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<p class="MsoNormal"><span lang="EN-US" style="font-size:10.0pt;color:#1F497D">hi Darren! :)<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:10.0pt;color:#1F497D"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:10.0pt;color:#1F497D">Multi-Variate Granger Causality is also a suitable framework to check for information transfer between time series:<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:10.0pt;color:#1F497D"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:10.0pt;color:#1F497D">Anil Seth’s MATLAB toolbox below:<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:10.0pt;color:#1F497D"><a href="http://users.sussex.ac.uk/~anils/aks_code.htm">http://users.sussex.ac.uk/~anils/aks_code.htm</a><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:10.0pt;color:#1F497D"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:10.0pt;color:#1F497D">I think that in the case of variables with Gaussian distributions and linear relationships between them, MVGC gives the same results as Multi-Variate Transfer Entropy (MVTE). However,
MVTE is also generalized to the case of variables with non-Gaussian distributions with non-linear relationships between them.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:10.0pt;color:#1F497D"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:10.0pt;color:#1F497D">A related framework is the Multi-Variate Auto-Regressive (MVAR) model, which can also be used to check for information transfer between time series. In particular, Partial Directed
Coherence (PDC) and Directed Transfer Function (DTF) can be interpreted in terms of information transfer between time series, and the non-normalised PDC also has a similar interpretation, perhaps even more straightforward than the conventional PDC measure.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:10.0pt;color:#1F497D"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:10.0pt;color:#1F497D">The MVAR-based connectivity measures are implemented in Fieldtrip, in
<b>ft_connectivityanalysis</b><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:10.0pt;color:#1F497D"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:10.0pt;color:#1F497D">Scott Makeig’s group also has the SIFT (Source Information Flow Toolbox) for this:<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:10.0pt;color:#1F497D"><a href="https://sccn.ucsd.edu/wiki/SIFT">https://sccn.ucsd.edu/wiki/SIFT</a><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:10.0pt;color:#1F497D"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:10.0pt;color:#1F497D">I have found the user manual to be helpful:<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:10.0pt;color:#1F497D"><a href="https://sccn.ucsd.edu/mediawiki/images/d/d2/SIFT_manual_0.1a.pdf">https://sccn.ucsd.edu/mediawiki/images/d/d2/SIFT_manual_0.1a.pdf</a><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:10.0pt;color:#1F497D"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:10.0pt;color:#1F497D">Both MVGC and MVAR allow for frequency-specific measures of information flow between time series.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:10.0pt;color:#1F497D"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:10.0pt;color:#1F497D">Regards,<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:10.0pt;color:#1F497D">Nitin<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="color:#1F497D"><o:p> </o:p></span></p>
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<p class="MsoNormal"><b><span lang="EN-US" style="mso-fareast-language:FI">From:</span></b><span lang="EN-US" style="mso-fareast-language:FI"> fieldtrip <fieldtrip-bounces@science.ru.nl>
<b>On Behalf Of </b>Darren Price<br>
<b>Sent:</b> Thursday, August 2, 2018 4:42 PM<br>
<b>To:</b> fieldtrip@science.ru.nl<br>
<b>Subject:</b> [FieldTrip] Transfer entropy<o:p></o:p></span></p>
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<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">Hi All <o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">Could anyone suggest the tools for computing transfer entropy in Matlab? I had a look at MuTE toolbox, but that seemed overly complicated, and I couldn’t even get the example to work. I’m currently looking at TRENTTOOL
which looks good and works with fieldtrip format. I will also try “phase transfer entropy”, which is a single matlab function and simple to implement.
<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">Any other suggestions or comments / experiences with those above would be very helpful.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">To begin with I would simply like to check for information transfer between two timeseries. I may also check for indirect serial transfer i.e. A>B>C<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">Thanks<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">Darren <o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB" style="mso-fareast-language:EN-GB">-------------------------------------------------------<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB" style="mso-fareast-language:EN-GB">Dr. Darren Price<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB" style="mso-fareast-language:EN-GB">Research Associate<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB" style="mso-fareast-language:EN-GB">MRC Cognition & Brain Sciences Unit<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB" style="mso-fareast-language:EN-GB">15 Chaucer Road<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB" style="mso-fareast-language:EN-GB">Cambridge, CB2 7EF<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB" style="mso-fareast-language:EN-GB">England
<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB" style="mso-fareast-language:EN-GB">EMAIL:
<a href="mailto:darren.price@mrc-cbu.cam.ac.uk">darren.price@mrc-cbu.cam.ac.uk</a><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB" style="mso-fareast-language:EN-GB">URL:
<a href="http://www.mrc-cbu.cam.ac.uk/people/darren.price"><span style="color:windowtext;text-decoration:none">http://www.mrc-cbu.cam.ac.uk/people/darren.price</span></a><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB" style="mso-fareast-language:EN-GB">TEL +44 (0)1223 355 294 x202<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB" style="mso-fareast-language:EN-GB">FAX +44 (0)1223 359 062<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB" style="mso-fareast-language:EN-GB">MOB +44 (0)7717822431<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB" style="mso-fareast-language:EN-GB">-------------------------------------------------------<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
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