EEGDash Corpus

EEGDash Corpus is an aggregated, training-ready collection of public EEG datasets for pretraining EEG foundation models, served through EEGDash as raw datasets and as one converted Zarr store. Version 0 holds 66 datasets (45,549 hours, converted); version 1 extends it to 78 datasets.

66datasets converted (v0)

45,549hours converted (v0)

5,091subjects converted (v0)

78datasets in v1 (+11 to convert, 1 to ingest)

46,519hours in v1 (measured so far)

9pending (1 to ingest, 8 blocked)

93datasets tracked in all

66 of the 93 datasets tracked are converted; 3 are gated and 4 excluded.

Introduction

The corpus

• What the corpus is and why it exists

• REVE’s corpus as the starting point

• How it was built, checked and licensed

What you will find: the definitions every page uses, the provenance of each number, the licences.

Introduction

Progress and Roadmap

Status

• Where each of the 93 datasets stands

• What comes next, in order

• From REVE’s paper to the versions

What you will find: the progress strip, the roadmap, and the table of every dataset tracked.

Progress and Roadmap

EEGDash Corpus v0

Converted

• 66 datasets, 45,549 hours, 5,091 subjects

• 386 electrode positions in 968 channel sets

• Hours, channels, subjects, rates, paradigms

What you will find: the converted Zarr store measured, the electrode map in 2-D and 3-D, the table of v0.

EEGDash Corpus v0

EEGDash Corpus v1

Next version

• 12 datasets added: 11 to convert, 1 to ingest

• 78 datasets, 46,519 hours measured so far

• The same views as v0, the added datasets by status

What you will find: what v1 adds, its numbers and caveats, the table of v1.

EEGDash Corpus v1