Discover datasets

Raw multimodal recordings of 18-channel EEG and functional near-infrared spectroscopy (fNIRS) from seven participants with orthopedic impairment performing motor imagery tasks. Each participant completed three sessions of 40 trials, with four motor imagery tasks (reach, twist, lift, grasp) presented in random order. The dataset supports research on multimodal brain-computer interfaces for people with motor impairments.

Participants

7

Channels

18

Citations

2

Size

635 MB

Version

v1.0.0

Updated

May 25, 2026

This case study records physiological and EEG data from a self-described practitioner of energy medicine who performed directed therapeutic intent on live and damaged cells. Across 60 double-blind treatment and control sessions, cell types (live, dead/x-rayed, or medium only) were randomized and concealed from both the practitioner and the experimenter. Matched control cells treated by a sham therapist provide behavioral measures of cellular outcomes.

Participants

1

Channels

65 (10-10)

Size

1.68 GB

Version

v1.0.0

Updated

Jun 26, 2026

A multichannel EEG dataset of self-paced (freewill) reach-and-grasp movements recorded from 23 healthy right-handed participants across 49 sessions. On each of 6808 trials the participant freely chose one of four cups, two filled with water and two empty, and decided when to move. Recordings were made at 250 Hz with a 31-channel scalp EEG montage plus EOG and auxiliary channels, to support brain-machine interface research on natural motor execution.

Participants

23

Channels

31 (10-10)

HED

v8.4.0

Size

2.53 GB

Version

v1.0.0

Updated

Oct 8, 2026

EEG dataset from the PROTEUS brain-computer interface (BCI) project in Bordeaux, released for the EEG/EMG Foundation Challenge 2026 (Track 02). It contains recordings from 10 participants across 14 sessions (112 runs) performing three cued mental tasks: kinesthetic motor imagery, mental subtraction and word generation. Runs include resting baselines, calibration runs with sham feedback and online runs with real feedback, using Graz and BrainHero interfaces.

Participants

10

Channels

41 (10-10)

Size

1.48 GB

Version

v1.0.0

Updated

Oct 1, 2026

M3CV is a multi-subject, multi-session, multi-task EEG database with 64-channel recordings from 95 healthy young adults. Each subject was recorded on two different days across six paradigms covering 13 distributed signal types: resting states, motor execution, transient visual, auditory and somatosensory responses, SSVEP, P300, SSAEP and SSSEP. The data were originally released for an EEG-based biometrics competition on Kaggle. This BIDS version reconstructs pseudo-continuous EEG from the distributed pre-epoched, preprocessed 250 Hz files.

Participants

95

Channels

64 (10-10)

Citations

31

Size

21.6 GB

Version

v1.0.0

Updated

May 11, 2026

An EEG dataset from the NeuroTechs group, collected in the context of STEM (science, technology, engineering and mathematics) skills. Recordings were acquired with a Unicorn wearable EEG system through its Python API, and values are provided in microvolts. The dataset is organized according to BIDS with HED annotations.

Participants

63

Channels

8 (10-10)

Size

1.39 GB

Version

v1.0.0

Updated

Jun 29, 2026

NEMAR Dataset nm000103: HBN-EEG NC - Healthy Brain Network EEG data

Participants

447

Channels

129 (egi-geodesic)

HED

v8.3.0

Size

250 GB

Version

v2.0.0

Updated

Feb 23, 2026

This dataset contains longitudinal resting-state EEG recordings from 43 healthy adults across four sessions spanning about two years, with an average inter-session interval of 7.2 months. It was collected to evaluate the test-retest reliability of EEG measures processed with an automated pipeline combining independent component analysis and wavelet-enhanced artifact removal. The data support analyses of neural components, relative power in regions of interest, and the longitudinal stability of quantitative EEG.

Participants

45

Channels

58 (10-10)

Citations

5

Size

21.1 GB

Version

v1.0.0

Updated

Mar 8, 2026

This dataset contains 32-channel EEG recordings acquired during a sham neurofeedback experiment in a virtual reality environment. The study examined how feedback valence (positive, negative, or none) modulates alpha-band activity during an attentional task. Each participant completed positive, negative, control, and resting-state (eyes open/eyes closed) conditions.

Participants

36

Channels

29 (10-10)

Size

10.4 GB

Version

v1.0.0

Updated

Jun 29, 2026

A mobile brain/body imaging (MoBI) dataset of 18 participants walking on a treadmill at constant speed while stepping in time to an auditory tone sequence. Participants adapted step length and rate to occasional shifts in the tempo of the pacing stimulus, to a faster or slower tempo. The dataset supports study of cortical dynamics during gait adaptation.

Participants

20

Channels

108 (10-05)

Size

32.0 GB

Version

v1.0.0

Updated

Jun 20, 2026