Discover datasets

This dataset comprises simultaneous EEG, fMRI, and diffusion-weighted imaging (DWI) recordings from 28 healthy adults performing a sustained attention gradual-onset continuous performance task (gradCPT), along with resting-state, checkerboard, and imagery task data. The dataset supports multimodal investigation of sustained attention and its neural correlates using combined electrophysiological, hemodynamic, and structural connectivity measures.

Participants

28

Channels

63

Citations

1

Size

680 GB

Version

v1.0.0

Updated

Aug 19, 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 recordings from a visual working memory task presented in virtual reality, where participants remembered object details cued by either a social (avatar) or non-social (stick) agent. The study investigates how social versus non-social cues modulate neural signatures of working memory, with cue validity (congruent vs. incongruent) manipulated across trials. Raw and preprocessed EEG data are provided alongside behavioral performance metrics and detailed event codes for memory encoding, maintenance, and retrieval phases.

Participants

47

Channels

59 (10-10)

Citations

5

Size

60.9 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset contains behavioral events and electrophysiological recordings from a hybrid spatial-navigation and free recall experiment conducted at the University of Pennsylvania (2021-2022). Participants performed a virtual courier task delivering items across a town, followed by recall testing. The experiment comprised two phases: read-only sessions for generating classifier training data, and closed-loop sessions where stimulus presentation timing was optimized based on real-time neural predictions of memory encoding. The dataset supports investigation of spatial memory dynamics and the efficacy of classifier-based closed-loop stimulation for memory enhancement.

Participants

34

Channels

128 (biosemi)

Citations

5

Size

1.30 TB

Version

v1.0.0

Updated

Jul 10, 2026

A preprocessed EEG dataset comprising motor imagery recordings from 14 healthy participants performing imagined right-hand tapping, left-hand tapping, and rest tasks. The dataset contains 1,665 trials acquired at 1024 Hz using a 19-channel montage with standard 10-20 electrode placement. Data have been preprocessed with ICA artifact removal and frequency filtering, and include annotations for motor imagery classification and brain-computer interface applications.

Participants

14

Channels

19 (10-20)

Citations

9

HED

v8.4.0

Size

1.23 GB

Version

v1.0.2

Updated

Aug 18, 2026

Participants

8

Citations

6

Size

7.74 GB

Version

v1.0.2

Updated

Jul 10, 2026

This dataset comprises EEG recordings from participants performing go-nogo categorization and detection tasks across two recording sessions. Participants viewed briefly presented images (20 ms) and responded according to task-specific rules: lifting a finger for target stimuli (go response) or maintaining button press for non-targets (nogo response). The dataset includes two complementary tasks—animal categorization and image recognition—with systematic manipulation of stimulus presentation and response requirements, providing a rich resource for investigating event-related potentials and decision-making processes.

Participants

14

Channels

31 (10-20)

Size

9.22 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises EEG recordings from 15 healthy subjects performing six different upper limb movements (elbow flexion/extension, forearm supination/pronation, hand open/close) and rest conditions in both movement execution and motor imagery modalities. The study investigates neural encoding of individual upper limb movements using low-frequency EEG signals (0.3-3 Hz) and achieves classification accuracies of 55-87% for executed movements and 27-73% for imagined movements. Source localization analysis identifies discriminative movement information in premotor areas, primary motor cortex, somatosensory cortex, and posterior parietal cortex, with applications toward non-invasive control of motor neuroprostheses and robotic arms.

Participants

15

Channels

61 (10-05)

Citations

94

HED

v8.4.0

Size

34.0 GB

Version

v1.0.3

Updated

Aug 18, 2026

An EEG dataset of imagined speech from 15 healthy participants comparing traditional cue-based and gamified paradigm designs for brain-computer interface applications. The dataset comprises 1,800 trials of four Spanish directional commands recorded at 500 Hz from 24 electrodes using the mBrainTrain Smarting system. This derivative dataset enables systematic evaluation of paradigm design effects on imagined speech decoding performance.

Participants

15

Channels

24 (10-10)

Citations

1

HED

v8.4.0

Size

1.52 GB

Version

v1.0.3

Updated

Aug 18, 2026

A large-scale longitudinal dataset of sensorimotor rhythm-based brain-computer interface (BCI) training in 62 healthy adults. The dataset comprises over 600 hours of EEG recordings across 598 sessions with more than 250,000 trials of motor imagery tasks (left hand, right hand, both hands, and rest). This resource enables investigation of BCI learning dynamics and algorithm development for non-invasive neural control applications.

Participants

62

Channels

60 (10-10)

Citations

59

HED

v8.4.0

Size

722 GB

Version

v1.0.4

Updated

Aug 18, 2026