off using a ratio of Grand Average subtraction of the control from the FOCUS conditions. or pwelch in MATLAB -then dropping the data into SPSS for some non parametric analysis (WIlcoxon rank ordered)?<br>
</div></div></blockquote><div>Sure. You should try what you are comfortable with. The results should be similar. </div></div><br><div>Arno</div><br></div></div><div class="">_______________________________________________
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</blockquote></div><br><br clear="all"><br>-- <br><div dir="ltr"><font><font color="mediumblue" face="Georgia, Times New Roman, Times, Serif">Sharon Jalene<br>
<br>
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