Discover datasets

This dataset comprises continuous EEG recordings from 12 subjects during a visual attention task, originally published by Gramann et al. (2010) to investigate dimension-based attention modulation of early visual processing. The dataset includes 64-channel scalp EEG data with pre-computed ICA decomposition and expert-annotated independent component labels, providing a resource for studying automatic component classification and visual attention mechanisms. The original data was subsequently used by Frølich et al. (2015) to investigate automatic labeling of independent components in ICA. Data was converted to BIDS format by Austin J. Brockmeier and Carlos H. Mendoza-Cardenas with permission from Klaus Gramann, following a data copy provided by Laura Frølich.

Participants

12

Channels

64 (10-10)

Size

5.63 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset contains raw electroencephalography (EEG) recordings collected during a social observation task. Participants viewed videos of social interactions while EEG was recorded. The dataset is organized according to the Brain Imaging Data Structure (BIDS) standard and includes EEG data from participants performing a passive social observation paradigm. This resource provides neurophysiological measurements suitable for investigating neural correlates of social perception, action observation, and interpersonal understanding. The dataset includes continuous EEG recordings, event markers for stimulus presentation, and participant demographic information. For complete technical details regarding electrode configuration, sampling rate, filter settings, and number of participants, please refer to the README.md file and dataset_description.json.

Participants

47

Channels

64 (10-10)

Size

12.1 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises high-density electroencephalography (EEG) recordings acquired during a visual stimulation task. Raw data are organized according to the EEG-BIDS specification and stored in BrainVision format. The dataset represents a single session of data collection and serves as a resource for investigating neural responses to visual stimuli.

Participants

31

Channels

64

Size

17.6 GB

Version

v1.0.0

Updated

Jul 10, 2026

A resting-state EEG dataset acquired from 128 channels at 1000 Hz sampling rate using an Electrical Geodesics amplifier system, complemented by structural MRI data from a GE MR750 scanner. The dataset includes preprocessed EEG signals with artifact removal and channel interpolation, as well as high-resolution anatomical imaging. This multimodal neuroimaging resource enables investigation of whole-brain electrophysiological functional connectivity dynamics during rest.

Participants

34

Channels

128 (other)

Size

3.00 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises intracranial EEG recordings from 23 patients with drug-resistant epilepsy undergoing stereo-EEG presurgical evaluation. The dataset includes 41 high-frequency stimulation events that evoked negative motor responses, with 24-second iEEG recordings per stimulation event (9-10 seconds pre-stimulation, up to 5 seconds stimulation, and 9-10 seconds post-stimulation). Stimulation parameters, contact pairs, current intensities, and evoked effects are documented in event files, enabling analysis of cortical responses to electrical stimulation.

Participants

21

Size

958 MB

Version

v1.0.0

Updated

Jul 10, 2026

This longitudinal neuroimaging study investigates neural mechanisms of motor skill learning, consolidation, and retention using magnetoencephalography (MEG) combined with structural MRI. Thirty-one healthy right-handed adults performed a sequential finger-tapping task during an initial training session followed by retest sessions at approximately 24 hours and 30 days post-training. The dataset includes continuous MEG recordings, high-resolution anatomical MRI, behavioral performance metrics, eye-tracking, pupillometry, and electromyography data synchronized across all sessions.

Participants

31

Size

95.7 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises electroencephalography (EEG) recordings from young adult participants during resting state and auditory oddball task conditions. Data were collected under two experimental conditions: a control condition and a shock threat condition involving threat of unpredictable shock. The dataset includes both passive and active variants of the auditory oddball task, as well as resting state recordings with eyes open and closed, designed to investigate locus coeruleus-noradrenaline system function and its relationship to attention and arousal.

Participants

68

Channels

65 (egi-geodesic)

Size

64.1 GB

Version

v1.0.0

Updated

Jul 10, 2026

MEG-SCANS is a comprehensive magnetoencephalography dataset comprising raw and MaxFiltered recordings from 24 German-speaking participants engaged in auditory experiments. The dataset includes approximately one hour of stimuli per participant consisting of audiobooks, sentences from the Oldenburger Matrix Sentence Test at varying intelligibility levels for speech reception threshold assessment, and chirp stimuli for signal quality evaluation. Each participant's data includes raw and processed MEG recordings, empty-room recordings, structural MRI, behavioral audiograms, and corresponding audio stimulus materials, organized according to BIDS standards to facilitate large-scale encoding/decoding analyses of neural responses to speech.

Participants

24

Size

204 GB

Version

v1.0.0

Updated

Jul 10, 2026

3M-CPSEED is an EEG dataset comprising recordings from 20 native Chinese speakers performing overt, silently articulated, and imagined speech tasks using Chinese Pinyin phonemes. The dataset captures neural activity across 6 initials (m, f, j, l, k, ch) and 4 finals (a, i, u, ü), with 1600 trials per participant. This resource supports investigation of neural mechanisms underlying speech production.

Participants

20

Channels

32 (10-10)

Size

15.1 GB

Version

v1.0.0

Updated

Jul 10, 2026

The LIGHT Hypnotherapy dataset comprises EEG and ECG recordings from guided imagery hypnotherapy sessions designed to enhance well-being through eudaemonic visualization techniques. This derivative dataset is derived from OpenNeuro ds006437 and includes physiological recordings from in-lab sessions with annotated hypnotherapist phase transitions. Participants underwent baseline resting EEG assessment followed by multiple hypnotherapy sessions incorporating structured visualization protocols (relaxation induction, imagined environments, guided descent, and emergence phases), providing a resource for investigating neural correlates of guided imagery and therapeutic hypnotherapy.

Participants

9

Channels

64 (10-10)

Size

4.31 GB

Version

v1.0.0

Updated

Jul 10, 2026