Discover datasets

This dataset comprises multimodal physiological recordings from 23 healthy adult participants collected during naturalistic smartphone interaction and standardized video viewing conditions. Simultaneous EEG (64-channel), eye-tracking, photoplethysmography (PPG), and galvanic skin response (GSR) data were acquired, synchronized via hardware TTL pulses. The dataset supports research into physiological and neural correlates of smartphone use and passive video viewing.

Participants

23

Channels

64 (10-10)

Citations

1

Size

6.12 GB

Version

v1.0.0

Updated

Aug 18, 2026

…copy-spell 'PATTERN RECOGNITION MACHINE LEARNING' (36 characters). Each character received 5…

Participants

54

Channels

62 (10-05)

Citations

100

HED

v8.4.0

Size

132 GB

Version

v1.0.4

Updated

Aug 18, 2026

This dataset comprises event-related potential (ERP) recordings from 13 healthy subjects performing a visual matrix speller task using a calibrationless brain-computer interface approach. The study introduces learning from label proportions (LLP), an unsupervised classification method that exploits known target/non-target stimulus ratios to enable online BCI operation without prior calibration. Subjects performed copy-spelling tasks using a 6×7 character grid across three sessions, achieving 84.5% character accuracy without labeled training data.

Participants

13

Channels

31 (10-10)

Citations

46

HED

v8.4.0

Size

5.15 GB

Version

v1.0.2

Updated

Aug 18, 2026

…A root-level `/stimuli` folder containing the facial cut-outs (JPG) of…

Participants

44

Channels

65

Size

13.4 GB

Version

v1.0.0

Updated

Jul 10, 2026

This magnetoencephalography (MEG) dataset investigates neural object representations during dynamic visual occlusion. Participants viewed objects that were either occluded or disappeared while their neural activity and eye movements were recorded. The dataset includes raw MEG data, behavioral responses, eye-tracking recordings, and preprocessed neural signals epoched relative to stimulus onset and position changes, enabling investigation of how the brain maintains object representations under conditions of visual disruption.

Participants

27

Size

258 GB

Version

v1.0.0

Updated

Jul 10, 2026

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on003751-blue…

Participants

40

Channels

128

Citations

4

Size

4.46 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

…time (TE) of 5.1ms. Facial structures were removed from T1-weighted…

Participants

35

Citations

74

Size

166 GB

Version

v1.0.0

Updated

Aug 18, 2026

FOODEEG is an open dataset of electroencephalographic (EEG) and behavioural responses to food images from 117 participants across two testing sessions. Session 1 involved a food categorisation task with continuous EEG recording, while Session 2 comprised a food go/no-go task and a food paired choice task, along with questionnaires on dietary style and eating motivations. The dataset also includes normative ratings on 22 food attributes collected from an independent online sample (N = 624), providing a rich resource for studying neural and behavioural correlates of food-related decision-making.

Participants

117

Size

91.1 GB

Version

v1.0.0

Updated

Aug 19, 2026

…Handwriting Recognition from EMG ## Overview **Dataset**: handwriting - Imagined handwriting from wrist-based…

Participants

100

Size

45.3 GB

Version

v2.0.0

Updated

Jul 10, 2026