Discover datasets

A multicenter intracranial electroencephalography (iEEG) dataset comprising segmented 3-second single-channel clips from epilepsy patients, annotated for graphoelement classification and artifact detection. The dataset includes clinical metadata such as seizure onset zone (SOZ) flags, electrode anatomy, and reviewer annotations, making it suitable for developing and validating automated signal classification algorithms in clinical neurophysiology.

Participants

14

Size

20.8 GB

Version

v1.0.2

Updated

Jul 10, 2026

A multicenter intracranial electroencephalography (iEEG) dataset comprising segmented 3-second single-channel clips from epilepsy patients, annotated for graphoelement classification and artifact detection. The dataset includes 10,000+ clips from multiple subjects with preserved clinical metadata including seizure onset zone (SOZ) flags, electrode anatomy, and reviewer annotations. This resource supports the development and validation of automated signal processing algorithms for clinical neurophysiology applications.

Participants

24

Size

15.0 GB

Version

v1.0.2

Updated

Jul 10, 2026

This dataset comprises EEG recordings from 15 healthy participants performing self-initiated reach-and-grasp motor tasks using three different recording 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 a total of 7,200 trials. Participants executed palmar and lateral grasp actions toward objects while EEG signals were recorded. 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)

HED

v8.4.0

Size

2.08 GB

Version

v1.0.1

Updated

Jul 10, 2026

A longitudinal motor imagery EEG dataset from 18 brain-computer interface (BCI)-naive subjects acquired across 6 sessions (1 offline + 5 online) to investigate transfer learning and domain adaptation for calibration-free BCI training. Subjects performed left/right hand motor imagery tasks with visual feedback using 22 EEG channels sampled at 512 Hz. The dataset compares Generic Recentering (unsupervised) and Personally Assisted Recentering (supervised) domain adaptation frameworks, with features extracted as covariance matrices and classified using Riemannian geometry-based methods.

Participants

18

Channels

22 (10-10)

HED

v8.4.0

Size

1.66 GB

Version

v1.0.1

Updated

Jul 10, 2026

An EEG dataset of imagined speech from 15 healthy participants comparing traditional cue-based and gamified (Pac-Man maze) paradigms for brain-computer interface applications. The dataset comprises 1,800 trials across four Spanish directional commands recorded at 500 Hz from 24 electrodes using the mBrainTrain Smarting system. This derivative dataset enables systematic evaluation of paradigm design effects on imagined speech decoding performance.

Participants

15

Channels

24 (10-10)

HED

v8.4.0

Size

829 MB

Version

v1.0.1

Updated

Jul 10, 2026

This dataset comprises functional near-infrared spectroscopy (fNIRS) recordings from human auditory cortex in individuals with subjective tinnitus and matched controls. The study investigates the relationship between subjective tinnitus severity and objective neurophysiological changes in auditory cortex function, utilizing a NIRx NIRSport2 system for non-invasive optical neuroimaging.

Participants

63

Size

274 MB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises electroencephalography (EEG) recordings collected to investigate the relationship between auditory streaming—the perceptual organization of sound sequences—and interoceptive awareness. The study examines how the brain processes complex auditory stimuli and integrates this information with internal bodily signals, contributing to our understanding of sensory integration and conscious perception.

Participants

22

Channels

1 (other)

Size

7.24 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises whole-head functional near-infrared spectroscopy (fNIRS) recordings from 38 subjects performing spatial-attention tasks in a cocktail-party paradigm with simultaneous eye-tracking. The study includes both overt attention tasks with eye movements and covert auditory attention tasks with central fixation, along with baseline and resting-state conditions. The fNIRS system captured 1134 measurement channels (56 sources, 144 detectors) at approximately 8.99 Hz sampling rate, providing comprehensive hemodynamic measurements during naturalistic audiovisual stimulus processing.

Participants

38

Size

32.3 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises synchronized multimodal neurophysiological and biomechanical recordings from 128-channel EEG, electromyography (EMG), electrooculography (EOG), and motion capture during a perturbed beam-walking task. Participants performed four 10-minute sessions of standing or walking on a narrow balance beam while exposed to sensorimotor perturbations (visual field rotations or waist pulls). The dataset includes preprocessed EEG data with identified good channels and independent component analysis results, enabling investigation of cortical mechanisms underlying balance control and responses to perturbations.

Participants

30

Channels

128 (biosemi)

Citations

162

Size

10.9 GB

Version

v1.0.0

Updated

Jul 10, 2026

Cambridge resting-state fNIRS dataset. This is a raw fNIRS neuroimaging dataset containing resting-state functional near-infrared spectroscopy recordings mirrored from OpenNeuro (ds007719). The dataset includes SNIRF format data files and associated metadata in BIDS format. For complete dataset details, participant information, and acquisition parameters, please refer to the source dataset on OpenNeuro.

Participants

65

Size

8.62 GB

Version

v1.0.0

Updated

Jul 10, 2026