Discover datasets

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

vv1.0.0

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

vv1.0.0

Updated

Jul 10, 2026

This dataset comprises EEG recordings from three experiments investigating the effects of selective attention on auditory brainstem and cortical responses to natural speech. Participants listened to audiobook narrations under different stimulus configurations (diotic, dichotic, and passive listening conditions) while EEG was recorded from both cortical (32-channel active montage) and subcortical (passive bipolar montage) electrode arrays. The study examines whether selective attention modulates the auditory brainstem response to natural speech stimuli.

Participants

66

Channels

32 (10-10)

Size

103 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset contains electrophysiological recordings from 33 participants performing visual and auditory surprise detection tasks. The study investigates electrophysiological markers associated with surprise-induced failures of awareness across sensory modalities. EEG data were collected during counterbalanced presentation of visual and auditory oddball-like tasks, with detailed event annotations and preprocessing information provided for reproducibility.

Participants

33

Channels

16 (10-20)

Size

521 MB

Version

vv1.0.0

Updated

Jul 10, 2026

This BIDS dataset demonstrates the application of the Hierarchical Event Descriptor (HED) schema library for Standardized Computer-based Organized Reporting of EEG (SCORE) to annotate intracranial EEG recordings. The dataset contains iEEG data from a single subject acquired during clinical photic stimulation at Mayo Clinic Rochester, with machine-readable event annotations validated against both BIDS and HED standards.

Participants

1

HED

vscore_2.0.0

Size

32.0 MB

Version

vv1.0.0

Updated

Jul 10, 2026

PhysioMotion_Artifact is an electrophysiological dataset organized in BIDS format containing EEG recordings with associated physiological motion artifacts. The dataset serves as a resource for studying and developing artifact detection and correction methods in EEG analysis, with potential applications in motor imagery and brain-computer interface research.

Participants

30

Channels

59 (10-10)

Size

36.2 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset investigates how expectation modulates repetition suppression in nociceptive processing. It contains raw neuroimaging data examining the neural mechanisms underlying pain perception and the influence of cognitive expectations on pain-related neural responses.

Participants

36

Channels

32 (10-10)

Size

42.7 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset contains EEG recordings from Experiment 2 of a study investigating whether memory reactivation levels are affected by anticipated interference during a dual-task paradigm. Participants performed a visual working memory task with varying cognitive load (single vs. dual task conditions), where they memorized lateral objects and later identified them among probes, with half the blocks including distractor identification tasks. The dataset includes raw EEG data collected during this experiment. For preprocessing details, see the related preprint and OSF repository listed in related_identifiers.

Participants

56

Channels

30 (10-10)

Size

40.1 GB

Version

vv1.0.0

Updated

Jul 10, 2026

The Mouse Sleep Staging Validation dataset (MSSV) comprises EEG and EMG recordings from 92 healthy mice collected across five international laboratories. The dataset includes expert-scored sleep stages and is designed to support validation of automated sleep staging algorithms in rodent models. All recordings have been standardized to 128 Hz sampling rate with 4-second epochs and formatted according to BIDS specifications.

Participants

92

Channels

1

Size

6.06 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset contains raw MEG recordings, anatomical T1-weighted MRI scans, and behavioral data from an audiovisual speech memory study. Participants performed a three-phase task involving encoding of audiovisual speech movies with synchrony judgments, a distractor task, and retrieval of speech memories cued by speaker faces. The study investigates how neocortical and hippocampal theta oscillations support audiovisual integration and memory replay of speech information.

Participants

30

Size

172 GB

Version

vv1.0.0

Updated

Jul 10, 2026