Python Developer Internship - ERP Analysis Task 🚀

Objective

This task evaluates your ability to process EEG data, extract event-related potentials (ERPs), and visualize the results using Python and MNE-Python.

Dataset

You are provided with an EDF file named John_Brain_Data.edf, which contains EEG recordings with event markers. Stimuli are categorized based on their trigger duration:

• Common Stimuli → If trigger duration is below 100 ms
• Uncommon Stimuli → If trigger duration is between 100 ms and 140 ms
• Super Trigger → If trigger duration is above 140 ms (Ignore these)

Your Task

1. Load the EEG Data

   • Use MNE-Python to read John_Brain_Data.edf

2. Preprocess the EEG Data

   • Apply a bandpass filter (e.g., 1–40 Hz).

   • Remove artifacts if necessary (e.g., using ICA or epoch rejection).

3. Extract Event-Related Potentials (ERPs)

   • Identify event markers for Common and Uncommon stimuli.

   • Segment the data into epochs around stimulus onset.

   • Compute and plot ERP waveforms (averaged over trials) for at least 3 electrodes of your choice.

4. Bonus Task (Optional)

   • Compute the grand average ERP across all trials for each condition.

   • Highlight key ERP components like P300 or N200, if visible.

   • Perform a statistical comparison between Common and Uncommon ERPs (e.g., using a t-test).

Submission Instructions

• Complete the task using Google Colab.

• Share the Colab Notebook link with [email protected].

• Use the email subject: "Python Developer Internship - ERP Analysis Submission - [Your Name]"

Hints & Resources

• MNE-Python documentation: https://mne.tools/stable/index.html