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The Python Toolbox for multichannel EEG-EMG connectivity analysis. This package is an extention of mne-tool with the focus on the application of the newest graph and network theory. It is first developped to investigate stroke and autism spectral disorder(ASD) via EEG-EMG coherence marker

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CM-graph

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The Python Toolbox for multichannel EEG-EMG connectivity analysis. This package is an extention of mne-tool with the focus on the application of the newest graph and network theory. It is first developped to investigate stroke and autism spectral disorder(ASD) via EEG-EMG coherence marker

Workflow:

The current contribution workflow is being developped. A detailed tutorial will be released in readthedocs in a few days.

Contribution:

You are welcomed to use modules of CM-graph and make your own contribution. There are few steps to begin with:

  • fork the project at your own (remote) repository
  • clone your (remote) repository at your computer (local repository).
  • create a branch named 'dev_feature' and start to playing with the codes
  • commit and push your changes to your own (remote) repository:
  • to show your contribution, please create a pull request from your dev branch to CM-graph\master
  • you can always syncronize your forked repository and cm-graph:
git add upstream https://github.com/CM-connectivity/CM-graph.git
fetch upstream
git checkout master (or your dev branch)
git merge upstream\master

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The Python Toolbox for multichannel EEG-EMG connectivity analysis. This package is an extention of mne-tool with the focus on the application of the newest graph and network theory. It is first developped to investigate stroke and autism spectral disorder(ASD) via EEG-EMG coherence marker

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