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Hi Jeremy,
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<div class="">Consider yourself backed up by the entire fieldtrip community to tell your supervisors (or the powers that are, who told you to downsample first) that you are going to reverse the order of things, and first do all the filtering/epoching/etc. and
only downsample afterwards. This will make your life much easier. I’d be happy to hear about good arguments why downsampling should be done first.</div>
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</div>
<div class="">Best wishes,</div>
<div class=""><br class="">
</div>
<div class="">Jan-Mathijs<br class="">
<div><br class="">
<blockquote type="cite" class="">
<div class="">On 19 Jul 2019, at 13:07, Jeremy Pulmano <<a href="mailto:jpulmano@princeton.edu" class="">jpulmano@princeton.edu</a>> wrote:</div>
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<div class="">Sadly, no that doesn't work. I am still getting approximately 1800 trials with an epoch length of 64 samples and 200 trials with an epoch length of 63. Additionally, I've run into extra complications because some trials after downsampling now
have the same start and/or end sample indices; this raises error messages later on.</div>
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<div class="">I might just bite the bullet and epoch first then downsample. But if you have any other solutions I would love to try them!</div>
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<div class="">Thanks!</div>
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<div dir="ltr" class="gmail_attr">On Fri, Jul 19, 2019 at 12:00 PM Stephen Whitmarsh <<a href="mailto:stephen.whitmarsh@gmail.com" class="">stephen.whitmarsh@gmail.com</a>> wrote:<br class="">
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<div class="">Hi Jeremy,</div>
<div dir="auto" class=""><br class="">
</div>
<div dir="auto" class="">A quick reply on your first question during lunch: round(trl/8+0.5)?</div>
<div dir="auto" class=""><br class="">
</div>
<div dir="auto" class="">Cheers,</div>
<div dir="auto" class="">s<br class="">
<br class="">
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<div dir="ltr" class="gmail_attr">On Fri, 19 Jul 2019, 12:35 Jeremy Pulmano, <<a href="mailto:jpulmano@princeton.edu" target="_blank" class="">jpulmano@princeton.edu</a>> wrote:<br class="">
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<div dir="ltr" class="">Hi Stephen,
<div class=""><br class="">
</div>
<div class="">Thank you, this is very helpful! However, I am encountering an issue when attempting to divide the cfg.trl by the same ratio (1024/128 = 8) and rounding them off as integers; this results in different sized epochs across trials. In my case, some
are 63 samples in length and others are 64 samples in length because of the rounding. Any ideas on how to avoid this? I was thinking that I can simply add one sample to those that become 63 in length but I'm worried that it will skew the data.</div>
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<div class="">In terms of the trial function, I have been doing some experimenting upon writing my own, but unfortunately, I've encountered a few roadblocks. First, the function ft_read_event only works with the original dataset and therefore only identifies
the epochs in the <b class="">raw</b> <b class="">data</b>. Thus, I cannot seem to find a way to identify the triggers in the downsampled data.</div>
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</div>
<div class="">In terms of your second point, yes it is definitely possible to resample after epoching. In my case, however, I have been instructed that downsampling
<i class="">before</i> epoching is the best practice for the dataset I am working with.</div>
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</div>
<div class="">Any further suggestions? Thanks again for your help.</div>
<div class="">J</div>
</div>
<br class="">
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<div dir="ltr" class="gmail_attr">On Thu, Jul 18, 2019 at 4:54 PM Stephen Whitmarsh <<a href="mailto:stephen.whitmarsh@gmail.com" rel="noreferrer" target="_blank" class="">stephen.whitmarsh@gmail.com</a>> wrote:<br class="">
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<div class="">Hi Jeremy,</div>
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<div class="">Yes, it seems likely that that would be the problem.</div>
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</div>
<div class="">I see a couple of solutions:</div>
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<div class="">1) Take your cfg.trl (trialdefinition which contains the start, end and offset sample) which you get out of ft_definetrial, and divide them with the same ratio as you did your data (and round them off to integers).</div>
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<div class="">2) Resample your trial data after epoching. Honestly not 100% sure this is supported, but only one way to find out :-)</div>
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<div class="">3a) Make your own trialfun*, i.e. function to create your own trl (trial definition), and that uses the appropriate samplerate (to be found in the datastructure field .fsample). An example on making your own trialfun can be found here:
<a href="http://www.fieldtriptoolbox.org/tutorial/preprocessing/" rel="noreferrer" target="_blank" class="">
http://www.fieldtriptoolbox.org/tutorial/preprocessing/</a>. You can also check <a href="http://www.fieldtriptoolbox.org/walkthrough/" rel="noreferrer" target="_blank" class="">
http://www.fieldtriptoolbox.org/walkthrough/</a></div>
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<div class="">3b) Use your fancy corrected trl in combination with ft_redefinetrial to epoch your resampled data.<br class="">
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<div class="">*) IMHO, creating your own trialfun pays off in the long run, as it allows you to be much flexible, and e.g. enter response times and those kind of things in extra columns in the .trl, which will then be carried trhough your data in a .trialinfo
field.</div>
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<div class="">Good fieldtripping!</div>
<div class="">Stephen<br class="">
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<div dir="ltr" class="gmail_attr">On Thu, 18 Jul 2019 at 16:59, Jeremy Pulmano <<a href="mailto:jpulmano@princeton.edu" rel="noreferrer" target="_blank" class="">jpulmano@princeton.edu</a>> wrote:<br class="">
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<div dir="ltr" class="">Hi Stephen,
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</div>
<div class="">Thanks so much for your reply. Apologies for the lack of specificity; what I meant to say is that out of 2000 trials, around 1500 of them contain NaNs after epoching. Thus, when I try visual artifact rejection, I only see 500 trials and the other
1500 are omitted completely.</div>
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<div class="">The NaNs appear after epoching. I think you're correct in identifying a mistake with the sampling rates. How can I specify the new sampling frequency in the trial definition? I think there might also be an issue because FieldTrip reads the old
sampling frequency from the headerfile (I am using Biosemi .bdf files).</div>
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</div>
<div class="">Here is a snippet of the code. I am also attaching it to this email for easier reference. Thanks again.</div>
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<div class="">
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%% Setup code (abridged)<br class="">
<br class="">
filename = 'example';<br class="">
header = ft_read_header(filename);<br class="">
new_fs = 128;<br class="">
prestim = 0.1;<br class="">
poststim = 0.4;<br class="">
trigger_codes = [ 1 2 3 ];<br class="">
<br class="">
%% High pass filter<br class="">
<br class="">
% Define trial for all the continuous data<br class="">
cfg = [];<br class="">
cfg.dataset = filename;<br class="">
cfg.headerfile = header;<br class="">
cfg.trialdef.triallength = Inf;<br class="">
cfg.trialdef.ntrials = 1; <br class="">
<br class="">
cfg = ft_definetrial(cfg);<br class="">
<br class="">
% Preprocess with high pass filter<br class="">
order = 100;<br class="">
cfg.hpfilter = 'yes';<br class="">
cfg.hpfilttype = 'fir';<br class="">
cfg.hpfreq = 0.1;<br class="">
cfg.hpfiltord = order;<br class="">
<br class="">
data = ft_preprocessing(cfg);<br class="">
data_hp = data;<br class="">
<br class="">
%% Downsampling<br class="">
<br class="">
fprintf('\nDownsampling\n');<br class="">
<br class="">
cfg = [];<br class="">
cfg.resamplefs = new_fs;<br class="">
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data = ft_resampledata(cfg, data);<br class="">
data_res = data;<br class="">
<br class="">
%% Epoch (NaNs appear after this block)<br class="">
<br class="">
% Now define the ACTUAL trial<br class="">
cfg = [];<br class="">
cfg.continuous = 'yes';<br class="">
cfg.dataset = filename; <br class="">
cfg.trialdef.prestim = prestim;<br class="">
cfg.trialdef.poststim = poststim;<br class="">
cfg.trialdef.eventtype = 'STATUS';<br class="">
cfg.trialdef.eventvalue = trigger_codes<br class="">
<br class="">
cfg = ft_definetrial(cfg);<br class="">
<br class="">
data = ft_redefinetrial(cfg, data);<br class="">
data_ep = data;<br class="">
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<div dir="ltr" class="gmail_attr">On Thu, Jul 18, 2019 at 3:06 PM Stephen Whitmarsh <<a href="mailto:stephen.whitmarsh@gmail.com" rel="noreferrer" target="_blank" class="">stephen.whitmarsh@gmail.com</a>> wrote:<br class="">
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<div class="">Dear Jeremy,</div>
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<div class="">Welcome to the FieldTrip community!</div>
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<div class="">Could you be more specific about "the data looks incorrect in the end.", and perhaps share a screenshot if informative? Sharing the relevant part of your script would be helpful too. For more info about how to get the best response to your questions,
please take a look at: <a href="http://www.fieldtriptoolbox.org/faq/how_to_ask_good_questions_to_the_community/" rel="noreferrer" target="_blank" class="">
http://www.fieldtriptoolbox.org/faq/how_to_ask_good_questions_to_the_community/</a>
</div>
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<div class="">Have you checked where the NaN's in the data are, and whether they appear before or after downsampling?</div>
<div class=""></div>
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<div class="">Just an shot in the dark, but have you perhaps defined your trials for epoching (i.e. the samples in the .trl) based on the old samplerate?</div>
<div class="">
<div class=""><br class="">
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<div class="">Cheers,</div>
<div class="">Stephen<br class="">
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<div dir="ltr" class="gmail_attr">On Thu, 18 Jul 2019 at 12:35, Jeremy Pulmano <<a href="mailto:jpulmano@princeton.edu" rel="noreferrer" target="_blank" class="">jpulmano@princeton.edu</a>> wrote:<br class="">
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Hi,
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<div class="">I've realized that the warning message often comes right after epoching (using ft_definetrial and then ft_redefinetrial). It seems like it successfully breaks the data into segments but still contains NaNs for whatever reason. Here are more details
about the pipeline so far:</div>
<div class="">
<ol class="">
<li style="margin-left:15px" class="">High pass filtering (0.1 Hz / FIR / order = 100)</li><li style="margin-left:15px" class="">Downsampling (1024 to 128 Hz)</li><li style="margin-left:15px" class="">Epoching (prestim 0.1, poststim 0.4)</li><li style="margin-left:15px" class="">Base-line correction [ -0.1 0 ]</li><li style="margin-left:15px" class="">Re-referencing (common avg.)</li><li style="margin-left:15px" class="">ICA / component rejection </li><li style="margin-left:15px" class="">Visual artifact removal</li><li style="margin-left:15px" class="">Low pass filter (30 Hz)</li></ol>
<div class="">Any further help would be greatly appreciated.</div>
</div>
<div class=""><br class="">
</div>
<div class="">Thanks,</div>
<div class="">Jeremy</div>
</div>
<br class="">
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<div dir="ltr" class="gmail_attr">On Wed, Jul 17, 2019 at 4:57 PM Jeremy Pulmano <<a href="mailto:jpulmano@princeton.edu" rel="noreferrer" target="_blank" class="">jpulmano@princeton.edu</a>> wrote:<br class="">
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<div class="">
<div dir="auto" class="">Hi Erika,</div>
</div>
<div dir="auto" class=""><br class="">
</div>
<div dir="auto" class="">The original sampling rate is 1024 Hz and the new sampling rate is 128 Hz.</div>
<div dir="auto" class=""><br class="">
</div>
<div dir="auto" class="">Thanks,</div>
<div dir="auto" class="">J</div>
<div class=""><br class="">
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<div dir="ltr" class="gmail_attr">On Wed, Jul 17, 2019 at 4:49 PM Erika Puiutta <<a href="mailto:erika.puiutta@uni-oldenburg.de" rel="noreferrer" target="_blank" class="">erika.puiutta@uni-oldenburg.de</a>> wrote:<br class="">
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<div class="">Hey J,</div>
<div class=""><br class="">
</div>
<div class="">this is just an educated guess since I don't really know how fieldtrip does the downsampling, but what is your sampling frequency and the sampling frequency you sample down to? Is it possible that your downsampling frequency is not a harmonic
of your original sampling frequency (say 1000Hz to 300Hz)? Maybe there are NaNs for the new samples where fieldtrip can't find a corresponding one from the old sampling frequency?</div>
<div class=""><br class="">
</div>
<div class="">Best of luck,</div>
<div class="">Erika</div>
</div>
<div dir="auto" class="">
<div class=""><br class="">
Am 17.07.2019 um 17:26 schrieb Jeremy Pulmano <<a href="mailto:jpulmano@princeton.edu" rel="noreferrer" target="_blank" class="">jpulmano@princeton.edu</a>>:<br class="">
<br class="">
</div>
<blockquote type="cite" class="">
<div class="">
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<div class="">Hi all,</div>
<div class=""><br class="">
</div>
<div class="">I am new to both neuroscience and FieldTrip and am trying to debug my preprocessing pipeline of EEG data (biosemi .bdf files). These are the current steps:</div>
<div class="">
<ol class="">
<li style="margin-left:15px" class="">High pass filtering</li><li style="margin-left:15px" class="">Downsampling</li><li style="margin-left:15px" class="">Epoching</li><li style="margin-left:15px" class="">Base-line correction</li><li style="margin-left:15px" class="">Re-referencing</li><li style="margin-left:15px" class="">ICA / component rejection</li><li style="margin-left:15px" class="">Visual artifact removal</li><li style="margin-left:15px" class="">Low pass filter (I save the low pass filter for the end so that ICA yields better time course plots).</li></ol>
<div class="">However, after the first three steps (high pass, downsample, epoch), I continue to get the warning message: "Warning: data contains NaN values, no filtering or preprocessing applied," starting at baseline correction. It repeats itself over and
over again. If I ignore these errors, the data looks incorrect in the end. Why does this happen, and how can I resolve this?</div>
</div>
<div class=""><br class="">
</div>
<div class="">Any tips would be appreciated.</div>
<div class=""><br class="">
</div>
<div class="">Thanks,</div>
<div class="">J</div>
</div>
</div>
</blockquote>
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<blockquote type="cite" class="">
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<td style="padding-left:15px" width="400" valign="top" class=""><font face="garamond, serif" class=""><font color="#222222" class=""><b class="">Jeremy Pulmano</b></font><br class="">
<span style="color:rgb(255,153,0)" class=""><b class="">Princeton University Class of 2021</b></span><font class=""><br class="">
B.S.E. Computer Science<br class="">
</font><font class="">e: <a href="mailto:jpulmano@princeton.edu" style="color:rgb(17,85,204)" rel="noreferrer" target="_blank" class="">jpulmano@princeton.edu</a> | c: (862) 220-5903</font></font></td>
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