<div dir="ltr">Dear Peter,<div><br></div><div>Try trimOutlier plugin to visualize your whole channel whole datapoints in figure.</div><div><a href="http://sccn.ucsd.edu/wiki/Plugin_list_process">http://sccn.ucsd.edu/wiki/Plugin_list_process</a><br>
</div><div>If you have an outlier, trimOutlier plot should show it to you.</div><div><br></div><div>Makoto</div></div><div class="gmail_extra"><br><br><div class="gmail_quote">2014-05-12 12:34 GMT-07:00 Iman M.Rezazadeh <span dir="ltr"><<a href="mailto:irezazadeh@ucdavis.edu" target="_blank">irezazadeh@ucdavis.edu</a>></span>:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">Hi Pete,<br>
In general ripples in Fourier transforms mean there are some sudden changes<br>
in the data for example the Fourier transform square wave is a Sinc wave (<br>
like a Guassian with a lot of ripples- Gibb's phenomena). Anyhow, could you<br>
try to filter your data with a low pass filter to see if you still see the<br>
sawtooth stuff?<br>
Best<br>
<span class="HOEnZb"><font color="#888888">Iman<br>
</font></span><div class="HOEnZb"><div class="h5"><br>
-----Original Message-----<br>
From: <a href="mailto:eeglablist-bounces@sccn.ucsd.edu">eeglablist-bounces@sccn.ucsd.edu</a><br>
[mailto:<a href="mailto:eeglablist-bounces@sccn.ucsd.edu">eeglablist-bounces@sccn.ucsd.edu</a>] On Behalf Of Bachman, Peter<br>
Sent: Monday, May 12, 2014 12:04 PM<br>
To: Matt Craddock; <a href="mailto:eeglablist@sccn.ucsd.edu">eeglablist@sccn.ucsd.edu</a><br>
Subject: Re: [Eeglablist] triangular / sawtooth / zig-zag pattern in<br>
spectral data<br>
<br>
Thanks, Matt! That would also explain why my results look fairly normal,<br>
after epoching (and demeaning), and other offline processing. I appreciate<br>
the suggestion.<br>
<br>
Thanks,<br>
Pete<br>
________________________________________<br>
From: Matt Craddock [<a href="mailto:matt.craddock@uni-leipzig.de">matt.craddock@uni-leipzig.de</a>]<br>
Sent: Monday, May 12, 2014 11:31 AM<br>
To: Bachman, Peter; <a href="mailto:eeglablist@sccn.ucsd.edu">eeglablist@sccn.ucsd.edu</a><br>
Subject: Re: [Eeglablist] triangular / sawtooth / zig-zag pattern in<br>
spectral data<br>
<br>
On 12/05/2014 18:53, Bachman, Peter wrote:<br>
> Hi everyone,<br>
><br>
><br>
> When I plot spectral data from continuous EEG, the resulting<br>
> Power-by-Frequency graph looks very strange. Specifically, starting<br>
> at about 5 Hz and continuing on to higher frequencies, the plots for<br>
> each channel have a repeating triangular, or sawtooth-like, or zig-zag<br>
shape.<br>
><br>
><br>
> Here is a Dropbox link to an image of representative data:<br>
> <a href="https://www.dropbox.com/s/lddxgzlti9m20vj/FFT_triangle_pattern.JPG" target="_blank">https://www.dropbox.com/s/lddxgzlti9m20vj/FFT_triangle_pattern.JPG</a><br>
><br>
><br>
> It looks like some kind of wacky filter has been applied, but the only<br>
> filter in the processing pipeline is a very conventional 0.16-100 Hz<br>
> bandpass.<br>
><br>
><br>
> The problem isn't a feature of the raw data itself, because opening<br>
> the same continuous data in different EEG analysis programs and<br>
> applying a FFT produces very normal looking spectra. This happens<br>
> across different versions of EEGLAB, Matlab, and Windows.<br>
><br>
><br>
> The continuous data were recorded using a Biosemi system and saved in<br>
> .bdf format.<br>
><br>
><br>
> Has anyone run into this before? I'd be very grateful for any<br>
suggestions.<br>
><br>
><br>
> Thanks!<br>
><br>
> Pete<br>
><br>
><br>
<br>
Hi Pete,<br>
<br>
This is typical with Biosemi. Here's an old post from Bradley Voytek about<br>
this very issue:<br>
<br>
<a href="http://sccn.ucsd.edu/pipermail/eeglablist/2008/002229.html" target="_blank">http://sccn.ucsd.edu/pipermail/eeglablist/2008/002229.html</a><br>
<br>
It's probably some sort of rounding error somewhere down the line. He<br>
suggests removing the mean from each channel during import. I tried that and<br>
it didn't solve the issue; I think sometimes demeaning based on the full<br>
continuous data might not work if there's an abrupt shift in offset<br>
somewhere in the data - the abrupt shift means the data either side of the<br>
shift isn't centred on zero as it should be after subtraction of the mean.<br>
Anyway, if you're planning on epoching the data, baseline correction will<br>
also solve the problem, in my experience.<br>
<br>
Cheers,<br>
Matt<br>
<br>
--<br>
Dr. Matt Craddock<br>
Research Fellow<br>
Institute of Psychological Sciences<br>
University of Leeds<br>
<br>
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</div></div></blockquote></div><br><br clear="all"><div><br></div>-- <br><div dir="ltr">Makoto Miyakoshi<br>Swartz Center for Computational Neuroscience<br>Institute for Neural Computation, University of California San Diego<br>
</div>
</div>