SCoT: a Python toolbox for EEG source connectivity

@article{Billinger2014SCoTAP,
  title={SCoT: a Python toolbox for EEG source connectivity},
  author={M. Billinger and C. Brunner and G. M{\"u}ller-Putz},
  journal={Frontiers in Neuroinformatics},
  year={2014},
  volume={8}
}
Analysis of brain connectivity has become an important research tool in neuroscience. Connectivity can be estimated between cortical sources reconstructed from the electroencephalogram (EEG). Such analysis often relies on trial averaging to obtain reliable results. However, some applications such as brain-computer interfaces (BCIs) require single-trial estimation methods. In this paper, we present SCoT—a source connectivity toolbox for Python. This toolbox implements routines for blind source… Expand
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