Discover datasets

A collection of electroencephalography (EEG) recordings from 15 students (8 male, 7 female, aged 21-23) performing essay-writing tasks. The task was designed to assess cognitive conditions such as creativity, memory, and critical thinking under different generative AI interaction conditions. The dataset supports studies of brain connectivity during student learning processes with Gen-AI.

Participants

15

Channels

14 (other)

Size

1.17 GB

Version

v1.0.0

Updated

Sep 8, 2026

This derivative dataset redistributes, unchanged, 20 per-patient feature tables computed from the Freiburg intracranial EEG database for epilepsy analysis. Each row is a 2-s sliding window (1-s step) with 1080 univariate and bivariate features, extracted from six electrodes (three in the epileptic focus, three outside it) across six frequency bands. Windows are labelled as pre-ictal, ictal, post-ictal or inter-ictal, so the tables can be used to train machine-learning models for seizure detection. No raw recordings are included.

Participants

20

Size

13.9 GB

Version

v1.0.0

Updated

Oct 8, 2026

Multimodal dataset of 31 participants watching five short educational videos while EEG, ECG, EOG, gaze, pupil size, blinks, saccades, and head motion were recorded. Each participant completed an attentive session, in which factual questions followed each video, and a distracted session, in which they silently counted backwards. Experiment 2 uses an incidental learning design, so participants did not know in advance that they would be tested. Questionnaire data, including stimulus-related questions and the ASRS adult ADHD checklist, are included.

Participants

31

Channels

64 (10-10)

Size

5.25 GB

Version

v1.0.0

Updated

Jun 3, 2026

Experiment 4 of the Brain, Body, and Behavior Dataset (BBBD) contains multimodal recordings from 43 participants who watched short educational videos across two sessions. In Session 1 (attentive), participants watched instructional videos with focus. Participants were instructed to watch 3 videos in one attentive condition and 3 different videos in a second attentive condition, and were tested on the videos in the second condition, answering 11 to 12 factual multiple-choice questions after each video. In Session 2 (distracted), the videos were repeated while participants silently counted backwards, and no questions were asked. EEG, EOG, ECG, respiration, pupil size, gaze, and head position were recorded, along with questionnaires including the ASRS adult ADHD checklist.

Participants

43

Citations

4

Size

5.12 GB

Version

v1.0.0

Updated

Jun 17, 2026

This derivative dataset repackages the authors' public Dryad release of phase-synchronization and detrended fluctuation analysis (DFA) results computed from resting-state SEEG (68 drug-resistant focal epilepsy patients) and MEG (52 healthy subjects, 192 sessions). It includes per-patient complex phase-locking value matrices, DFA exponents, and contact masks, along with group-level MEG and simulated hierarchical Kuramoto model data. The data support the finding that brain criticality predicts individual levels of inter-areal synchronization. Raw recordings are not included.

Participants

68

Size

3.78 GB

Version

v1.0.0

Updated

Oct 8, 2026

Resting-state, eyes-closed scalp EEG recordings from 88 participants: 36 with Alzheimer's disease, 23 with frontotemporal dementia, and 29 healthy controls. Recordings were acquired in routine clinical conditions with a 19-electrode 10-20 montage, and cognitive status was assessed with the MMSE. The dataset includes raw recordings and preprocessed, denoised derivatives, supporting research on EEG-based dementia detection and classification.

Participants

88

Channels

19 (10-20)

Citations

96

Size

5.38 GB

Version

v1.0.0

Updated

Jun 20, 2026

Multimodal dataset of 29 participants watching six educational videos under two conditions: an attentive session with intentional learning and subsequent factual questions, and a distracted session with a silent backward-counting task. Recordings include EEG, EOG, ECG, gaze, pupil size, blinks, saccades and head position. Questionnaires (stimulus knowledge questions and the ASRS adult ADHD checklist) are provided. The dataset supports research on attention and learning from video.

Participants

29

Channels

64 (10-10)

Size

7.47 GB

Version

v1.0.0

Updated

Jun 3, 2026

Infant EEG recordings collected while infants viewed 200 object images presented in rapid visual streams. The dataset supports investigation of the early development of visual object representations and includes analysis code for preprocessing, epoching and representational similarity analysis (RSA).

Participants

42

Citations

7

Size

12.6 GB

Version

v1.0.0

Updated

Jun 26, 2026

FOODEEG is an open dataset of electroencephalographic (EEG) and behavioural responses to food images from 117 participants. In one session, EEG was recorded during a food categorisation task in which participants judged images as healthy, tasty, or something they were willing to eat. In a second session, participants completed a food go/no-go task, a paired choice task, and questionnaires on dietary style and motivation. The dataset also includes raw and cleaned EEG data and normative ratings of the food stimuli from online samples.

Participants

117

Size

91.1 GB

Version

v1.0.0

Updated

Jun 29, 2026

A BIDS-formatted derivative of the OpenBMI SSVEP EEG dataset (Lee et al. 2019), converted via the MOABB framework for standardized BCI benchmarking. It contains 62-channel EEG recorded at 1000 Hz from 54 participants over two sessions, with a four-class steady-state visually evoked potential paradigm (21,600 trials of 4 s each). The data support analysis of SSVEP-based brain-computer interfaces and BCI illiteracy.

Participants

54

Channels

62 (10-05)

Citations

101

Size

72.4 GB

Version

v1.0.8

Updated

Oct 8, 2026