NOD-EEG
…are stored in the `stimuli/ImageNet` directory. Images within this folder are…
- Participants
- 19
- Channels
- 62 (10-10)
- Citations
- 5
- Size
- 24.3 GB
- Version
- v1.0.0
- Updated
- Jun 28, 2026
…are stored in the `stimuli/ImageNet` directory. Images within this folder are…
This dataset, named DataSet2, is an EEG dataset originally deposited on OpenNeuro (ds002833) and mirrored on NEMAR. It was contributed by Mheich and colleagues. The available documentation gives no details on the experimental paradigm or participants.
…are stored in the `stimuli/ImageNet` directory. Images within this folder are…
Beetl2021-A is a preprocessed four-class motor imagery EEG dataset (rest, left hand, right hand, feet) from Task 2 of the BEETL Competition at NeurIPS 2021. It contains 63-channel recordings at 500 Hz from healthy participants playing an online BCI racing game (Cybathlon2020IC), with 1490 trials of 4 s each in a single session. It serves as a benchmark for transfer learning and domain adaptation across heterogeneous EEG datasets and subjects, and is re-hosted in BIDS format via the MOABB pipeline.
A cross-session motor imagery EEG dataset from 14 healthy participants who performed cued left- versus right-hand motor imagery on two separate days. Data were recorded with 28 EEG channels at 250 Hz and comprise 60 trials per class per session. The dataset supports research on brain-computer interface decoding and cross-session variability, and it is distributed here in BIDS format with HED event annotations.
A cross-session motor imagery EEG dataset from 10 healthy participants who performed cued left- versus right-hand motor imagery across two sessions. Recordings used 28 EEG channels sampled at 250 Hz with a Neuroscan SynAmps2 amplifier, with roughly 180 trials per session. In session 2, test trials included online feedback. The data were re-released in BIDS format via MOABB for brain-computer interface research.
Beetl2021-B is a preprocessed 32-channel EEG dataset from the NeurIPS 2021 BEETL competition, built to benchmark transfer learning for motor imagery decoding. It contains recordings from 2 healthy subjects performing four-class motor imagery (left hand, right hand, feet, rest) at 200 Hz, totaling 1590 trials. The dataset supports evaluation of cross-subject and cross-dataset generalization and domain adaptation in brain-computer interfaces.
Release 8 of the HBN-EEG dataset, the EEG component of the Child Mind Institute Healthy Brain Network project, organized in BIDS format. It contains EEG recordings and behavioral responses from 257 children and young adults (ages 5-21) performing six passive and active tasks: resting state, surround suppression, movie watching, contrast change detection, sequence learning, and symbol search. Events carry Hierarchical Event Descriptor (HED) annotations, and the participants file includes CBCL-derived psychopathology factors and quality-control results.
Release 10 of the HBN-EEG dataset, the EEG section of the Child Mind Institute Healthy Brain Network project, organized in BIDS format. It contains EEG recordings and behavioral responses from 533 participants aged 5-21 years performing six passive and active tasks (resting state, surround suppression, movie watching, contrast change detection, sequence learning, symbol search). Events carry HED annotations, and the participants file includes quality-control results and psychopathology factors derived from the CBCL.
Release 6 of the HBN-EEG dataset, the EEG component of the Child Mind Institute Healthy Brain Network project, organized in BIDS format. It contains EEG recordings and behavioral responses from 134 participants aged 5-21 performing three passive tasks (resting state, surround suppression, movie watching) and three active tasks (contrast change detection, sequence learning, symbol search). Events carry HED annotations, and psychopathology factors derived from the CBCL (p-factor, attention, internalizing, externalizing) are provided alongside basic quality-control results.