/Time_Frequency_Analysis

Time-Frequency Analysis and Inter Trial Phase Consistency Implementation

Primary LanguageJupyter Notebook

This project focuses on EEG data analysis, specifically detecting and analyzing event-related potentials (P300) using Python, MNE, and PCA. Key steps include:

  • Data Preprocessing: Load and preprocess EEG data from CSV, creating an MNE RawArray object and extracting relevant channels.
  • Event Detection: Identify target and non-target events in the signal for analysis.
  • Dimensionality Reduction: Apply PCA to reduce the EEG data from 3 channels to 1 per trial.
  • Time-Frequency Analysis: Perform time-frequency analysis using custom DFT and generate spectrograms for visualization.
  • Phase Consistency: Calculate inter-trial phase consistency to measure signal stability across trials.