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Instruction.md

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Install MNE Python and get familar with Spyder

  1. Download and install MNE-Python installers from here.

    • Choose the installers based on your operating system (Windows,MacOS or Linux).
    • Use the default option during the installation.
    • The installer adds menu entries on Linux and Windows, and several application bundles to the Applications folder on macOS.

  2. Open Spyder from the menu/application.

    • You can use Spyder to write your own python analysis scripts or open demo python scripts.
    • The python scripts (*.py file) can be opened form File menu-> Open.
    • Run the entire script/file by clicking the button the Toolbar (or press F5 key).
    • Run selection or current line by clicking the button in the Toolbar (or press F5 key).
    • You can learn more about the basics of Spyder from the Youtube video here.

Analyze oddball and imagmove EEG data in MNE Python

  • Download the whole repository as a zip file and unzip it on your own computer.
  • The scripts are located in CIBA120-2022-Analyzing-EEG-master\script folder.

Task 1: Practice the EEG preprocessing step using the oddball data from two participants:

  • Open the script: Practise-processing-oddball.py in Spyder.
  • Follow the detailed instruction in the comments (lines starting with #) of the scripts.
  • It is possible to run the entire script or run each line at a time.

Task 2: Run the group analysis script for Oddball task

  • Open the script: oddball-group_analysis.py in Spyder
  • Change the processed_data_folder in the code to the place where you put the processed_data_folder (downloaded from Moodle) in your own computer.
  • Run the script and try to resovle possible errors.
  • Check the output in the ipython terminal and the figure plotted.
  • Compare your own results with the demo results in oddball-group_analysis.ipynb (can be opened on the Github webpage) or oddball-group_analysis.html (need to download and open locally).

Task 3: Run the group analysis script for ImagMove task

  • Same steps as in Task 2 but run the script: ImagMove-group_analysis.py and compare with corresponding demo results.