<div dir="ltr"><div class="gmail_quote"><div dir="ltr" class="gmail_attr">Good Evening,<br></div><div dir="ltr"><div><br></div>I tried estimating the functional connectivity using different phase-based measures like PLV and wPLI_debiased. I tried testing the two measures using<i> cfg.output</i> set to either <i>'fourier' or</i> <i>'powandcsd' </i>as I have seen people implementing PLV with both. However, I am getting quite varying results using either of these on an EEG data saved in .set file loaded and run using the commands shown at the end of this question. <div><br></div><div>
Even though I think <i>'fourier'</i> is the right way to implement these, to test for the validity of it, I tested this on the artificial data created using the <i>ft_connectivitysimulation function</i> ( 3 channel, 200 Hz Fs, the same number of trials as EEG, default noise covariance and params as in the example). In this case however, I am getting the very same results using either output (off-diagonal elements are the same in either; diagonal elements are NAN in using powandcsd whereas 1 while using Fourier).</div><div><br><div><b><i>My question is mainly the following</i></b></div><div><u>1) Am I missing something while testing on EEG data? If not, why is there a discrepancy found while testing on EEG but not on the simulated data? </u><div><u>2) Is there any recommended instance of using 'powandcsd ' over 'fourier' in any of the connectivity measures?</u></div><div><br></div><div><div><br></div><div>% EEG sampled at 200 Hz, 60 channels with events. The epoching is fine as the ERP was validated after epoching. <br><div>data = ft_connectivitysimulation(cfg);<div><div>cfg = [];<br>cfg.channel = ['all']; <br>cfg.dataset = 'Dataset_Epochs.set';<br>cfg.trialfun = 'ft_trialfun_general'; % this is the default<br>cfg.trialdef.eventtype = 'trigger';<br>cfg.trialdef.eventvalue = 'Onset'; <br>cfg.trialdef.prestim = 0.2; % in seconds<br>cfg.trialdef.poststim = 0.6; % in seconds<br>cfg = ft_definetrial(cfg);<br>data= ft_preprocessing(cfg); </div><div><br></div><div><div><br></div><div>cfg = [];</div><div>cfg.pad = 'nextpow2'; <br>cfg.method = 'mtmfft';<br>cfg.taper = 'hanning';<br>cfg.output = 'fourier';; % Tried replacing this with powandcsd and both yielded different results<br>cfg.keeptrials = 'yes'<br>cfg.tapsmofrq = 1;<br>spectral_decomp = ft_freqanalysis(cfg,
data); </div><div>% Compute the functional connectivity using PLV <br>cfg = [];<br>cfg.method = 'plv'<br></div><div>fc = ft_connectivityanalysis(cfg, spectral_decomp); </div></div><div><br></div><div><br></div><div>To further test if it is something with the particular dataset, I also tried on separate continuous EEG data which was segmented in fieldtrip. However this yielded similar quite varying results when using either output</div><div> % cfg.dataset = 'Dataset_RS.set'; <br></div><div><div> % [data] = ft_preprocessing(cfg) <br></div><div></div>%cfg = [];<br>%cfg.length = 6;<br>%cfg.overlap = 0;<br>%data_segmented = ft_redefinetrial(cfg, data);</div><div><br></div><div> Thanks,</div><div><div><br></div>-- <br><div dir="ltr" data-smartmail="gmail_signature"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div style="color:rgb(80,0,80);font-size:12.8px"><span style="font-size:12.8px">Regards,</span></div><div style="color:rgb(80,0,80);font-size:12.8px"><span style="font-size:12.8px"><br></span></div><div style="color:rgb(80,0,80);font-size:12.8px">ASR</div><div style="color:rgb(80,0,80);font-size:12.8px"><br></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>
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