Discover datasets

This mobile brain body imaging (MoBI) dataset comprises EEG recordings from 18 subjects performing a gait adaptation task on a treadmill. Participants were instructed to synchronize their stepping with an auditory pacing stimulus and adapt their gait parameters (step length and rate) in response to tempo shifts. The dataset provides multimodal neurophysiological data during dynamic motor behavior, enabling investigation of neural mechanisms underlying auditory-motor coupling and gait adaptation.

Participants

20

Channels

108 (10-05)

Size

32.0 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset contains anonymized raw magnetoencephalography (MEG) recordings from 23 healthy adult participants performing an n-item delayed temporal reproduction task, designed to probe working memory for temporal durations. Alongside task MEG data, the dataset includes EOG and ECG recordings, digitized sensor and fiducial coordinates, a resting-state MEG recording, and individual high-resolution structural MRI scans for source reconstruction. The data support research on neural dynamics underlying working memory, auditory processing, and motor responses in the healthy adult brain.

Participants

24

Citations

1

Size

136 GB

Version

v1.0.0

Updated

Aug 19, 2026

Imported from OpenNeuro ds004850

Participants

1

Channels

64 (10-10)

Citations

1

HED

v8.1.0

Size

78.9 MB

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

EmoEEG-MC is a multi-context emotional EEG dataset comprising 64-channel EEG and peripheral physiological recordings (PPG, GSR) from 60 participants exposed to video-induced and imagery-induced emotional stimuli. Seven emotion categories (joy, inspiration, tenderness, fear, disgust, sadness, neutral) were evoked and validated through subjective reports, enabling investigation of cross-context emotion decoding. The dataset supports research on neural mechanisms of emotion and generalization of affective computing models across contexts.

Participants

60

Channels

64

Citations

3

Size

70.4 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains electrocorticography (ECoG) recordings from three cohorts of C57BL/6 mice examining how transcranially delivered diagnostic ultrasound (tDUS) modulates cortical responses to a blinking light stimulus. Mice were exposed to combinations of tDUS and light stimulation, with electrodes targeting visual and somatosensory cortices, to investigate ultrasound's potential to intentionally modulate brain activity for future clinical and therapeutic applications.

Participants

20

Size

8.42 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises intracranial electrocorticography (ECoG) recordings from 9 epilepsy patients implanted with grid, depth, and strip electrodes (1,330 electrodes total), collected while participants listened to a 30-minute naturalistic story containing over 5,000 words. It provides raw and minimally preprocessed (high-gamma band) neural data along with aligned auditory stimuli, word-level transcripts, and linguistic features spanning low-level acoustics to large language model embeddings. The dataset is intended to support research on natural language comprehension using high-fidelity invasive recordings and includes tutorials replicating prior findings.

Participants

9

Citations

4

Size

14.4 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises raw 64-channel EEG, ECG, PPG, and behavioral data collected from 30 healthy young adults during resting-state and verbal working memory tasks. Participants completed a digit-span serial recall task under four stimulus presentation modes (simultaneous, fast, fast+delay, and slow sequential), enabling investigation of neural and physiological correlates of encoding, maintenance, and retrieval. The dataset supports research on working memory load classification and the relationship between oscillatory brain activity, autonomic signals, and behavioral performance.

Participants

30

Channels

63 (10-10)

Citations

5

Size

41.4 GB

Version

v1.0.0

Updated

Aug 19, 2026

The YOTO (You Only Think Once) dataset is a human electroencephalography resource comprising high-resolution EEG recordings from 20 participants performing multisensory perception and mental imagery tasks. Signals were acquired at 1000 Hz sampling rate during exposure to unimodal (visual and auditory) and multimodal stimuli, with participants providing subjective vividness ratings. Technical validation through event-related potentials and power spectral density analyses confirmed distinct neural responses across stimulus conditions, supporting applications in neural decoding, perception, and cognitive modeling.

Participants

20

Channels

30

Size

9.91 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset contains behavioral and EEG data from twenty-one participants who learned to perform two drumming sequences (AABA and AAABAA) at three tempos (60, 100, and 150 bpm) using keyboard responses. Trial-by-trial visual feedback indicated timing accuracy relative to an adaptive response window, allowing investigation of motor learning and timing control. The dataset includes detailed event coding for stimulus conditions and feedback types across trials.

Participants

21

Channels

31 (10-10)

Citations

1

Size

4.77 GB

Version

v1.0.0

Updated

Aug 19, 2026