Discover datasets

The HID dataset is a neuroimaging collection of intracranial electroencephalography (iEEG) recordings curated and formatted according to BIDS standards (version 1.8.0). This dataset is derived from OpenNeuro dataset ds004851 (DOI: 10.18112/openneuro.ds004851.v2.1.0) and serves as a resource for neuroscience research on electrophysiological brain activity. The dataset is made available under the CC0 license to facilitate open science and data sharing. It contains iEEG recordings with associated metadata documenting electrode placement, recording parameters, sampling rates, and brain regions of interest.

Participants

66

Channels

72 (10-10)

Citations

2

Size

56.6 GB

Version

v1.0.0

Updated

Jul 10, 2026

The TX22 dataset investigates real-time prediction and management of trust-based decisions during simulated semi-automated driving in a leader-follower paradigm. This neuroimaging study examines how operators' trust in autonomous vehicle systems can be predicted and influenced through targeted feedback interventions, with the goal of resolving discrepancies between perceived trust and actual system trustworthiness to optimize joint human-automation performance.

Participants

17

Channels

64 (10-10)

HED

v8.1.0

Size

22.3 GB

Version

v1.0.0

Updated

Jul 10, 2026

T16 is an EEG neuroimaging dataset containing electroencephalography recordings organized according to the Brain Imaging Data Structure (BIDS) standard version 1.8.0. The dataset includes hierarchical event descriptors (HED) version 8.1.0 for detailed annotation of experimental events and conditions. The dataset comprises 185 files totaling 8.2 GB of EEG data with standardized metadata and event annotations to support reproducible neuroscience research.

Participants

14

Channels

64 (10-10)

HED

v8.1.0

Size

7.66 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises multi-channel EEG recordings from 27 healthy adults performing a sustained-attention driving task in a virtual-reality simulator across 62 sessions. The task involved event-related lane-departure paradigms where participants maintained vehicle position on a simulated highway, with recordings capturing 32-channel EEG (30 scalp + 2 mastoid references) sampled at 500 Hz alongside vehicle position data. The dataset includes approximately 82 hours of raw, unfiltered EEG data with over 27,000 lane-departure trials and associated behavioral markers, providing a resource for investigating fatigue, drowsiness, and sustained attention mechanisms.

Participants

27

Channels

32 (10-10)

Citations

68

HED

v8.2.0

Size

36.4 GB

Version

v1.0.0

Updated

Jul 10, 2026

TX15 is a BIDS-formatted EEG dataset (BIDS version 1.8.0) with HED (Hierarchical Event Descriptors) version 8.1.0 annotations. The dataset includes EEG recordings and associated metadata in standardized formats (.set, .fdt, .tsv, .json). This dataset is derived from OpenNeuro dataset ds004842 (v1.0.0) and has been processed and annotated with HED tags to support standardized neuroimaging research. Released under the CC0 license, this dataset is made openly available to support reproducible science and neuroimaging research.

Participants

14

Channels

64 (10-10)

Citations

2

HED

v8.1.0

Size

5.21 GB

Version

v1.0.0

Updated

Jul 10, 2026

The TX14 dataset comprises neuroimaging recordings collected during a local situational awareness task performed concurrently with supervisory control of a semi-autonomous vehicle. This dataset investigates the cognitive and neural correlates of human-machine interaction in military contexts, examining the trade-offs between maintaining situational awareness and vehicle control during autonomous system operation.

Participants

20

Channels

64 (10-10)

HED

v8.1.0

Size

7.31 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises electrophysiological recordings (EEG, ECG, EMG) collected from 9 adult burn patients in an intensive care unit during Music-Assisted Relaxation therapy sessions. As part of a randomized clinical trial (NCT04571255), participants underwent two recording sessions with pre-intervention baseline, intervention, and post-intervention phases. The study investigates the physiological effects of music therapy on pain perception and anxiety-depression levels in critically ill burn patients using clinical-grade equipment with standardized electrode montages.

Participants

9

Channels

8

Citations

1

Size

1.75 GB

Version

v1.0.0

Updated

Jul 10, 2026

This magnetoencephalographic (MEG) dataset comprises auditory oddball paradigm recordings from participants with first-episode psychosis and healthy controls, designed to investigate mismatch negativity (MMN) responses to pitch and duration deviants. The study includes three participant groups: healthy controls, first-episode schizophrenia, and first-episode affective psychosis patients. Data were collected as part of the Pittsburgh Early Psychosis Program between December 2017 and September 2021. The dataset includes clinical, neuropsychological, demographic, and medication data in the derivatives.

Participants

60

Citations

10

Size

120 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset contains intracranial EEG (iEEG) recordings from human patients, rodents, pigs, and non-human primates acquired using novel flexible, scalable, high-resolution micro-stereo-electrodes. The study evaluates the performance of these custom-fabricated depth electrodes for neural recording and includes direct electrical stimulation experiments to assess stimulation effects on brain activity. Raw and preprocessed epoched data are provided in iEEG-BIDS format with accompanying channel maps and derivatives.

Participants

1

Citations

4

Size

1.36 GB

Version

v1.0.0

Updated

Jul 10, 2026

EEG dataset from Experiment 2 of Grootswagers et al. (2021) investigating neural dynamics of task-relevant information prioritization. Participants performed a rapid serial visual presentation (RSVP) task with small objects embedded in large letters while EEG was recorded. This dataset examines how the brain prioritizes and processes behaviorally relevant stimuli in visual attention tasks.

Participants

20

Citations

29

Size

25.3 GB

Version

v1.0.0

Updated

Jul 10, 2026