Datasets:

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EEGDash

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eeg-mi-datasets

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EEGDash — the Python library for 700+ BIDS-first EEG/MEG/EMG/fNRIS/iEEG datasets. 14

Adds WRCC2023_MI_A, WRCC2023_MI_B and WRCC2023_MI_C (Harvard Dataverse J9JFES, HFNWRX, G8FBHH v1.0, CC0 1.0): 26 files, 4.42 GB, in MOABB's cache layout, byte for byte; each file matches Dataverse's MD5, and MOABB (555d14a) loads all 26 subjects from these copies.

The card gains the three datasets and, for every dataset, classes, trials per class per session, EEG channels, sampling rate and participants (blank where docs/datasets.md has no figure), plus updated totals: 32 datasets, 841 subjects, 1,917 sessions, 637 GB. Counts come from mirror.py's integrity facts; on the 124 sessions also checked on 8-9 Oct they agree.