Discover datasets

This dataset contains EEG, eye-tracking, and vehicle performance data collected during the BCIT Traffic Complexity study, in which subjects performed a simulated driving task under varying visual complexity and perturbation frequency conditions. The study aimed to identify biomarkers of driver fatigue by comparing EEG-based predictive algorithms to objective performance measures and subjective fatigue scales. Data collection took place at Teledyne Corporation in Durham, NC, and is related to companion datasets on Baseline Driving and Calibration Driving tasks.

Participants

29

Channels

64 (10-10)

Citations

39

HED

v8.0.0

Size

17.5 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains EEG and vehicle performance data from the BCIT Speed Control study, designed to investigate driver fatigue during extended, simulated driving tasks. Subjects performed continuous driving under cruise-controlled and manual speed conditions while EEG, steering, and lane-position data were recorded to identify biomarkers of fatigue-related performance decline. The study builds on the related Baseline Driving paradigm and contrasts fatigued driving conditions with a non-fatigued calibration session.

Participants

32

Channels

64 (10-10)

Citations

41

HED

v8.0.0

Size

36.2 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains EEG, eye-tracking, and simulated driving performance data collected during the BCIT Mind Wandering study, in which subjects performed a prolonged simulated driving task under varying background audio conditions (task-relevant, non-task-relevant, and internal focus) while responding to periodic lateral perturbations and a vigilance task requiring detection of police vehicles. The study aimed to identify EEG-based biomarkers of driver fatigue and mind wandering by comparing extended time-on-task driving performance to a non-fatigued calibration session. Data were collected at Teledyne Laboratories under a US Army Research Laboratory contract as part of a broader effort to develop predictive fatigue algorithms from neural and behavioral signals.

Participants

21

Channels

64 (10-10)

Citations

32

HED

v8.0.0

Size

23.9 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains EEG and driving performance data from the Baseline Driving study, part of the BCIT program investigating fatigue-related biomarkers during simulated driving tasks. Subjects performed a 60-minute driving task with EEG recorded at three different sites using varying channel configurations (64 or 256-channel Biosemi systems). The dataset supports research into predictive algorithms for detecting driver fatigue through EEG analysis and objective performance measures.

Participants

109

Channels

64 (10-10)

Citations

30

HED

v8.0.0

Size

302 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains EEG, eye-tracking, and behavioral data from the Basic Guard Duty study, part of a larger project examining sustained vigilance in realistic task settings. Participants performed a two-alternative forced-choice ID verification task, judging the validity of replica identification cards presented at varying rates, while high-density EEG (256+8 channels) and eye-tracking data were recorded. The task was designed to probe attentional and vigilance dynamics under varying cognitive load, complementing companion driving tasks not included in this release.

Participants

21

Channels

256 (biosemi)

Citations

25

HED

v8.0.0

Size

55.1 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains EEG, eye-tracking, and vehicle simulator data from the BCIT Calibration Driving study, part of the larger BCIT program investigating fatigue in driving performance. Data were collected from participants at three sites using identical driving simulator and EEG setups, with each session consisting of a 15-minute calibration driving task performed prior to other longer BCIT experimental tasks. The dataset is intended to serve as a baseline for non-fatigue-related driving performance for comparison with other same-subject recordings from longer fatigue-inducing tasks.

Participants

156

Channels

64 (10-10)

Citations

29

HED

v8.0.0

Size

124 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains scalp EEG recordings from 23 healthy young adults performing a Modified Sternberg Working Memory task, in which participants memorized subsets of letters while ignoring others, then responded to probe letters after a maintenance period. The study, conducted at the Swartz Center for Neural Computation (UCSD) in 2004-05, was designed to examine source-resolved EEG brain dynamics related to working memory encoding, maintenance, and retrieval. The dataset was curated and annotated using the Hierarchical Event Descriptors (HED) framework and shared via OpenNeuro and NEMAR in BIDS format.

Participants

23

Channels

69 (10-10)

Citations

88

HED

v8.0.0

Size

5.80 GB

Version

v1.0.0

Updated

Aug 19, 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

Citations

17

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)

Citations

27

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