Discover datasets

This dataset comprises electroencephalography (EEG) recordings from 17 participants during continuous gameplay of an 8-bit style video game, supplemented by recordings from a visual oddball task and a gambling task. EEG signals were synchronized with behavioral data including player position, movement, actions, and antagonist information logged continuously during gameplay. The dataset provides a rich resource for investigating neural correlates of real-time decision-making and motor control in dynamic gaming environments.

Participants

17

Channels

65 (10-10)

Citations

20

Size

6.48 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises EEG recordings from 25 participants performing a two-competing speaker paradigm where subjects attended to one of two simultaneously presented audiobooks while their own name was embedded in the ignored stream. The experiment consisted of five 10-minute blocks presented under omnidirectional and beamforming acoustic conditions to investigate neural mechanisms of selective attention and self-referential processing in cocktail party listening scenarios.

Participants

25

Channels

47 (egi-geodesic)

Citations

39

Size

13.5 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises EEG recordings from 28 Parkinson's disease patients and 28 matched controls performing a Simon conflict task with cost of conflict reinforcement manipulation. Parkinson's patients were tested twice within one week under both ON and OFF medication conditions, while controls participated in a single session. The study investigates neural correlates of conflict processing and decision-making in Parkinson's disease using event-related potentials.

Participants

56

Channels

67 (10-10)

Citations

1

Size

22.3 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises electroencephalography (EEG) recordings from 28 Parkinson's disease patients and 28 matched healthy controls performing a reinforcement learning task with volitional and instructed choice conditions. Parkinson's patients were tested twice within one week under both ON and OFF medication states, while controls participated in a single session. The study investigates neural correlates of reinforcement learning and decision-making in Parkinson's disease, with concurrent accelerometer recordings from the most tremor-affected hand.

Participants

56

Channels

67 (10-10)

Citations

2

Size

16.2 GB

Version

v1.0.0

Updated

Jul 10, 2026

VEPCON is a multimodal neuroimaging dataset comprising high-density EEG, structural MRI, and diffusion-weighted imaging from 20 participants performing visual discrimination tasks (face vs. scrambled faces, coherent vs. incoherent motion). The dataset includes preprocessed EEG single trials, individual brain parcellations at five spatial resolutions, structural connectomes derived from diffusion data, and EEG source imaging solutions based on individual anatomy. This resource supports multimodal methods development, structure-function relationship studies, and optimization of source imaging and graph analysis techniques.

Participants

20

Channels

128 (biosemi)

Citations

24

Size

58.2 GB

Version

v1.0.0

Updated

Jul 22, 2026

This dataset comprises intracranial electroencephalography (iEEG) recordings from 20 subjects with marked high-frequency oscillations (HFOs) during slow-wave sleep. The data includes ripple and fast ripple events detected and validated from the original publication, with electrode contacts selected to exclude motor and language-responsive sites. The dataset has been converted to BIDS format and includes HFO event annotations in standardized TSV files, facilitating validation of HFO detection algorithms.

Participants

20

Citations

96

Size

44.7 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises resting-state EEG recordings from 122 college-age participants with varying levels of depressive symptoms as measured by the Beck Depression Inventory. Participants completed two 6-minute resting sessions with eyes-open and eyes-closed conditions, with the first session occurring immediately after EEG setup and the second following approximately one hour of task performance. The data were collected between 2008-2010 in the John J.B. Allen lab at the University of Arizona and include clinical interview information for a subset of participants. NOTE: Data quality considerations include potential HEOG/VEOG mislabeling for some subjects, some channels with prior interpolation, and limited review of the second rest run. Subject 516 is missing rest2 data, and subject 544 was excluded from analyses due to unstable BDI scores between assessment timepoints.

Participants

122

Channels

66 (10-10)

Citations

14

Size

10.6 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises EEG recordings from 121 college-age participants (122 collected, 1 excluded) performing a probabilistic selection task, stratified by depression symptomatology as measured by the Beck Depression Inventory. Collected between 2008-2010 in the lab of John J.B. Allen at the University of Arizona, the data were acquired to investigate neural correlates of decision-making and reward processing in relation to depressive symptoms. Some participants underwent clinical interviews to confirm depression status. NOTE: Data quality considerations include potential mislabeling of HEOG/VEOG channels in some subjects, and some files have had channels interpolated already with no raw data available for reversion. Subject 544 was excluded due to unstable BDI scores between pre-assessment and test session.

Participants

122

Channels

66 (10-10)

Citations

89

Size

16.6 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises electroencephalography (EEG) recordings from 23 healthy college students performing a three-armed bandit gambling task with dynamically oscillating reward probabilities. The task was designed to investigate neural correlates of reward processing and reward prediction error during adaptive decision-making and task set generation. Each stimulus condition (blue, red, and green) had oscillating reinforcement probabilities (ranging from 20% to 90%) that moved in different phases across trials. Supplementary physiological recordings including corrugator EMG and skin conductance were acquired on most participants; however, data quality for these supplementary recordings was limited and they were not extensively analyzed. Data were collected in 2014 at the University of New Mexico's Cognitive Rhythms and Computation Lab.

Participants

23

Channels

64 (10-10)

Size

4.72 GB

Version

v1.0.0

Updated

Jul 10, 2026

This high-density EEG dataset comprises recordings from 20 healthy right-handed volunteers (10 females, 10 males, mean age 23 years) collected between 2014 and 2017 during four experimental conditions: resting state, visual naming, auditory naming, and working memory tasks. The dataset contains 256-channel EEG data acquired at 1000 Hz sampling frequency and is designed to investigate dynamic functional brain network reorganization across different cognitive states.

Participants

20

Channels

257 (egi-geodesic)

Citations

1

Size

76.8 GB

Version

v1.0.0

Updated

Jul 10, 2026