Discover datasets

MIPDB is a multimodal neuroimaging resource comprising high-density EEG and eye-tracking data collected from 111 participants spanning childhood to adulthood. Participants completed a standardized battery of six cognitive and perceptual paradigms (resting state, surround suppression, naturalistic viewing, contrast-change detection, sequence learning, and symbol search) designed to probe information processing maturation across development. This dataset enables investigation of neurodevelopmental trajectories in sensory and cognitive processing.

Size

110 GB

Version

vv1.0.0

Updated

Jul 10, 2026

Participants

85

Size

126 GB

Version

vv1.0.0

Updated

Jul 10, 2026

A large longitudinal dataset of sensorimotor rhythm-based brain-computer interface (BCI) training in 62 healthy adults. The dataset comprises over 600 hours of EEG recordings collected across up to 11 training sessions per participant, containing more than 250,000 trials of motor-imagery tasks (left hand, right hand, both hands, and rest). This resource enables investigation of BCI learning dynamics and algorithm development for non-invasive neural control applications.

Participants

62

Channels

60 (10-10)

Citations

57

HED

v8.4.0

Size

371 GB

Version

vv1.0.1

Updated

Jul 10, 2026

A derivative EEG dataset comprising checkerboard m-sequence-based code-modulated visual evoked potentials (c-VEP) recordings from 16 healthy participants across 8 sessions. The dataset evaluates the influence of spatial frequency in visual stimuli for brain-computer interface applications, with 16-channel EEG data sampled at 256 Hz and annotated with HED 8.4.0 event labels for two stimulus intensity classes.

Participants

16

Citations

6

HED

v8.4.0

Size

622 MB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset comprises EEG recordings from 16 healthy participants performing a code-modulated visual evoked potential (c-VEP) brain-computer interface task using p-ary m-sequences. The study evaluates non-binary m-sequence stimulation patterns to enhance user comfort in c-VEP-based BCIs. Data were collected across 5 sessions per subject with 8 runs per session at 256 Hz sampling rate using 16 EEG channels, providing a comprehensive resource for BCI research and algorithm development.

Participants

16

Citations

27

HED

v8.4.0

Size

764 MB

Version

vv1.0.0

Updated

Jul 10, 2026

Participants

70

Channels

64 (10-10)

Citations

97

HED

v8.4.0

Size

2.80 GB

Version

vv1.0.0

Updated

Jul 10, 2026

Participants

59

Channels

8 (10-10)

Citations

3

HED

v8.4.0

Size

396 MB

Version

vv1.0.0

Updated

Jul 10, 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

vv2.0.0

Updated

Jul 10, 2026

NEMAR Dataset nm000104: emg2qwerty - EMG-based typing detection

Participants

108

Size

372 GB

Version

vv2.0.0

Updated

Jul 10, 2026

NEMAR Dataset nm000105: discrete_gestures - Discrete hand gesture detection from EMG

Participants

100

Size

34.3 GB

Version

vv2.0.0

Updated

Jul 10, 2026