deep learning life sciences machine learning neuroimaging neuroscience
The EEG-DaSh (EEG Data Sharing) data archive is a large-scale data-sharing resource for magnetoencephalography and electroencephalography (MEEG) data hosted at the Swartz Center for Computational Neuroscience (SCCN), UC San Diego. It provides curated, BIDS-formatted datasets for neuroscience research, machine learning, and deep learning applications. The archive spans three S3 buckets: (1) the EEGDash bucket for data served through the EEGDash platform, (2) the NEMAR archive containing datasets contributed through the NEMAR (Neuroelectromagnetic Data Archive and Tools Resource) platform, which serves as the upstream data source for EEGDash, and (3) a competition-specific collection of datasets adapted and preprocessed for machine learning benchmarks and competitions.
About once a week
There are no restrictions on the use of this data.
Swartz Center for Computational Neuroscience
See all datasets managed by Swartz Center for Computational Neuroscience.
EEGDash on AWS was accessed on DATE from https://registry.opendata.aws/eegdash.
arn:aws:s3:::eegdashus-east-2aws s3 ls --no-sign-request s3://eegdash/arn:aws:s3:::nemarus-east-2aws s3 ls --no-sign-request s3://nemar/arn:aws:s3:::nmdatasetsus-east-2aws s3 ls --no-sign-request s3://nmdatasets/arn:aws:sns:us-east-2:191754232783:eegdash-nemarus-east-2