Discover datasets

This dataset contains MEG recordings from participants performing a risky decision-making task alongside a localizer task and a probability learning task. It was collected to investigate heuristics in risky decision-making and their relationship to preferential neural representation of choice- and outcome-related information. The dataset includes raw MEG data and derivative event and epoched data tables supporting analyses reported in an associated preprint.

Participants

21

Size

431 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises stereoelectroencephalography (sEEG) recordings from patients performing a forced two-choice response task, collected in the epilepsy monitoring unit at Oregon Health & Science University. The data extends characterization of movement-related neural oscillations using intracranial electrode recordings, providing insights into canonical motor-related activity patterns across distributed brain regions.

Participants

8

Citations

5

Size

14.5 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

BIDS-EMG dataset - HDsEMG recordings of tibialis anterior during isometric contractions at 30% and 50% MVC, 6 subjects, 256-channel grids (MUniverse benchmark)

Participants

6

Size

448 MB

Version

v1.0.1

Updated

Jul 10, 2026

This dataset contains scalp EEG recordings from 28 participants performing or imagining upper-limb rehabilitation exercises under a multi-paradigm protocol. It was designed to support research on motor-imagery-based brain–computer interfaces (BCI) for upper-limb rehabilitation. The data have been converted to BIDS format from the original dataset published by Chang et al. (2025).

Participants

28

Channels

59 (10-10)

Citations

3

HED

v8.4.0

Size

47.1 GB

Version

v1.0.5

Updated

Aug 20, 2026

This dataset presents multimodal simultaneous fMRI/EEG data collected from participants performing an auditory category learning task, alongside resting-state fMRI scans. Each dataset includes 63-channel EEG with additional ECG, EOG, facial EMG, and skin conductance recordings, a physiological file capturing respiration and finger-pulse signals, and structural MRI (T1-weighted and PD-weighted UTE) scans for anatomical reference and electrode localization. Collected at the Combinatorial NeuroImaging core facility of the Leibniz Institute for Neurobiology, the data support research into multi-dimensional auditory category learning and its neural correlates.

Participants

34

Channels

72 (10-10)

Citations

9

Size

6.43 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains continuous 64-channel scalp EEG recordings from 12 right-handed subjects performing a visual attention task designed to examine dimension-based attentional modulation of early visual processing. The data include independent component analysis (ICA) decompositions with expert-annotated component labels, originally collected for a study on visual attention and later reused for research on automatic classification of independent components. The dataset was converted to BIDS format from the original recordings with permission from the original authors.

Participants

12

Channels

64 (10-10)

Citations

35

Size

5.63 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises EEG recordings from 15 healthy participants performing reach-and-grasp motor imagery tasks using three different electrode systems: gel-based laboratory equipment, water-based mobile EEG, and dry-electrode mobile EEG. Data were acquired at 256 Hz from 58 EEG channels plus 6 EOG channels across three sessions with 7200 total trials. Participants executed palmar grasp (toward glass) and lateral grasp (toward spoon) actions. The study investigates the feasibility of decoding natural reach-and-grasp neural correlates across different EEG acquisition modalities for brain-computer interface applications.

Participants

45

Channels

58 (10-05)

Citations

51

HED

v8.4.0

Size

8.67 GB

Version

v1.0.3

Updated

Aug 18, 2026

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

Participants

100

Size

20.6 GB

Version

v2.0.0

Updated

Jul 10, 2026

This dataset is a NEMAR re-host and BIDS conversion of the emg2pose benchmark, comprising surface electromyography (EMG) recordings paired with hand pose labels for wrist-worn sEMG-based hand pose estimation. It includes 16-channel, 2 kHz sEMG recordings synchronized with joint-angle labels derived from a 26-camera motion-capture rig, spanning 193 users, 370 hours, and approximately 80 million labeled frames across 29 behavioral stages.

Participants

97

Size

740 GB

Version

v1.0.3

Updated

Aug 31, 2026