<div dir="ltr">Thank you Mikolaj! Yes, I simultaneously discovered the EEG.CAT.Conn fields, which contain the data I am seeking. However, I don't know of an easy way to plot it.<div><br></div><div>What I've succeeded in doing is kind of a hack-path work around: I just take a duplicate version of one the datasets I'm using to generate the difference coherence, and overwrite the EEG.CAT.Conn.Coh (because in my case right now I'm looking at Complex Coherence) with the matrix-subtracted EEG.CAT.Conn.Coh 4-D matrix I just created. In other words (in case anyone else needs to do this)</div>
<div><br></div><div>coh_diff_Condition1_minus_Condition2 = EEG(2).CAT.Conn.Coh - EEG(1).CAT.Conn.Coh; </div><div><br></div><div>%%% This assumes both coherence matrices have the same dimensions, i.e. same number of windows.</div>
<div><br></div><div>%%% Then I take one of those EEG datasets, duplicate it as EEG(3).</div><div><br></div><div>EEG(3).CAT.Conn.Coh = coh_diff_Condition1_minus_Condition2; </div><div><br></div><div>%%% This I can then plot using the Time-Frequency Grid process in SIFT, and it works like a charm, although beware that any other connectivity measures that haven't been modified will still look the same as in the dummy dataset that I used to hold this difference coherence matrix, unless you replace those, too, with difference/subtraction values.</div>
<div><br></div><div>Thanks,</div><div><br>James</div></div><div class="gmail_extra"><br><br><div class="gmail_quote">On Wed, Feb 12, 2014 at 7:40 AM, Mikołaj Magnuski <span dir="ltr"><<a href="mailto:imponderabilion@gmail.com" target="_blank">imponderabilion@gmail.com</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><p dir="ltr">Hi James,</p>
<p dir="ltr">You can find all computed connectivity measures in EEG.CAT.Conn (although I am not sure why the field is named 'CAT' - it would be nice to know :) ).<br>
The matrices that reside there have the same names as method names that can be chosen in SIFT connectivity measures gui.<br>
For example EEG.CAT.Conn.nPDC contains a 4-d matrix of normalized partial directed coherence.<br>
The dimensions are component-component-time-frequency (the last two may be the other way around, I don't remember now).</p>
<p dir="ltr">(BTW "obliterate the putative "difference coherence" due to destructive interference." sounds really cool. :) Would make for good lyrics for a SIFT theme song maybe? )</p>
<div class="gmail_quote">7 lut 2014 22:32 "James Jones-Rounds" <<a href="mailto:jj324@cornell.edu" target="_blank">jj324@cornell.edu</a>> napisał(a):<br type="attribution"><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
<div><div class="h5">
<div dir="ltr">Hello all (and Tim),<div><br></div><div>I am a happy SIFT user and have found some exciting results measuring event-related complex coherence in certain frequency bands, between independent components, in a within-subject design using SIFT. My next step is to generate "difference" plots, i.e. the coherence (between two components) during one task (i.e. averaged epochs) subtracted from the coherence (between those same two components within the dataset, or between different components in another dataset) during another task.</div>
<div><br></div><div>I don't see an apparent way to do this in SIFT. Do you have any suggestions? </div><div><br></div><div>One idea I had was that if the coherence data existed in a matrix or structure field that SIFT generated, I could do a matrix-subtraction and then plot that resulting matrix. I wouldn't want to just matrix-subtract one set of raw frequency data from another, because I imagine that unless they're perfectly phase-locked (unlikely), that would obliterate the putative "difference coherence" due to destructive interference. I want to just matrix-subtract the coherence values (coherence power at each frequency, at each time point in the epochs) that's used to plot coherence using the "Visualization > Time-Frequency Grid" menu item in SIFT.</div>
<div><br></div><div>Thanks for your advice in advance, to any and all who can think of some!</div><div><br>James<br clear="all"><div><br></div>-- <br><div dir="ltr"><div>James Jones-Rounds</div>Laboratory Manager<br>Human Development EEG and Psychophysiology (HEP) Laboratory,<div>
Department of Human Development,<br>--------------------------------------------<br>Cornell University | Ithaca, NY<br></div><div><a href="tel:607-255-9883" value="+16072559883" target="_blank">607-255-9883</a></div><div>
<a href="mailto:eeg@cornell.edu" target="_blank">eeg@cornell.edu</a></div>
</div>
</div></div>
<br></div></div>_______________________________________________<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 href="mailto:eeglablist-unsubscribe@sccn.ucsd.edu" target="_blank">eeglablist-unsubscribe@sccn.ucsd.edu</a><br>
For digest mode, send an email with the subject "set digest mime" to <a href="mailto:eeglablist-request@sccn.ucsd.edu" target="_blank">eeglablist-request@sccn.ucsd.edu</a><br></blockquote></div>
</blockquote></div><br><br clear="all"><div><br></div>-- <br><div dir="ltr"><div>James Jones-Rounds</div>Laboratory Manager<br>Human Development EEG and Psychophysiology (HEP) Laboratory,<div>Department of Human Development,<br>
--------------------------------------------<br>Cornell University | Ithaca, NY<br></div><div>607-255-9883</div><div><a href="mailto:eeg@cornell.edu" target="_blank">eeg@cornell.edu</a></div></div>
</div>