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Jose,
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<div>Regarding the time-resolved PLV, isn't it different to do it with mtmconvol, which in my view provides a TFR, than with a time signal based on the Hilbert transform which estimates instantaneous phase.</div>
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<div>My doubt is that the time-resolved PLV will need three or four cycles for good spectral estimation, and two things can happen:</div>
<div>1 - I analyse non-overlapping chunks and get a low number of time-points.</div>
<div>2 - I analyse highly overlapping segments and thus a lot of PLV estimations but not really independent from each other and therefore biasing the comparison to other conditions</div>
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<div>With the Hilbert derived transform I would theoretically have as many independent estimates of the PLV, right?</div>
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<div>Is there a caveat in my line of thought? I might be missing something here…</div>
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<div>The thing you are missing here, is that the Hilbert transform also integrates over time to get an ‘instantaneous’ estimate of phase and amplitude (in other words, there’s nothing instantaneous about it). The difference with Fourier based methods is that
you explicitly have to set the time window when doing a short window FFT, and for the Hilbert transform (which by the way in MATLAB is computed through a Fourier transform as far as I remember) one only can guess about how independent the time samples are
from one sample to the next. Note, that temporal overlap is not so much an issue when doing statistical inference by means of permutation tests.</div>
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<div>Best,</div>
<div>Jan-Mathijs</div>
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Jan-Mathijs Schoffelen, MD PhD, Senior researcher
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Max Planck Institute for Psycholinguistics<br>
Donders Centre for Cognitive Neuroimaging</div>
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E-mail: <a href="mailto:j.schoffelen@donders.ru.nl">j.schoffelen@donders.ru.nl</a><br>
Telephone: +31-24-3614793<br>
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<a href="http://www.hettaligebrein.nl">http://www.hettaligebrein.nl</a></div>
<div><a href="http://www.fieldtriptoolbox.org">http://www.fieldtriptoolbox.org</a></div>
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