Discover datasets

The BCIT Traffic Complexity dataset comprises extended neurophysiological recordings during simulated driving tasks designed to assess fatigue-related performance changes. Participants performed continuous driving in a simulator while EEG, eye tracking, and vehicle performance data were collected simultaneously. The study manipulated visual complexity and perturbation frequency to investigate driver fatigue biomarkers and brain-behavior interactions during sustained attention tasks.

Participants

29

Channels

64 (10-10)

HED

v8.0.0

Size

17.5 GB

Version

v1.0.0

Updated

Jul 10, 2026

The BCIT Speed Control dataset comprises extended time-on-task EEG recordings from subjects performing simulated driving tasks designed to assess fatigue-related performance changes. Participants completed two 45-minute driving conditions with varying levels of control responsibility while experiencing periodic vehicle perturbations. The dataset includes 64-channel EEG data plus 8 additional channels (4 EOG and 2 mastoid channels) recorded at 2048 Hz sampling rate, vehicle performance metrics, and behavioral measures of fatigue, providing a resource for investigating brain-behavior interactions and fatigue biomarkers in sustained attention tasks.

Participants

32

Channels

64 (10-10)

HED

v8.0.0

Size

36.2 GB

Version

v1.0.0

Updated

Jul 10, 2026

The BCIT Mind Wandering dataset comprises electroencephalography (EEG), eye tracking, and vehicle performance data collected during prolonged simulated driving tasks designed to assess fatigue-related biomarkers and driver performance under different cognitive load conditions. Participants performed 30-minute driving scenarios with three types of background audio (task-relevant, non-task-relevant, and internal focus) while responding to vigilance tasks and managing vehicle perturbations. This dataset extends prior driving research by incorporating extended time-on-task measurements and novel audio manipulations to investigate the relationship between brain activity, mind wandering, and driving performance.

Participants

21

Channels

64 (10-10)

HED

v8.0.0

Size

23.9 GB

Version

v1.0.0

Updated

Jul 10, 2026

The BCIT Baseline Driving dataset comprises extended time-on-task EEG recordings from subjects performing a 60-minute simulated driving task across three research sites. Designed to assess fatigue-related performance degradation through novel EEG biomarkers, the study collected high-density EEG data (64 or 256 channels) synchronized with objective driving performance metrics including steering corrections, lane position, and reaction times to vehicle perturbations. This dataset serves as a foundational resource for investigating the neurophysiological correlates of driver fatigue and developing predictive algorithms for fatigue detection.

Participants

109

Channels

64 (10-10)

HED

v8.0.0

Size

302 GB

Version

v1.0.0

Updated

Jul 10, 2026

The BCIT Basic Guard Duty dataset comprises EEG, eye-tracking, and behavioral data collected during a sustained vigilance task in which participants verified replica identification cards against reference images. Subjects performed ten 5-minute blocks of the guard duty task with varying ID presentation rates (1-25 per minute) while seated in a driving simulator. This dataset provides multimodal neurophysiological and performance measures of cognitive fatigue and attention during a realistic security screening task.

Participants

21

Channels

256 (biosemi)

HED

v8.0.0

Size

55.1 GB

Version

v1.0.0

Updated

Jul 10, 2026

The BCIT Calibration Driving dataset comprises electroencephalography (EEG) recordings collected during a standardized 15-minute driving simulator task designed to establish baseline, non-fatigued performance metrics. Participants controlled vehicle steering on a simulated straight road while responding to lateral perturbations, with data collected across three sites: Army Research Laboratory (Aberdeen, MD), Teledyne Corporation (Durham, NC), and Science Applications International Corporation (Louisville, CO), using 64- or 256-channel Biosemi EEG systems. This calibration dataset serves as the foundational component for fatigue-related driver performance prediction algorithms within the broader BCIT neuroimaging program.

Participants

156

Channels

64 (10-10)

HED

v8.0.0

Size

124 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises scalp EEG recordings from 23 healthy young adults performing a modified Sternberg working memory task. Participants selectively memorized sequences of letters while ignoring distractors, maintained them during a delay period, and responded to probe letters via button press. The study investigates source-resolved EEG brain dynamics underlying working memory encoding, maintenance, and retrieval processes, with auditory feedback provided for response accuracy.

Participants

23

Channels

69 (10-10)

HED

v8.0.0

Size

5.80 GB

Version

v1.0.0

Updated

Jul 10, 2026

This magnetoencephalography (MEG) dataset comprises neuroimaging data collected to establish standardized protocols for cross-site pooling of MEG data. The dataset demonstrates the application of BIDS formatting to MEG neuroimaging, facilitating data harmonization and reproducible analysis across multiple research institutions.

Participants

9

Size

77.2 GB

Version

v1.0.0

Updated

Jul 10, 2026

The Advanced Guard Duty dataset comprises EEG, eye tracking, and behavioral data collected during a sustained vigilance task involving verification of replica identification cards. Subjects performed a 50-minute guard duty task organized into ten 5-minute blocks with varying ID presentation rates (1-25 per minute) and verification criteria. This dataset provides neurophysiological and performance measures of cognitive workload and fatigue in a realistic security screening scenario.

Participants

27

Channels

256 (biosemi)

HED

v8.0.0

Size

67.6 GB

Version

v1.0.0

Updated

Jul 10, 2026

The BCIT Auditory Cueing dataset comprises EEG, eye-tracking, and vehicle performance data collected during a prolonged simulated driving task designed to assess driver fatigue and cognitive state. Subjects performed two 45-minute driving conditions with either random or predictive auditory cues preceding lateral vehicle perturbations, while continuous measurements of steering behavior, reaction times, and subjective fatigue scales were recorded. This dataset extends prior driving research by examining the relationship between neural biomarkers and fatigue-related performance decrements in a controlled, high-frequency perturbation environment.

Participants

17

Channels

64 (10-10)

HED

v8.0.0

Size

20.4 GB

Version

v1.0.0

Updated

Jul 10, 2026