Discover datasets

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 simultaneous EEG-fMRI recordings from 22 participants (ages 23-51) during naturalistic viewing, collected at the Nathan Kline Institute. The 64-channel EEG data (61 cortical channels, 2 EOG, 1 ECG) was acquired concurrently with fMRI, supplemented by eye-tracking and respiratory recordings. The dataset includes demographic information and behavioral assessments (sleep quality, caffeine intake) to investigate correlations between electrical brain activity and hemodynamic fluctuations during naturalistic stimulation.

Participants

22

Channels

61 (10-10)

Citations

41

Size

256 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises 64-channel EEG recordings from 11 healthy participants performing an auditory P300-based brain-computer interface task using selective attention to multiple tone streams. Participants attended to one of three auditory streams of musical tones and counted target stimuli while P300 event-related potentials were recorded. Classification using Riemannian geometry achieved >80% accuracy for 5 subjects and >75% for 9 subjects, demonstrating the feasibility of multi-class auditory BCIs based on auditory stream segregation.

Participants

11

Channels

64 (10-10)

Citations

11

HED

v8.4.0

Size

6.31 GB

Version

v1.0.4

Updated

Aug 18, 2026

This dataset contains resting-state EEG recordings from 140 juvenile participants in Colombia, including 74 juvenile offenders and 66 non-offender controls, collected to study neurocognitive patterns associated with delinquency. Recordings were acquired using a 128-channel Biosemi ActiveTwo system during alternating eyes-closed/eyes-open resting-state paradigms. The dataset includes both preprocessed EEG data and extracted spectral power features (mean power, RMS, standard deviation, min/max power, skewness, kurtosis) across delta, theta, alpha, and beta frequency bands for each channel and epoch.

Participants

140

Channels

128 (other)

Size

8.13 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises EEG recordings from 15 healthy subjects performing an auditory brain-computer interface task based on the ASME (Auditory Stream segregation Multiclass ERP) paradigm. The study investigates two strategies for achieving four-class classification: ASME-4stream (four independent streams with single target stimuli) and ASME-2stream (two streams with dual target stimuli each). EEG data were recorded at 1000 Hz from 64 channels and analyzed using event-related potential methods and linear discriminant analysis classification, achieving accuracies of 83% and 86% respectively.

Participants

15

Channels

64 (10-10)

Citations

6

HED

v8.4.0

Size

23.5 GB

Version

v1.0.4

Updated

Aug 18, 2026

This dataset comprises electroencephalographic recordings from 12 healthy subjects during music listening with and without a passive head-mounted display (PHMD). The study employed a 16-channel EEG system sampling at 512 Hz. A passive head-mounted display is a head-mounted device without integrated electronics, consisting of a smartphone holder. The dataset provides raw, unfiltered EEG data in mat and csv formats, designed to support research on the effects of head-mounted displays and auditory stimuli on brain activity. This is a BIDS-converted derivative of the original Zenodo dataset (10.5281/zenodo.2617084).

Participants

12

Channels

16 (10-10)

Citations

19

HED

v8.4.0

Size

516 MB

Version

v1.0.5

Updated

Aug 18, 2026

This dataset contains EEG recordings from elderly patients with dementia undergoing 40Hz auditory gamma-band entrainment sessions. The study investigates whether auditory stimulation modulated at 40Hz can entrain brain oscillations and enhance functional connectivity, particularly within the default mode network, as a potential intervention for Alzheimer's disease symptoms. Both short and long entrainment sessions were conducted to accommodate participant tolerance, with EEG data collected using a 19-channel 10/20 system setup.

Participants

35

Channels

19 (10-20)

Citations

32

Size

356 MB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises EEG/ERP recordings collected from a sample of healthy adults performing multiple cognitive tasks, including an extended multi-source interference task (MSIT+), a 3-stimuli oddball task, a control simple reaction task (SRT), and a resting-state protocol. It is intended to support research on cognitive control, attention, and resting-state brain dynamics using electrophysiological methods.

Participants

42

Channels

127 (10-05)

Citations

18

Size

77.4 GB

Version

v1.0.0

Updated

Aug 19, 2026

The RECAP-EEG dataset provides resting-state electroencephalography recordings from 21 neurotypical undergraduate students collected before and after different study interventions (active retrieval practice, passive review, and control conditions) at the Federal University of Paraíba, Brazil. The dataset aims to support research into the neural correlates of learning, retrieval practice, and educational neuroscience. Recordings include pre- and post-intervention resting-state EEG with eyes-open and eyes-closed blocks.

Participants

21

Channels

31

Citations

1

Size

1.32 GB

Version

v1.0.0

Updated

Aug 19, 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