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Preprocessing of EEG raw data for hypothesis testing and predictive modeling

This is a fundamental pipeline for semi-manual pre-processing of EEG (ElectroEncephalyGraphic) data, using the MNE-python package (https://mne.tools/stable/index.html).

Includes the following stages:

  • Reading .edf file containing raw EEG + triggers channel.
  • Performing visual inspection of the data and interactively marking movement artifacts and bad electrodes.
  • Removing eye blinks and heart-beat traces by decomposing and recomposing the signal using Independent Component Analysis (ICA).
  • Final inspection of the clean data, and saving.

This script is set as a tutorial, with an example data file. Data file: 'Example_data.edf'

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