<div dir="ltr">Dear Jumana,<div><br></div><div>It's a bad idea to perform ICA with 0.1Hz high-pass filtered data. The cutoff frequency is too low. See this page and the referenced paper.</div><div><br></div><div><a href="https://sccn.ucsd.edu/wiki/Makoto%27s_preprocessing_pipeline#High-pass_filter_the_data_at_1-Hz_.28for_ICA.2C_ASR.2C_and_CleanLine.29">https://sccn.ucsd.edu/wiki/Makoto%27s_preprocessing_pipeline#High-pass_filter_the_data_at_1-Hz_.28for_ICA.2C_ASR.2C_and_CleanLine.29</a><br></div><div><br></div><div>> A 30Hz low pass does not help to get rid of the oscillation, which is really significant in the data.<br></div><div class="gmail_extra"><br></div><div class="gmail_extra">Check the channel frequency spectra and tell me if you see peaks in it. If necessary, you can cut it off using a designed low-pass filter (not like Butterworth...)</div><div class="gmail_extra"><br></div><div class="gmail_extra">> I use a butterworth filter, which is good for ERP analysis with low phase distortion.<br></div><div class="gmail_extra"><br></div><div class="gmail_extra">Do not make qualitative judgement just because something is NOT a classic Butterworth. Of course, if the attenuation is small, the phase 'distortion' is small. But if such small attenuation is not useful, it does not help at all! Also, be careful with the word 'phase'. Particularly people who do not know basics of signal processing believe phase as some magical thing. If you are not performing Granger Causality Analysis or something, you don't need to be so worried about phase issue in practice.</div><div class="gmail_extra"><br></div><div class="gmail_extra"><p class="MsoNormal">> I also already run ICA, but in some datasets there is a very significant high frequency oscillation.<u></u><u></u></p><div><br></div><div>Remember, to eliminate this is more important than being afraid of qualitative phase issue.</div></div><div class="gmail_extra"><br></div><div class="gmail_extra"><p class="MsoNormal">> However, I can see the high frequency oscillations in my ERP, which is not ideal and now I need to try and get rid of it further.<u></u><u></u></p><p class="MsoNormal">Can I filter again on top of the data which already has already undergone ICA- I only use ICA to remove blinks?</p></div><div class="gmail_extra"><br></div><div class="gmail_extra">You'd better to filter the data on continuous state. If you need to filter the epoched data, the half of filter length from both ends becomes unreliable.</div><div class="gmail_extra"><br></div><div class="gmail_extra"><p class="MsoNormal">> Should I do cleanline, although it would have to be after ICA now- I read this is not advisable.<u></u><u></u></p><p class="MsoNormal">> Should I use a notch filter?</p></div><div class="gmail_extra"><br></div><div class="gmail_extra">If you see > 20dB line noise, Cleanline may not help. In this case, I would simply apply a designed low-pass filter, either Hamming (-50dB) or Blackman (-70dB) using firfilt(). See 'Tools' -> 'Filter the data' -> 'Windowed sinc FIR filter'.</div><div class="gmail_extra"><br></div><div class="gmail_extra">There are different guys saying different things about data preprocessing. It is confusing, I know! The only good solution for this is to become an engineer yourself...</div><div class="gmail_extra"><br></div><div class="gmail_extra">Makoto</div><div class="gmail_extra"><br></div><div class="gmail_extra"><br></div><div class="gmail_extra"><br><div class="gmail_quote">On Tue, Jan 24, 2017 at 7:00 AM, Ahmad, Jumana <span dir="ltr"><<a href="mailto:jumana.ahmad@kcl.ac.uk" target="_blank">jumana.ahmad@kcl.ac.uk</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">
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<p class="MsoNormal">Hi Everyone,<u></u><u></u></p>
<p class="MsoNormal">I am running a large scale ERP analysis. I filtered 1-40Hz (ICA AMICA), or 0.1-40Hz for the ERP dataset. A 30Hz low pass does not help to get rid of the oscillation, which is really significant in the data. I use a butterworth filter, which
is good for ERP analysis with low phase distortion. <u></u><u></u></p>
<p class="MsoNormal">I also already run ICA, but in some datasets there is a very significant high frequency oscillation.<u></u><u></u></p>
<p class="MsoNormal">I do not use cleanline, which is not typical in the literature I have been basing my pipeline on.<u></u><u></u></p>
<p class="MsoNormal"><u></u> <u></u></p>
<p class="MsoNormal">However, I can see the high frequency oscillations in my ERP, which is not ideal and now I need to try and get rid of it further.
<u></u><u></u></p>
<p class="MsoNormal">Can I filter again on top of the data which already has already undergone ICA- I only use ICA to remove blinks?<u></u><u></u></p>
<p class="MsoNormal">Should I do cleanline, although it would have to be after ICA now- I read this is not advisable.<u></u><u></u></p>
<p class="MsoNormal">Should I use a notch filter?<u></u><u></u></p>
<p class="MsoNormal"><u></u> <u></u></p>
<p class="MsoNormal">Any help would be appreciated.<u></u><u></u></p>
<p class="MsoNormal">Best wishes,<u></u><u></u></p>
<p class="MsoNormal">Jumana <u></u><u></u></p>
<p class="MsoNormal"><u></u> <u></u></p>
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