Discover datasets

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

This dataset contains functional near-infrared spectroscopy (fNIRS) recordings of prefrontal cortex activity from 20 participants (ages 21-46; 5 female, 15 male) in a driving simulator. Participants experienced fourteen types of highly automated driving scenarios, and the dataset accompanies scenario data and subjective danger ratings. It is intended to support study of prefrontal activity differences between low-risk and high-risk driving episodes, with potential application to brain-computer interfaces and improving safety of the intended functionality (SOTIF).

Participants

20

Size

2.32 GB

Version

v1.0.0

Updated

Jun 18, 2026

…Study examined psychological and cognitive predictors of MI-BCI performance. Feedback type…

Participants

55

Channels

16 (10-10)

HED

v8.4.0

Size

5.30 GB

Version

v1.0.0

Updated

Oct 8, 2026

FOODEEG is an open dataset of electroencephalographic (EEG) and behavioural responses to food images from 117 participants. In one session, EEG was recorded during a food categorisation task in which participants judged images as healthy, tasty, or something they were willing to eat. In a second session, participants completed a food go/no-go task, a paired choice task, and questionnaires on dietary style and motivation. The dataset also includes raw and cleaned EEG data and normative ratings of the food stimuli from online samples.

Participants

117

Size

91.1 GB

Version

v1.0.0

Updated

Jun 29, 2026

EEG recordings from 13 healthy participants performing a copy-spelling task with a visual 6x7 matrix ERP speller. The speller was designed for learning from label proportions (LLP), an unsupervised, calibrationless classification approach for ERP-based brain-computer interfaces. Two stimulus sequences with different target/non-target ratios allowed LLP to reconstruct mean target and non-target responses without labeled data. In the original online study, 84.5% of characters were spelled correctly on average without prior calibration.

Participants

13

Channels

31 (10-10)

Citations

46

HED

v8.4.0

Size

5.15 GB

Version

v1.0.3

Updated

Oct 8, 2026

…to these processes in healthy cognitive aging. Results indicate that VSWM sequence…

Participants

62

Channels

65 (10-10)

Size

25.1 GB

Version

v1.0.0

Updated

Jun 25, 2026

This dataset contains psychometric and EEG data from 76 Mexican children with reading or math learning difficulties. Children were assigned to an experimental group, who used the online learning method Smartick for three months, or a control group with no intervention. EEG (resting state and reading or arithmetic tasks) and psychometric assessments were collected before and after the intervention to evaluate gains in reading and math skills.

Participants

76

Channels

32 (10-10)

Size

2.76 GB

Version

v1.0.0

Updated

Jun 28, 2026

…measures captured acute and longitudinal cognitive and subjective effects, with follow-ups…

Participants

65

Channels

64 (10-10)

Size

936 GB

Version

v1.0.0

Updated

Jun 21, 2026

Stereo-EEG recordings from six patients with medically refractory epilepsy performing a scene recognition memory task with concurrent EyeLink eye tracking. The dataset accompanies a study of how the human hippocampus rapidly coordinates effective learning, and is a lossless iEEG-BIDS re-packaging of the authors' public Zenodo release. It includes electrode MNI coordinates, behavioural arrays, eye-tracking files and the authors' analysis code in sourcedata.

Participants

6

Size

41.7 GB

Version

v1.0.0

Updated

Oct 8, 2026

Pilot EEG dataset collected in preparation for a registered report on loneliness and its neural correlates. The study aims to distinguish between hypersensitivity and hyperalertness to social information in the brain. Further details on the registered report are provided via an associated OSF project.

Participants

38

Channels

65

Size

29.3 GB

Version

v1.0.0

Updated

Jun 25, 2026