Discover datasets

This EEG dataset comprises recordings from children performing letter discrimination and visual search tasks across three experimental stages: pre-intervention baseline, intervention measurement, and post-intervention assessment. Participants were assigned to intervention and control groups to evaluate the effects of embodied learning on literacy-related neural processing. The dataset includes event markers corresponding to stimulus presentations of letters 'b' and 'd', enabling analysis of neural responses to letter discrimination and visual search performance.

Participants

21

Channels

64 (10-10)

Size

36.6 GB

Version

v1.0.0

Updated

Jul 10, 2026

The PURSUE N2pc Visual Search dataset comprises event-related potential (ERP) recordings from a visual search task conducted across three undergraduate institutions. Data were collected from participants in 2017-2018 and represent a component of the ERP CORE resource for standardized human electrophysiological research. The dataset includes demographic information and is designed to facilitate investigation of the N2pc component, a neural marker of attentional selection during visual search.

Participants

294

Channels

32 (10-10)

Size

12.2 GB

Version

v1.0.0

Updated

Jul 10, 2026

The Healthy Brain Network (HBN) EEG Release 10 dataset comprises high-resolution electroencephalogram recordings from 533 children and adolescents (ages 5-21 years) performing six distinct cognitive and perceptual tasks, including resting state, passive viewing tasks (surround suppression, movie watching), and active tasks (contrast change detection, sequence learning, symbol search). The dataset includes behavioral responses, hierarchical event descriptors for systematic meta-analysis, and psychopathology factors derived from the Child Behavior Checklist, providing a comprehensive resource for investigating neural correlates of development and mental health in youth. This is Release 10 of an 11-release series.

Participants

533

Channels

129 (egi-geodesic)

Size

161 GB

Version

v1.0.0

Updated

Jul 22, 2026

BigP3BCI Study J is a P300-based brain-computer interface dataset comprising EEG recordings from 20 healthy subjects performing a 9x8 character grid speller task. This derivative dataset is part of the larger BigP3BCI collection, the largest public P300 BCI dataset with ~267 subjects across 20 studies. The data were acquired at 256 Hz using 16-channel EEG with a g.USBamp amplifier and include target and non-target event classifications suitable for machine learning applications.

Participants

20

Channels

16 (10-10)

HED

v8.4.0

Size

1.49 GB

Version

v1.0.3

Updated

Aug 18, 2026

This magnetoencephalography (MEG) dataset comprises neuroimaging data collected to establish standardized protocols for cross-site pooling of MEG data. The dataset demonstrates the application of BIDS formatting to MEG neuroimaging, facilitating data harmonization and reproducible analysis across multiple research institutions.

Participants

9

Citations

17

Size

77.2 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises EEG, physiological (ECG, respiration, EDA, EMG), and behavioural data collected in 2020 from 44 healthy adults (ages 21-40) during resting-state and task-based conditions. Tasks included a spontaneous deception paradigm (a gambling game requiring participants to report predictions truthfully or deceptively) and a cognitive control battery assessing processing speed, response selection, response inhibition, and conflict resolution. The dataset supports research into the neurophysiological correlates of deception and cognitive control processes.

Participants

45

Channels

139 (other)

Citations

4

Size

202 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains 64-channel EEG recordings and behavioral ratings from 148 healthy adults performing an Emotion Processing and Regulation task using static emotional images. The study examines discrepancies between self-reported and neurophysiological socio-affective responses in relation to loneliness, using a factorial design manipulating stimulus content (social/non-social) and regulation instructions (watch-neutral, watch-negative, reappraise-negative). Participants rated arousal and valence after viewing each stimulus, enabling analysis of the relationship between subjective and physiological emotional responses.

Participants

148

Channels

69 (10-10)

Size

118 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises scalp EEG recordings from 22 participants who used BrainForm, a gamified brain-computer interface (BCI) designed for P300 event-related potential (ERP) training and scalable data collection with consumer hardware. Participants performed repeated runs of a P300 spelling/selection task, allowing analysis of BCI skill acquisition across sessions and the effects of different visual stimulation textures on performance. The dataset supports research on BCI training, human factors, and machine learning applications on ERP data.

Participants

22

Channels

8 (10-10)

Citations

1

HED

v8.4.0

Size

237 MB

Version

v1.0.6

Updated

Aug 20, 2026

BigP3BCI Study G is a P300-based brain-computer interface dataset comprising EEG recordings from 20 healthy subjects performing a 9x8 checkerboard visual speller task. This derivative dataset is one of 20 studies in the larger BigP3BCI collection, the largest public P300 BCI dataset with ~267 subjects total. The data were acquired at 256 Hz using 16-channel EEG with a g.USBamp amplifier and include target and non-target event classifications suitable for machine learning applications.

Participants

20

Channels

16 (10-10)

HED

v8.4.0

Size

1.62 GB

Version

v1.0.3

Updated

Aug 18, 2026

This dataset contains electroencephalogram (EEG), galvanic skin response (GSR), and electrocardiogram (ECG) recordings from 19 healthy adult participants during a calibration session of an affective brain-computer music interface system. Participants listened to 40-second synthetic music clips designed to induce specific affective states defined by valence and arousal dimensions across 5 runs of 18 trials each. The synthetic music was generated in real-time based on target emotional states and could be modified online to induce target emotional states. The dataset includes self-reported affective state ratings and auxiliary variables, serving as calibration data for the brain-computer music interface system. This dataset is part of a three-dataset collection that includes offline training and online real-time control sessions.

Participants

19

Channels

32 (10-10)

Size

6.10 GB

Version

v1.0.0

Updated

Jul 10, 2026