source-Imaging

A collection of scripts and tools for EEG source imaging using MNE-Python. This repository encompasses preprocessing pipelines, source localization methods, statistical analysis, and visualization utilities tailored for EEG data analysis.([github.com][1])

Features

• Preprocessing Pipelines: Automated scripts for EEG data cleaning, including bad channel detection and artifact rejection.
• Source Localization: Implementations of various source imaging techniques using MNE-Python.
• Statistical Analysis: Tools for cluster-based permutation tests and other statistical evaluations.
• Visualization: Scripts for plotting sensor layouts, source estimates, and statistical results.
• Compatibility: Supports data formats commonly used in EEG research, such as .mat and .vmrk files.([researchgate.net][2], [github.com][1])

Installation

1. Clone the repository:

   git clone https://github.com/berdakh/source-Imaging.git
   cd source-Imaging

2. Create a virtual environment (optional but recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install required packages:

   pip install -r requirements.txt

Note: Ensure that MNE-Python is installed, as it's central to the functionalities provided.

Usage

The repository contains multiple scripts, each serving specific purposes. Here's a brief overview:

• Preprocessing:

  • preproc.py, batch_preproc.py: Scripts for preprocessing EEG data, including filtering and artifact removal.
  • badchannel-example.py: Example script for detecting and handling bad channels.([github.com][1])

• Source Localization:

  • plot_mne_dspm_source_localization.py: Demonstrates source localization using dSPM method.
  • uh_forward.py, uh_inverseBatch.py: Scripts for forward and inverse modeling.([github.com][1])

• Statistical Analysis:

  • plot_stats_cluster_spatio_temporal.py, stats_cluster_spatio_temporal.py: Perform cluster-based permutation tests.([github.com][1])

• Visualization:

  • plot_forward.py, plot_source_alignment.py: Visualize forward models and source alignments.([github.com][1])

• Utilities:

  • find_vmrk.py: Locate and process .vmrk files.
  • load_mat_MRCP.py: Load .mat files containing MRCP data.([github.com][1])

To execute a script, navigate to the repository directory and run:

python script_name.py

Replace script_name.py with the desired script.

File Structure

source-Imaging/
├── preprocessing/
│   ├── preproc.py
│   ├── batch_preproc.py
│   └── badchannel-example.py
├── source_localization/
│   ├── plot_mne_dspm_source_localization.py
│   ├── uh_forward.py
│   └── uh_inverseBatch.py
├── statistics/
│   ├── plot_stats_cluster_spatio_temporal.py
│   └── stats_cluster_spatio_temporal.py
├── visualization/
│   ├── plot_forward.py
│   └── plot_source_alignment.py
├── utilities/
│   ├── find_vmrk.py
│   └── load_mat_MRCP.py
├── requirements.txt
└── README.md

Note: The above structure is a suggested organization. Adjust directories as needed based on actual file locations.

Contributing

Contributions are welcome! If you have suggestions, bug reports, or enhancements, please open an issue or submit a pull request.([github.com][3])

License

This project is open-source and available under the MIT License.

Acknowledgments

This repository was developed by Berdakh Abibullaev, focusing on EEG source imaging techniques using MNE-Python.([github.com][4])

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For detailed explanations and methodologies, refer to the Source localization with MNE.pdf included in the repository.