<html><head></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space; "><div>My apologies, I think I may have been a bit unclear about the aims of collecting the data.</div><div>We're aiming to measure saccadic onset from the signal on a per-trial basis.</div><div>I was hoping to isolate the MRI noise "component" and subtract this from the EOG signal component</div><div>to give a cleaner EOG signal.</div><div><br></div><div>Can the ICA module be applied in the temporal domain in this fashion?</div><div>There are 40 single session trials of 6 seconds each, I would have thought that'd be enough data to</div><div>give it a try. Also open to any suggestions as to other adaptive filter techniques....</div><div><br></div><div>Thanks</div><div><br></div><div><div>On 17/06/2011, at 8:37 AM, Rodolphe Nenert wrote:</div><br class="Apple-interchange-newline"><blockquote type="cite">Im still afraid that the power of this analysis will be very low.<div>Maybe you can try an ICA on your fMRI data and try to correlate each component with your EOG timecourse.</div><div><br></div><div>Rodolphe N.<br><br><div class="gmail_quote">
On Thu, Jun 16, 2011 at 1:16 PM, <a href="mailto:frank@greenant.net">frank@greenant.net</a> <span dir="ltr"><<a href="mailto:fieldtrip@greenant.net">fieldtrip@greenant.net</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;">
<div style="word-wrap:break-word"><div>It's a bit of a unique experiment, we're trying to use an ECG machine</div><div>to acquire EOG, so it's only a single output channel.</div><div><br></div><div>i guess what I need is a temporal ICA rather than a spatial one...</div>
<div><div></div><div class="h5"><br><div><div>On 17/06/2011, at 2:48 AM, Rodolphe Nenert wrote:</div><br><blockquote type="cite">To summarize, the ICA will decompose your signal into as many components as Electrodes.<div>
Therefore, trying to decompose only one source is useless.</div><div>Did you use a full net of electrodes into your MRI machine or only EOG electrodes?</div>
<div><br></div><div>Hope this helps, </div><div><br></div><div>Rodolphe N.<br><br><div class="gmail_quote">On Thu, Jun 16, 2011 at 11:42 AM, <a href="mailto:frank@greenant.net" target="_blank">frank@greenant.net</a> <span dir="ltr"><<a href="mailto:fieldtrip@greenant.net" target="_blank">fieldtrip@greenant.net</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">I am trying to use fieldtrip to filter EOG data obtained in an MRI.<br>
I want to be able to spot the saccades in the samples and ideally measure their onset at the<br>
end of each trial.<br>
<br>
As you may guess, it's quite noisy and it's broad spectrum noise, despite pre-filtering.<br>
<br>
Ideally, I would like to isolate the component that corresponds to the MRI interference<br>
and then filter this out.<br>
<br>
I have managed to import the data and can run ft_componentanalysis<br>
but it fails with:<br>
<br>
runica() - data size (1,30720) too small<br>
<br>
My data is single channel, 40 epochs, each of 6 seconds (time locked to stim onset but not saccade onset)<br>
Is there a different method I should be using?<br>
<br>
I have posted some sample data and the current script (which reads in the<br>
data and runs preprocessing) to the following urls:<br>
<br>
<a href="http://greenant.net/temp/1_2_MRI_2011-04-29%2016:19:33.mat" target="_blank">http://greenant.net/temp/1_2_MRI_2011-04-29%2016:19:33.mat</a><br>
<a href="http://greenant.net/temp/EOG_analysis.m" target="_blank">http://greenant.net/temp/EOG_analysis.m</a><br>
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