<div dir="ltr">Hi Darren,<div><br></div><div>I personally recommend GCMI by Robin Ince: <a href="https://github.com/robince/gcmi">https://github.com/robince/gcmi</a><div><br></div><div>Transfer Entropy computation is definitely possible, but as far as I see in the toolbox there is no function that computes it directly. You will have to compute the required MI/CMI terms yourself and assemble them to calculate TE. With this code, you can indeed also compute a "feature informed" version of TE (i.e. Directed Feature Information), which isolates the contribution to connectivity of the transfer of a time-varying stimulus feature you specify explicitly. Significance testing for single-subject and group level can proceed as specified here: <a href="https://elifesciences.org/articles/24763">https://elifesciences.org/articles/24763</a></div><div><br></div><div>Best,</div><div><br></div><div> Bruno</div></div></div><br><div class="gmail_quote"><div dir="ltr">On Fri, 3 Aug 2018 at 12:24, Patricia Wollstadt <<a href="mailto:Patricia.Wollstadt@gmx.de">Patricia.Wollstadt@gmx.de</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div><div style="font-family:Verdana;font-size:12.0px"><div>
<div>Hi Darren,</div>
<div> </div>
<div>there is also the excellent JIDT (Java information dynamics toolkit) by Joe Lizier, which comes with MATLAB/octave wrappers: <a href="https://github.com/jlizier/jidt" target="_blank">https://github.com/jlizier/jidt</a></div>
<div> </div>
<div>There is even a demo for the quick calculation of TE from two time series: <a href="https://github.com/jlizier/jidt/blob/master/demos/octave/example4TeContinuousDataKraskov.m" target="_blank">https://github.com/jlizier/jidt/blob/master/demos/octave/example4TeContinuousDataKraskov.m</a></div>
<div> </div>
<div>Hope this helps!</div>
<div> </div>
<div>Best,</div>
<div>Patricia</div>
<div> </div>
<div>
<div style="margin:10.0px 5.0px 5.0px 10.0px;padding:10.0px 0 10.0px 10.0px;border-left:2.0px solid rgb(195,217,229)">
<div style="margin:0 0 10.0px 0"><b>Gesendet:</b> Donnerstag, 02. August 2018 um 15:42 Uhr<br>
<b>Von:</b> "Darren Price" <<a href="mailto:Darren.Price@mrc-cbu.cam.ac.uk" target="_blank">Darren.Price@mrc-cbu.cam.ac.uk</a>><br>
<b>An:</b> "<a href="mailto:fieldtrip@science.ru.nl" target="_blank">fieldtrip@science.ru.nl</a>" <<a href="mailto:fieldtrip@science.ru.nl" target="_blank">fieldtrip@science.ru.nl</a>><br>
<b>Betreff:</b> [FieldTrip] Transfer entropy</div>
<div>
<div>
<div class="m_220457222838399968WordSection1">
<p class="MsoNormal">Hi All</p>
<p class="MsoNormal"> </p>
<p class="MsoNormal">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.</p>
<p class="MsoNormal"> </p>
<p class="MsoNormal">Any other suggestions or comments / experiences with those above would be very helpful.</p>
<p class="MsoNormal"> </p>
<p class="MsoNormal">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</p>
<p class="MsoNormal"> </p>
<p class="MsoNormal">Thanks</p>
<p class="MsoNormal"> </p>
<p class="MsoNormal">Darren</p>
<p class="MsoNormal"> </p>
<p class="MsoNormal"><span>-------------------------------------------------------</span></p>
<p class="MsoNormal"><span>Dr. Darren Price</span></p>
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<p class="MsoNormal"><span>EMAIL: <a href="mailto:darren.price@mrc-cbu.cam.ac.uk" target="_blank">darren.price@mrc-cbu.cam.ac.uk</a></span></p>
<p class="MsoNormal"><span>URL: <a href="http://www.mrc-cbu.cam.ac.uk/people/darren.price" target="_blank"> <span style="color:windowtext;text-decoration:none">http://www.mrc-cbu.cam.ac.uk/people/darren.price</span></a></span></p>
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</blockquote></div><br clear="all"><div><br></div>-- <br><div dir="ltr" class="gmail_signature" data-smartmail="gmail_signature"><div dir="ltr"><div style="color:rgb(136,136,136);font-size:12.8px">~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~</div><div style="color:rgb(136,136,136);font-size:12.8px">Bruno L. Giordano, PhD – CR1</div><div style="color:rgb(136,136,136);font-size:12.8px">Institut de Neurosciences de la Timone (INT)</div><div style="color:rgb(136,136,136);font-size:12.8px">UMR 7289, CNRS and Aix Marseille Université</div><div style="color:rgb(136,136,136);font-size:12.8px"><a href="http://www.int.univ-amu.fr/" style="color:rgb(17,85,204)" target="_blank">http://www.int.univ-amu.fr/</a></div><div style="color:rgb(136,136,136);font-size:12.8px">Campus santé Timone</div><div style="color:rgb(136,136,136);font-size:12.8px">27, boulevard Jean Moulin</div><div style="color:rgb(136,136,136);font-size:12.8px">13385 Marseille cedex 5</div><div style="color:rgb(136,136,136);font-size:12.8px">Www: <a href="http://www.brunolgiordano.net/" style="color:rgb(17,85,204)" target="_blank">http://www.brunolgiordano.net</a></div></div></div>