EEGDash: the Python library for 700+ BIDS-first EEG/MEG datasets.

Install with pip install eegdash, then load, preprocess, and train PyTorch models on open EEG/MEG data in minutes. Works hand-in-hand with MNE-Python and braindecode.

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Get started

Quickstart

pip install eegdash

from eegdash import EEGDash

eegdash = EEGDash()
records = eegdash.find(dataset="ds002718")
print(f"Found {len(records)} records.")

Works with Python 3.10+. BIDS-first. Runs locally.

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Read the Docs

At a glance

Search-first discovery with reproducible pipelines and standardized metadata.

Test Status Doc Status PyPI Python Versions Downloads Code Coverage License GitHub Stars
Datasets

700+

Curated and standardized metadata ready to explore.

Datasets Catalog
Modalities

5

EEG, MEG, fNIRS, EMG, and iEEG coverage.

Datasets Catalog
BIDS-first

BIDS

Interoperability and reproducibility baked in.

User Guide
Open source

GitHub

Community-driven datasets, pipelines, and benchmarks.

https://github.com/eegdash/EEGDash

Build with the community

Share datasets, contribute pipelines, and help define open standards for EEG and MEG.

GitHub

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Support Institutions

UCSD UCSD
Ben-Gurion University of the Negev (BGU) Ben-Gurion University of the Negev (BGU)

Funders

AWS Open Data Sponsorship Program