Discover datasets

This dataset contains electroencephalography (EEG) recordings from a study investigating the illusion of agency over electrically-actuated bodily movements. The research examines how individuals perceive control over movements induced via electrical muscle stimulation, contributing to the understanding of the sense of agency in human-computer interaction and body perception. Data were collected from human participants and organized according to the Brain Imaging Data Structure (BIDS) standard.

Participants

23

Channels

62 (10-10)

Size

98.0 GB

Version

v1.0.0

Updated

Aug 19, 2026

…Naming is Shaped by Early Facilitative and Late Compensatory Neural Interactions: An…

Participants

108

Citations

1

Size

17.3 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains EEG recordings from participants performing a novel instruction-following task and an accompanying 1-back localizer task, designed to investigate how complex task instructions are represented and implemented in the brain. Each participant completed a single session including 16 blocks of the main instruction-following task, requiring integration or selection of visual features across sequential instruction screens, and 8 blocks of a localizer task. The dataset is intended to support research on instruction-based cognitive control and rule representation.

Participants

41

Channels

63 (10-10)

Citations

5

Size

57.7 GB

Version

v1.0.0

Updated

Aug 19, 2026

…We introduce the “Podcast” electrocorticography (ECoG) dataset for modeling neural activity supporting…

Participants

9

Citations

4

Size

14.4 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains EEG recordings from 23 participants performing a passive viewing task involving partially occluded and uncovered visual scenes containing varying numbers of game pieces. The study investigates how the brain processes numerosity information under conditions of occlusion and disocclusion. Participants viewed scenes with 4 or 32 initially visible game pieces, followed by uncovering to reveal different numbers of additional pieces, across 640 trials.

Participants

23

Channels

60 (10-10)

Size

28.7 GB

Version

v1.0.0

Updated

Aug 19, 2026

…whether seen touch evokes overlapping neural representations with the first-hand experience…

Participants

40

Channels

64

Citations

11

Size

172 GB

Version

v1.0.0

Updated

Jul 10, 2026

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on003703-blue…

Participants

34

Citations

1

Size

195 GB

Version

v1.0.0

Updated

Jul 10, 2026

Beetl2021-A is a preprocessed motor imagery EEG dataset derived from the BEETL Competition 2021 (NeurIPS Task 2), comprising 63-channel, 500 Hz recordings from healthy subjects performing a four-class motor imagery task (rest, left hand, right hand, feet) during an online BCI racing game (Cybathlon2020IC). The dataset was designed to benchmark transfer learning and domain adaptation methods for subject-independent, cross-dataset EEG-based brain-computer interfacing.

Participants

3

Channels

63 (10-10)

Citations

2

HED

v8.4.0

Size

2.17 GB

Version

v1.0.6

Updated

Aug 20, 2026

…for the study 'A common neural mechanism underlies experiences of passage of…

Participants

42

Channels

63 (10-10)

Size

29.6 GB

Version

v1.0.0

Updated

Aug 18, 2026

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on003694-blue…

Participants

28

Citations

3

Size

218 GB

Version

v1.0.0

Updated

Jul 10, 2026