Discover datasets

This dataset comprises intracranial EEG recordings from 14 epilepsy patients implanted with clinical surface and depth electrodes, collected during visual stimulation tasks between 2017-2020. Participants viewed grayscale patterns with varied spatial and temporal properties, as well as color images from six semantic categories, while performing a fixation task. The dataset includes raw voltage data, common-average-referenced recordings, broadband responses, preprocessed epochs, and surface reconstructions with electrode localizations, enabling investigation of neural dynamics in human visual cortex.

Participants

14

Size

57.9 GB

Version

vv1.0.0

Updated

Jul 22, 2026

This randomized controlled trial investigates the differential effects of forward and backward span training on working memory capacity. Event-related potentials (ERPs) were recorded during a distractor version of the change detection task at pre-, mid-, and post-test timepoints, while behavioral measures were collected from additional cognitive tasks. The study demonstrates that both training types enhance working memory maintenance compared to control conditions, with backward span training providing superior benefits for interference control based on ERP indices.

Participants

71

Size

77.1 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset comprises electroencephalography (EEG) recordings from 21 participants learning to perform two distinct drumming patterns at three different tempos using keyboard responses. Participants received real-time visual feedback indicating response timing accuracy (early, on-time, or late) relative to target durations. The study investigates motor learning and timing control during sequential pattern acquisition, with detailed event markers capturing metronome beats, response types, and feedback outcomes across 72 trials per participant.

Participants

21

Channels

31 (10-10)

Size

4.76 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This EEG dataset comprises electrophysiological recordings from 57 obese and non-obese preadolescents performing a stop-signal task, designed to investigate the effect of obesity on inhibitory control mechanisms. Data were acquired using a 128-channel Geodesic Hydrocell Sensor Net system and include participant demographics (age, gender, BMI, weight status). The study employs event-related potential analysis to examine neural correlates of response inhibition across weight status groups.

Participants

57

Channels

128 (egi-geodesic)

Size

23.1 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset comprises EEG recordings from twelve participants performing three learning tasks with varying reward contingencies. Participants learned cue-response mappings for colored shape stimuli with feedback validity manipulated across conditions (50% for low-value cues, 80% for high-value cues). The study investigates how average task value influences learning and neural processing during reinforcement learning.

Participants

12

Channels

31 (10-10)

Size

4.00 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset contains electrophysiological recordings from rat somatosensory cortex using DISC (Distributed Intracortical Silicon Electrodes) microelectrode arrays during whisker stimulation. Anesthetized rats received air puffer stimulation to individual whiskers while neural activity was recorded, providing validation data for DISC technology in primary sensory cortex.

Participants

8

Size

188 GB

Version

vv1.0.0

Updated

Jul 10, 2026

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

vv1.0.0

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

vv1.0.0

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

vv1.0.0

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

vv1.0.0

Updated

Jul 10, 2026