This repository serves as a curated, community-driven list of publicly available Electroencephalography (EEG) datasets. It aims to be a comprehensive resource for researchers, students, and practitioners working with EEG data, providing categorized links and brief descriptions for various experimental paradigms and research areas.

How It Works

The project functions as a central index, aggregating links to diverse EEG datasets. Datasets are categorized by the type of cognitive or experimental task they represent, such as Motor Imagery, Emotion Recognition, Error-Related Potentials (ErrP), Visually Evoked Potentials (VEPs), and more. Each entry typically includes the number of subjects, electrode count, sampling rate, and a brief description of the experimental setup or data type.

Quick Start & Requirements

No installation or execution is required. This is a reference list. Users will need to visit the provided links to access and download the datasets, which may have their own specific requirements.

Highlighted Details

• Extensive categorization covering a wide range of EEG research areas.
• Includes datasets with varying subject counts, electrode configurations, and sampling rates.
• Provides links to associated publications and sometimes pre-processed data.
• Features a "Miscellaneous" section for unique or less common EEG data types.

Maintenance & Community

This is a community-driven project. Users are encouraged to contribute by updating the list with new datasets or corrections. There are no explicit community channels or active development mentions in the README.

Licensing & Compatibility

Dataset licensing varies by source. Users must adhere to the specific terms of use for each dataset they access. Compatibility for commercial use depends entirely on the individual dataset licenses.

Limitations & Caveats

The README explicitly states that the list is not exhaustive and may contain duplicates. Some datasets are available only upon request or require specific contact with the authors. The "Unfiltered" section contains a large number of links that may require manual vetting.