Discover datasets

This dataset contains simultaneous scalp and ear-EEG recordings from six healthy right-handed participants performing cued left- and right-hand fist clenching (motor execution). It comprises 1114 trials recorded at 1000 Hz with a Neuroscan SynAmps2 amplifier. The data support evaluation of in-ear sensing for motor task classification and brain-computer interface research. This BIDS version was generated with MOABB from the original Zenodo deposit.

Participants

6

Channels

122 (10-05)

Citations

12

HED

v8.4.0

Size

18.4 GB

Version

v1.0.3

Updated

Aug 20, 2026

EEG recordings from 14 healthy, BCI-naive participants performing asynchronous voluntary index-finger tapping (right, left) and rest, originally reported by Wairagkar et al. (2018). Data were recorded at 1024 Hz from 19 scalp channels and preprocessed with filtering and ICA artifact removal. Trials are segmented around movement onset to study neural correlates of movement intention, and the dataset is distributed in BIDS format via MOABB.

Participants

14

Channels

19 (10-20)

Citations

10

HED

v8.4.0

Size

1.23 GB

Version

v1.0.2

Updated

Aug 18, 2026

This dataset contains 19-channel EEG recordings from 7 healthy participants performing classical motor imagery of the left hand, right hand, and passive rest. Participants responded to visual arrow cues in offline sessions, without feedback. The recordings were made with a Nihon Kohden EEG-1200 system at 200 Hz. The data support brain-computer interface research and motor imagery classification benchmarking.

Participants

7

Channels

19 (10-20)

Citations

82

HED

v8.4.0

Size

1.20 GB

Version

v1.0.2

Updated

Aug 18, 2026

Resting-state (eyes-closed and eyes-open) and auditory oddball P300 task EEG recordings from patients with Major Depressive Disorder and healthy control participants. Data were recorded with a 19-channel 10-20 system at 256 Hz to support research on neurophysiological biomarkers of depression and on differences in attentional processing. This BIDS version was converted from the original figshare deposit.

Participants

64

Channels

22 (10-20)

Citations

173

Size

812 MB

Version

v1.0.0

Updated

Mar 14, 2026

EEG recordings from 15 participants performing imagined speech of five commands ("Hello", "Help me", "Stop", "Thank you", "Yes"), released for the 2020 BCI Competition Track 3. The data are split into training, validation and test runs to support machine-learning decoding of imagined speech for brain-computer interfaces. The dataset was converted from the original MATLAB files to BIDS-compliant EDF with trial annotations.

Participants

15

Channels

64 (10-10)

Size

585 MB

Version

v1.0.0

Updated

Mar 14, 2026

Scalp EEG recordings from 36 healthy university students during eyes-closed rest and a serial-subtraction mental arithmetic task. The dataset supports study of EEG correlates of cognitive workload and mathematical cognition, with applications in mental workload assessment and brain-computer interfaces. Participants were split post hoc into good and bad counters based on the number of completed subtractions. This BIDS version was converted from the PhysioNet release.

Participants

36

Channels

20 (10-20)

Citations

89

Size

174 MB

Version

v1.0.0

Updated

Mar 14, 2026

ERP CORE (Compendium of Open Resources and Experiments) is an open resource of raw EEG recordings from 40 neurotypical adults performing six optimized task paradigms. The paradigms elicit seven widely used ERP components: N170, MMN, N2pc, N400, P3, LRP and ERN. The dataset includes event code schemes, task stimuli for the N170, MMN and N400 paradigms, and participant demographics.

Participants

40

Channels

30 (10-10)

Citations

162

HED

v8.4.0

Size

17.5 GB

Version

v1.1.1

Updated

Apr 4, 2026

The Finer-grained Affective Computing EEG Dataset (FACED) contains 32-channel scalp EEG from 123 healthy participants who watched 28 emotion-eliciting video clips targeting nine emotion categories (four negative, four positive, and neutral). Participants gave self-reported ratings on 12 dimensions, including discrete emotions, valence, arousal, liking, and familiarity. The dataset supports cross-subject affective computing and the development of EEG-based emotion recognition algorithms. This version is converted to BIDS with events annotated by video and emotion labels.

Participants

123

Channels

32 (10-10)

Citations

94

Size

31.4 GB

Version

v1.1.3

Updated

May 29, 2026

The CHB-MIT Scalp EEG Database contains continuous scalp EEG recordings from pediatric patients with intractable epilepsy, collected at Children's Hospital Boston. Subjects were monitored for days after anti-seizure medication withdrawal to characterize seizures and assess candidacy for surgical intervention. The recordings include 198 annotated seizures, sampled at 256 Hz on the 10-20 system with bipolar montages. This version is a BIDS conversion of the original PhysioNet data, with seizure onset and offset annotations provided as events.

Participants

24

Channels

23 (other)

Citations

48

Size

42.6 GB

Version

v1.0.1

Updated

Mar 11, 2026

EEG recordings from four participants performing motor imagery of the left hand, right hand, and feet, originally reported by Zhou et al. (2016) in a study on automated trial selection for motor imagery brain-computer interfaces. Each participant completed three sessions of two runs, giving 450 trials per subject. Data were recorded from 14 channels at 250 Hz and reformatted into BIDS from a MOABB-generated Zenodo version.

Participants

4

Channels

14 (10-10)

Citations

87

Size

152 MB

Version

v1.0.0

Updated

Mar 3, 2026