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<p class="MsoNormal"><font>I am proposing a project in Motor Control for my
thesis.<span> </span>My school does not have an EEG
presence. <span> </span>I
earned $$ to buy an EMOTIV research edition, extra electrodes, MATLAB and other
software, and a dedicated laptop.<span> </span>I
took a MATLAB course, attended the recent EEGLab workshop, and continue to work
through the tutorial and material from the workshop.<span> </span>I truly want to learn this technology and do
more research in Motor Control.<span> </span>What I
have to start with is the EMOTIV and EEGLab.<span>
</span>There are 2 Biomechanists on my committee who are looking at this with
interest for future projects – and better equipment.</font></p><font>
</font><p class="MsoNormal"><font> </font></p><font>
</font><p class="MsoNormal"><font><span> </span>I will be doing
60-second data collection periods in a Control and 2 different FOCUS Conditions
during an unstable balance task.<span>
</span>Additionally, I will be looking at the RMSE of postural sway between
conditions.<span> </span>I also intend to play
recorded focus instruction at 15 sec intervals to control for mind wandering
and to have a place to sync/mark the data for future ERP and ERSP
analyses.<span> </span>This far, I have been
processing it as continuous data.<span> </span>It has
been my intention compare 8-12Hz and 12-25Hz readings from the left and right
electrode arrays, the L & R <span> </span>frontal
array, and the L & R - TPO arrays. </font></p><font>
</font><p class="MsoNormal"><font> </font></p><font>
</font><p class="MsoNormal"><font>I have waited to post until I could ask reasonable
questions.<span> </span>First, I do understand that
looking at components instead of electrodes is much preferred, but to start, I
have opted to look at channels to keep it simple.<span> </span>I am in the unusual position of using
tech/software that no one here is familiar with, and I am learning it as fast
as I can...<span> </span>Whatever I do, I have to be
able to explain it clearly- rather teach it.<span>
</span>I am running into roadblocks, but it forces me to learn.</font></p><font>
</font><p class="MsoNormal"><font> </font></p><font>
</font><p class="" style><font><b><span><span>1.<span style="font-family:"Times New Roman";font-style:normal;font-variant:normal;font-weight:normal;line-height: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></font></p><font>
</font><p class="" style><font><b><span><span>2.<span style="font-family:"Times New Roman";font-style:normal;font-variant:normal;font-weight:normal;line-height: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></font></p><font>
</font><p class="" style="margin-left:1in"><font><b><span><span>a.<span style="font-family:"Times New Roman";font-style:normal;font-variant:normal;font-weight:normal;line-height: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?</font></p><font>
</font><p class="" style><font><b><span><span>3.<span style="font-family:"Times New Roman";font-style:normal;font-variant:normal;font-weight:normal;line-height: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></font></p><font>
</font><p class="" style="margin-left:1in"><font><b><span><span>a.<span style="font-family:"Times New Roman";font-style:normal;font-variant:normal;font-weight:normal;line-height: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?</font></p><font>
</font><p class="" style="margin-left:1in"><font><b><span><span>b.<span style="font-family:"Times New Roman";font-style:normal;font-variant:normal;font-weight:normal;line-height: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?</font></p><font>
</font><p class="" style="margin-left:1in"><font><b><span><span>c.<span style="font-family:"Times New Roman";font-style:normal;font-variant:normal;font-weight:normal;line-height: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?</font></p><font>
</font><p class="" style="margin-left:1in"><font><b><span><span>d.<span style="font-family:"Times New Roman";font-style:normal;font-variant:normal;font-weight:normal;line-height: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? </font></p><font>
</font><p class="" style="margin-left:1in"><font><b><span><span>e.<span style="font-family:"Times New Roman";font-style:normal;font-variant:normal;font-weight:normal;line-height: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)?</font></p>
<font>I am being encouraged to use as simple of methodology as possible for the thesis project. <br><br></font></div><div><br><div dir="ltr"><font><font color="mediumblue" face="Georgia, Times New Roman, Times, Serif">Sharon Jalene<br>
<br>
<font size="1"><a href="http://www.youregettingverysleepy.com/" target="_blank">www.youregettingverysleepy.com</a></font><span style="text-decoration:underline"></span><br>
<font size="1">office: 702-966-3010<br>
mobile: 303-908-8441<br></font></font></font><span style="color:rgb(0,0,255)"><b><font size="1"><span><br></span></font></b></span><div style="text-align:center"><div style="text-align:center"><span style="color:rgb(0,0,255)"><b><font size="1"><span><span style="background-color:rgb(255,255,255)"></span></span></font></b></span><font size="1"><b><span style="color:rgb(0,0,255)"><span style="background-color:rgb(255,255,255)"></span><span style="font-family:georgia,serif"><font size="1"><span style="background-color:rgb(243,243,243)"><span>If one dream should fall and break into a thousand pieces, never be afraid to pick one of those pieces </span></span></font></span></span></b></font><br>
<font size="1"><b><span style="color:rgb(0,0,255)"><span style="font-family:georgia,serif"><font size="1"><span style="background-color:rgb(243,243,243)"><span>and begin again.</span></span></font></span></span></b></font><br>
<font size="1"><b><span style="color:rgb(0,0,255)"><span style="font-family:georgia,serif"><font size="1"><span style="background-color:rgb(243,243,243)"><span>Flavia Weedn</span></span></font></span></span></b></font><br>
</div><font size="1"><b><span style="color:rgb(0,0,255)"><span style="font-family:georgia,serif"><font size="1"><span style="background-color:rgb(243,243,243)"><span></span></span></font></span></span></b></font></div><font size="1"><b><span style="color:rgb(0,0,255)"><span style="font-family:georgia,serif"><font size="1"><span style="background-color:rgb(243,243,243)"><span> <br>
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