Neurotheque Resources

Neurotheque Resources is a comprehensive, modular toolkit for EEG data processing and analysis. Built on state-of-the-art libraries such as MNE-Python and autoreject, it provides a flexible framework for building reproducible EEG processing pipelines.

Core Features

• Modular Pipeline Architecture: Build custom pipelines by combining a series of processing steps.
• Configuration-driven: Define your pipelines using simple YAML files.
• BIDS Compatibility: Organized to work with BIDS-formatted data.
• Artifact Rejection: Includes advanced methods like ICA and autoreject.
• Automated Reporting: Generate HTML reports with key metrics and plots.
• Command-Line Interface: Run your pipelines easily from the terminal.

Quick Start

Get up and running with Neurotheque in just a few steps.

1. Installation

First, clone the repository and install the package in editable mode. This will also install all the required dependencies.

git clone https://github.com/YannFeurprier/neurotheque_resources.git
cd neurotheque_resources
pip install -e .

2. Run a Demo Pipeline

You can run a demo pipeline using one of the provided configuration files. For example, to run the minimal Go/No-Go pipeline:

neurotheque run-pipeline configs/gonogo_minimal_pipeline.yml

This will process the sample data and generate the results in the data/processed and reports directories.

Usage

Command-Line Interface (CLI)

The primary way to use Neurotheque is through its command-line interface.

neurotheque run-pipeline [CONFIG_FILE]

• CONFIG_FILE: Path to the YAML configuration file for the pipeline.

Creating a Custom Pipeline

To create your own pipeline, you can create a new YAML configuration file. The configuration file specifies the steps to be executed and their parameters.

Here is an example of a simple pipeline configuration:

directory:
  root: "data"
  raw_data_dir: "raw"
  processed_dir: "processed"
  reports_dir: "reports"
  derivatives_dir: "derivatives"

file_path_pattern: "sub-01/ses-001/eeg/*_eeg.vhdr"

pipeline:
  steps:
    - name: LoadData
    - name: Filter
      params:
        l_freq: 1.0
        h_freq: 40.0
    - name: Epoching
      params:
        task_type: "gng"
        trigger_ids:
          go: 1
          nogo: 2
          response: 3
    - name: GenerateReport

You can find more examples in the configs directory.

For Developers

Setting up the Development Environment

To install the development dependencies, including pytest for testing, run:

pip install -e .[test]

Running Tests

To run the test suite, use pytest:

pytest

Contributing

Contributions are welcome! Please feel free to submit a pull request or open an issue.

License

This project is licensed under the BSD-3-Clause License. See the LICENSE file for details.