Discover datasets

This EEG dataset investigates the neural dynamics of visual object coding across brain hemispheres. Object and word stimuli were rapidly presented (5Hz) in the left visual field, right visual field, or centrally, while participants engaged in an orthogonal red-target detection task. The dataset supports investigation of within- and cross-hemisphere object representation dynamics using frequency-tagging EEG paradigms.

Participants

20

Citations

11

Size

58.8 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises EEG recordings from 20 healthy participants performing motor imagery of handwritten letter production. Participants imagined writing ten different letters (a, d, e, f, j, n, o, s, t, v) using their right index finger in response to visual cues. The study investigates brain-computer interface applications through direct EEG classification and continuous kinematic decoding approaches, achieving classification accuracies of 26.2% for ten-letter and 46.7% for five-letter tasks.

Participants

20

Channels

60 (10-10)

Citations

12

HED

v8.4.0

Size

27.0 GB

Version

v1.0.2

Updated

Aug 18, 2026

A high-gamma EEG dataset comprising 14 healthy subjects performing motor imagery tasks (left hand, right hand, feet, and rest) recorded at 500 Hz with 128 channels. This is a BIDS-formatted derivative of the original dataset described in Schirrmeister et al. 2017, which was used to develop and validate deep convolutional neural networks for end-to-end EEG decoding. The derivative demonstrates that deep learning approaches can match or exceed traditional feature-based methods (FBCSP) while learning interpretable spectral power modulations in alpha, beta, and high-gamma frequency bands.

Participants

14

Channels

128 (10-05)

Citations

76

HED

v8.4.0

Size

31.3 GB

Version

v1.0.3

Updated

Aug 18, 2026

Imported from OpenNeuro ds005628

Participants

102

Channels

8 (10-10)

Citations

1

Size

633 MB

Version

v1.0.0

Updated

Jul 10, 2026

A longitudinal wireless subdural electrocorticography (ECoG) dataset from two fully implanted macaque monkeys (Macaca fuscata), organized in BIDS-iEEG format. The dataset comprises multiple recording sessions acquired weekly using an inductively powered wireless implant during rest and task-based conditions (pressing, reaching, listening, and sensorimotor tasks). This resource enables reproducible research in primate neurophysiology and brain-computer interface development. The dataset was independently curated and reorganized from in-house raw recordings (.bin files) using a custom BIDS converter. The original in-house raw recordings that served as the source for this BIDS-organized dataset are not publicly released. While a related version exists on OpenNeuro (ds006890), this dataset represents an independently maintained BIDS reorganization of the original in-house recordings.

Participants

2

Citations

4

Size

41.2 GB

Version

v1.0.0

Updated

Jul 10, 2026

Participants

24

Channels

64

HED

v8.4.0

Size

5.69 GB

Version

v1.0.0

Updated

Jul 10, 2026

The Brain, Body, and Behaviour Dataset - Experiment 3 is a multimodal neurophysiological dataset comprising 29 subjects across 2 sessions designed to investigate the effects of attentional state on learning from educational videos. Participants watched six educational videos under two conditions: attentive (with post-video testing) and distracted (with concurrent cognitive load), while simultaneous recordings of brain activity, cardiovascular function, eye movements, and head motion were collected. The dataset includes concurrent EEG, ECG, EOG, gaze tracking, pupil size, and head position data, along with behavioral measures including memory questionnaires and ADHD symptom assessments.

Participants

29

Channels

64 (10-10)

Size

7.44 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises high-density EEG recordings from 30 healthy, right-handed, native Chinese-speaking adults performing imagined and executed vocalization and writing tasks involving four Chinese strokes and four English letters. The factorial design crossed task mode, action, script and token identity, yielding 32 event-coded conditions across 15,360 task events. The dataset supports research into motor imagery, speech and handwriting-related neural communication signals.

Participants

30

Channels

124 (10-05)

Size

181 GB

Version

v1.0.0

Updated

Sep 8, 2026

This dataset provides complementary EEG recordings, obtained under photic stimulation with eyes open, from a cohort of individuals with Alzheimer's disease, frontotemporal dementia, and healthy controls previously described in a related open-eyes-closed EEG dataset. Recordings were collected at incremental photic stimulation frequencies (5-30 Hz) at the 2nd Department of Neurology, AHEPA University Hospital, Thessaloniki, Greece, using a 19-channel clinical EEG system. The dataset includes both raw and preprocessed (denoised) EEG data, intended to support research on neurodegenerative disease biomarkers and cognitive decline.

Participants

88

Channels

19 (10-20)

Citations

37

Size

2.11 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises EEG and behavioral recordings from a study examining the effects of transcranial direct current stimulation (tDCS) over the dorsolateral prefrontal cortex on emotion processing and regulation in lonely individuals. 120 participants completed two sessions (sham and active stimulation) involving an emotion regulation task with static social and non-social images, rated on arousal and valence. The dataset includes raw EEG, behavioral ratings, and derived ERP data, along with questionnaires assessing side effects and blinding effectiveness.

Participants

120

Channels

37 (10-10)

Size

53.6 GB

Version

v1.0.0

Updated

Aug 19, 2026