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<div>Dear fieldtrip commity,</div>
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<div>I have a mat file containing raw EEG data with the following fields: start, length, values, times, interval, scale, offset, units, and units of measurement.<br>
They have no correlation with any common raw data.<br>
Do you think I could manually create a field trip structure?<br>
<br>
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<div><img alt="" aria-expanded="false" contextid="img362089" aria-haspopup="true" aria-owns="_ariaId_573" aria-flowto="_ariaId_573" style="" sizeoption="small" tabindex="0" width="370" height="180"></div>
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<div>In fact, I attempted to design it and ended up with a structure that contained the fields hdr, label, time, trial, fsampel, and sampleinfo.<br>
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"></span></div>
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<div>After I manually did the work of ft preprocessing() function, I wanted to epoch the data. To do this, I manually generated the 'trl' matrix by specifying the trial duration, however
<span>I got an error with ft_redefinetrial() function</span>:<br>
<br>
</div>
<div><b>"Unrecognized field name "dimord". Error in ft_redefinetrial (line 112) strcmp(data.dimord, 'rpt_chan_time') &&..."</b></div>
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"><br>
<br>
Thanks in advance,<br>
<br>
Hasnae AGOURAM<br>
<br>
</div>
<br>
<p></p>
</div>
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