And, in addition, yields the best visualization?
Statistics do not matter as they are usually computed through R, anyway.
I'm already familiar with SIFT and EEGNET.
All kinds of help/suggestions are much appreciated!
Thanks!
Hmm, I am myself not using a connectivity package except for Barnett and Seth's MVGC and SSGC toolboxes. The rest is custom code by Guido Nolte and me. Guido's code is here: https://www.uke.de/english/departments-institutes/institutes
I have put some fragmented code here:
http://bbci.de/supplementary/EEGconnectivity/BBCB.html
https://github.com/stefanhaufe/GC_vs_TRGC/releases
The focus is on metrics robust to volume conduction. There is some modest plotting capability, too, see this twitter thread: https://bit.ly/2WOur2t. But this yet needs to be put into a proper software framework. Arnaud Delorme has plans to do this to some extent and I hope to support him.
Overall, I suggest to use a toolbox that allows calculation of robust connectivity metrics (imaginary part of coherence, time-reversed GC, weighted phase-lag index). But I'm afraid I cannot give you better advise resp. eeglab integration and vizualization.
Hmm, I am myself not using a connectivity package except for Barnett and Seth's MVGC and SSGC toolboxes. The rest is custom code by Guido Nolte and me. Guido's code is here: https://www.uke.de/english/departments-institutes/institutes
I have put some fragmented code here:
http://bbci.de/supplementary/EEGconnectivity/BBCB.html
https://github.com/stefanhaufe/GC_vs_TRGC/releases
The focus is on metrics robust to volume conduction. There is some modest plotting capability, too, see this twitter thread: https://bit.ly/2WOur2t. But this yet needs to be put into a proper software framework. Arnaud Delorme has plans to do this to some extent and I hope to support him.
Overall, I suggest to use a toolbox that allows calculation of robust connectivity metrics (imaginary part of coherence, time-reversed GC, weighted phase-lag index). But I'm afraid I cannot give you better advise resp. eeglab integration and vizualization.
Super! This is awesome work! Thank you so much for sharing, I will have a deeper look very soon.
I hope to be able to link parts of your code to the existing EEGLAB data-structure, and hopefully get some visualization. To be sure, you're using time reversed granger causality to determine direction, right? I'm still in the process of figuring what may work better for EEG.
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